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Apr 23 2019
Artezio among the Top Software Developers in Eastern Europe According to the British Agency
The report covers 11 Eastern European countries and, according to the authors, should help businesses decide on the choice of technical partners for the implementation of complex IT projects. “It is difficult to compile a list of the very top IT outsourcing companies in Eastern Europe. However, based on several studies and tops, we can bring together information that will help you understand who are the best players on the Eastern European IT outsourcing market,” say the authors of the research.
The British agency notes that the demand for services of companies from Eastern Europe is constantly growing.
“Businesses who need outsourcing services are starting to move away from their main focus until now India or China. Eastern Europe is a shiny new outsourcing destination for those who require high-quality software development. First of all, because Eastern European IT companies guarantee a good price-to-quality ratio and a timezone that can be easily coordinated with other locations on the globe. Besides, the IT potential of outsourcing in Eastern Europe is supported by a large number of talented specialists. According to the latest data, over a million programmers work in Eastern Europe,” sum up the MAN Digital experts.
Artezio is one of the best outsourcing companies in the world according to 100 Global Outsourcing (2017, 2018) and TOP-5000 of the fastest-growing European private companies according to Inc. magazine. In 2019, Artezio was named among the best by several international analytical agencies in the United States.
Apr 17 2019
Artezio among Top Ten Best Belarusian Software Development Companies
Clutch publishes professional ratings of technology companies in various professional fields and countries. They help customers choose a competent partner for high-quality implementation of technical or business tasks. Clutch researchers analyze the situation on the development market using a patented method that takes into account not only the financial performance of software companies, but also customers’ reviews.
Artezio is one of the world best outsourcing companies according to 100 Global Outsourcing (2017) and TOP-5000 of the fastest-growing European private companies according to Inc. magazine. In 2019, Artezio was recognized by several international analytical agencies of the United States.
Apr 8 2019
What are Embeddings? How Do They Help AI Understand the Human World?
In the most primitive form, word embeddings are created by simply enumerating words in some rather large dictionary and setting a value of 1 in a long dimensional vector equal to the number of words in the dictionary. For example, let’s take Ushakov’s Dictionary and enumerate all words from the first one to the last one. Thus, the word “abacus” is converted to number 5, and the “lampshade” — to 7, and so on. The total number of words in the dictionary is 85,289. The embedding of the word “abacus” will have 85,288 zeros in all positions except the 5th one, where it will be 1, and the word “lampshade” will have zeros in all 85,288 positions except the 7th one, where it will be 1. This method of building embeddings is called unitary coding, and in the modern English literature — one-hot encoding. Any sentence in Russian can be set a sequence, more correctly from a mathematical point of view to say, a tuple of such 85,289-dimensional vectors. And then actions with words can be transformed into actions with these numerical vectors, which is inherent in the computer itself. However, it is not that simple. The first problem of applying such embeddings that you will encounter is the absence of the word for which an embedding is sought in the selected dictionary. Look at Ushakov’s Dictionary mentioned above, and you will not find such a popular word as “computer” there. It is possible to significantly reduce the likelihood of such a problem by not using a special dictionary, but numbering words in an arbitrary extensive set of texts, for example, in Wikipedia, the Great Russian Encyclopedia. Today for these purposes, special sets are created called text corpuses.
What actions over numerical equivalents of words would we like to perform and why? Probably, so that the computer itself could take any actions depending on the content of the text it has, without human intervention. However, the use of corpuses does not in itself help to derive any benefit from turning a particular text into a tuple of numbers. After all, any text in a natural language is not only a collection of words, but also carries some semantics and meaning. And the task to train a computer system to somehow understand the meaning of the text, to extract semantic information from it, is unsolvable if primitive embedding is used. Therefore, the next step in NLP was made by taking into account how often each word of a language (term) is found in a corpus and how important its appearance is in a specific text. Thus, frequency embedding emerged, in which each word, in the position corresponding to its number, is assigned a number - TF - Term Frequency, or rather the corrected frequency value - TF / IDF. If everything is obvious for the first concept: for each word in the text its number of occurrences is calculated and divided by the total number of words, the second term is more complicated. IDF - Inverse document frequency stands for the inverse (inverted) frequency of the document. It is the inversion of frequency, with which a certain word appears in the corpus of texts (documents). Due to this indicator, it is possible to reduce the weight of the most widely used words (prepositions, conjunctions, common terms, and concepts). For each term within the framework of a specific corpus, only one single IDF value is provided. The TF/IDF indicator will be higher if a certain word is used with great frequency in a specific text, but rarely in other documents. Using embeddings in the form of such vectors, for the first time it was possible to carry out an automatic semantic analysis of texts, determining the topics in the corpus and classifying texts by main topics.
There are several successfully used algorithms for such analysis. Among them are the classic LSA – Latent Semantic Analysis, LDA – Latent Dirichlet Allocation, and BTM – Biterm Topic Model. The use of such models, for example, made it possible to sort out the giant flows of emails by subject and send them according to the prescribed rules. At this stage, a powerful set of technologies began to form within NLP, called NLU - Natural Language Understanding. In the revolutionary work of Tomash Mikolov and his colleagues in 2013, it was proposed to use the hypothesis of locality: “words with similar meanings occur in the same environments” (Tomas Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States, pages 3111–3119, 2013). Proximity in this case is understood very broadly, as the fact that only matching words can stand next to each other. For example, the phrase "a wind-up alarm clock" is common to us. But we can’t say "wind-up ocean", as these words do not collocate. To obtain such properties, it is necessary to build embeddings of words in a high-dimensional vector space (but independent of the number of words). A set of 200-500 numbers matched each word, and these sets satisfied the properties of a mathematical vector space — they could be added, multiplied by scalar quantities, it was possible to find distances between them, and each such action with number vectors made sense as some action on words. The most interesting thing that resulted in multidimensional space is the transfer of many semantic relations of words to the relations of the corresponding vectors. From the point of view of mathematics, one can speak of a homomorphism of a natural language and a multidimensional vector space. All publications and lectures on embeddings today are illustrated by a famous image describing what was said.
We can see that the semantic relation MAN ~ WOMEN for embeddings of these words is reduced to the presence of a certain vector of difference between them, which is surprisingly preserved for the equivalent semantic relation UNCLE ~ AUNT, KING ~ QUEEN. This allows writing down a simple mathematical relationship: WOMAN-MAN = QUEEN-KING. Let's make a simple transformation of this formula: WOMAN-QUEEN=MAN-KING. It looks fair: a woman without the title of queen is the same thing as a man without the title of king. But the second image explains that embeddings retain the “one” ~ “many” relationship. Mikolov called the method of obtaining such embeddings as word2vec. It is based on the use of a probabilistic assessment of the joint use of word groups and the neural network that is self-learning on the corpus of texts. The idea turned out to be fruitful and soon we saw the construction of even more sophisticated models for embeddings of both individual words and sentences, as well as whole documents. This is the GloVe model developed at Stanford, fastText developed by Facebook, and doc2vec, a model that displays a whole document in a numerical vector. In recent years, embeddings are obtained using very complex models of deep learning in order to preserve ever more subtle natural language relations in the properties of vectors. The results are so impressive that experts have noted the emergence of models such as ELMo and BERT as a new era of embeddings. ( Jay Alammar, The Illustrated BERT, ELMo , and co. (How NLP Cracked Transfer Learning).
Understanding the complexity of models of this level, I’d like to describe how embeddings in the popular model BERT, developed by Google AI Language in 2018, are built today.
It is based on the neuroarchitecture called Transformer that has an attention mechanism that learns contextual relations between words (or sub-words) in a text. Each word is encoded with a unique token and the sequence of words is led to the so-called recurrent neural network to predict some numerical multidimensional vector – embedding. In BERT, the Transformer architecture is not fully used: only the input network, called an encoder.
Before feeding word sequences in BERT, 15% of the words in each sequence are replaced with a [MASK] token. The model then attempts to predict the original value of the masked words based on the context provided by other, non-masked, words in the sequence. From a technical point of view, the prediction of the output words requires:
- Adding a classification layer on top of the encoder output
- Multiplying the output vectors by the embedding matrix, transforming them in the vocabulary dimens
- Calculating the probability of each word in the vocabulary using softmax – the function that normalizes the activation values of the output layer of the neural network
BERT can predict not only words, but also the whole sentences. In the process of training, the BERT model receives pairs of sentences as input and learns to predict whether the second sentence in a pair is the subsequent sentence in the original document. During training, 50% of the inputs are a pair in which the second sentence is the subsequent sentence in the original document, while in the remaining 50% a random sentence from the corpus is selected as the second sentence. It is assumed that the random sentence will be disconnected from the first sentence.
BERT can be used for a wide variety of language tasks, adding only a small additional layer of neurons to the core model.
- Classification tasks such as sentiment analysis are performed similarly to the Next Sentence classification, adding a classification layer on top of the Transformer output for the [CLS] token.
- In Question Answering tasks, the software receives a question regarding a text sequence and should mark the answer in the sequence. Using BERT, a Q&A model can be trained by learning two additional vectors that mark the beginning and the end of the answer.
- In Named Entity Recognition (NER), the model receives a text sequence and is required to mark the various types of entities (Person, Organization, Date, etc.) that appear in the text. Using BERT, the NER model can be trained by feeding the output vector of each token into the classification layer that predicts the NER label – geographical name, name, company name, etc.
The results of implementing BERT embeddings are impressive. In addition to the usual assessments of the tone of the text – positive and negative statements, the computer began to determine the presence of sarcasm in the text as well as detect lies and fear. These are the deep features of human psychology that can be turned into algebraic relations of embeddings.
Embeddings have opened up the possibility of simultaneously operating in different natural languages. After all, if we construct the space of sentences and words embeddings in English and Russian, then the same embeddings should correspond to the same semantic concepts. Such a combination should be carried out in the process of teaching a neurotranslator. Then the translation of the new text from English will be reduced to its embedding and decoding in the words of the Russian language, which you need to translate. There are known search engines that accept a request in one language and search for information in any language using a reverse index based on embeddings.
Artificial intelligence (AI) is open to a mass of tasks, not only to understand what is said by a person and to choose in advance declared possible solutions based on them, but also to build solutions. The achievement of such goals in AI systems is carried out using architectures with many neural networks, genetic algorithms, trees of choice, and others. All of them, as a rule, work efficiently if data is represented as numerical vectors. This means that all data for artificial intelligence should be represented as embeddings. The experience of word embedding in NLU that we have just described allows assuming that homomorphic transformations should be performed with other entities that AI operates with, keeping in mind basic relations that exist objectively in the set of entities used. Recently, several papers have appeared on embeddings of entities different from linguistic studies. However, one can doubt here if the both artificial intelligence and natural intelligence need to know some entities, other than those expressed by means of a language, either natural or artificial, but perceived by a man. In the end, the relations between entities are described by means of a language, thus, they can be treated equally along with the relations of words, sentences, and texts. It suggests that the embedding path for any entities that AI must operate with is promising and correct.
Let’s have a look at a number of examples. The social platform Pinterest has created and uses 128-dimensional embeddings for entities called Pin-pages or images from the Internet and entities of Pinner users. A method similar to word2vec, the so-called Pin2Vec, was developed and used to reflect the context of each user's and each Pin's relation.
The author of this article conducted research on the use of embeddings to represent the legal space – articles of the criminal code, civil code, labor code, court decisions together with the presentation of narratives (narrative texts) describing some facts. Already today, we have managed to build a high quality AI that can replace the court system for qualifying case materials at the stage of drafting a court decision: which normative acts are violated in describing the facts presented by the narrative. You will find an interactive acquaintance with the world of three-dimensional space with points corresponding to both normative acts and random textual narratives. If the link for any reason is inoperable, then have a look at the following image.
The number of publications on the use of embeddings in the development of AI systems is increasing. In general, it is already possible to say that a fairly universal approach can be the construction of a textual description of any state of the world that AI sees and the further construction of a vector numerical image for this text, embedding in the usual sense. This approach is based on the idea that AI must “think” in words, in a language form. Another idea is based on the assumption that the states of the world can be transformed into embeddings bypassing a verbal description, for example, images or audio recordings can be immediately transformed into multidimensional vectors. If you train a model for such embedding in conjunction with texts, AI will be able to operate both with homogeneous data and pictures, and with words and sounds. Recently, Dan Gillick at Google, in his lecture at Berkeley, proposed building AIs to search for information by placing all different objects/entities, regardless of whether they are composed of text, images, video, or audio in the same vector space. Based on this principle, AI will be able to answer questions asked in various languages, illustrations and sound recordings, in writing or orally. What dimensions of embeddings will be required for such universal descriptions and whether the structure and capacity of the multidimensional vector space is sufficient to keep all the necessary complexity and diversity of the world in which AI should work is a matter of current and future research.
Apr 2 2019
Artezio to Discuss Healthcare Digital Transformation with Experts in Berlin
Traditionally, DMEA guests are invited to attend special events, an exhibition and lecture sections that help reveal important topics and problems in healthcare. This year, among the topical issues at the exhibition are artificial intelligence and blockchain. Artezio has extensive experience in developing healthcare projects, and it will present its own expertise to DMEA attendees within the scheduled meetings.
If you would like to hold a business meeting with Artezio representatives at DMEA, please send a request to Anastassia.Panshyna@artezio.com
Apr 1 2019
Artezio Among Top 20 Best Software Development Companies
Artezio ranked among the top 20 best companies. The overall score based on 6 criteria was 9.51 points.
Artezio has been on the international market for over 19 years and has implemented more than 1000 custom software development projects in many industries, including finance, logistics, healthcare, retail, media, and so on. Artezio's customers include brands like Sencha, Microsoft, Raiffeisen Bank, Siemens, and Pepsico.
Mar 31 2019
Artezio to Share its Blockchain and Machine Learning Expertise at BioIT
Artezio closely monitors technology trends in healthcare and takes part in all major events that are devoted to this field. In particular, the company already met with experts and business representatives at BioIT in January this year. New meetings with BioIT attendees in Boston will allow Artezio to present its latest experience in the use of blockchain and ML technologies in various fields, including healthcare, to colleagues and private companies.
“The BioIT conference is an opportunity to share Artezio's key expertise in developing effective solutions for medical companies in the United States. Offering the latest technologies, we aim to encourage not only the technological development of the US healthcare sector, but also improve customer service and quality in medical clinics,” says Dmitry Rodionov, the Head of Artezio office in the US.
Artezio’s experts highly evaluate the potential of process automation developments in healthcare based on blockchain and ML. The company has expertise in this area and conducts its own research in the field of artificial intelligence and other advanced technologies.
Mar 26 2019
Speech Recognition: Prospects for Use
Development of voice recognition technologies
Speech recognition is not a new technology. The first speech recognition device appeared in 1952. In 1963, Septrons, the devices that could perform voice commands, were introduced in the United States. They were successfully used in the defense industry, allowing pilots of combat helicopters to use voice control. In mass markets and in large commercial projects, voice solutions became popular after the appearance of smartphones and the spread of voice interfaces with voice support in mobile phones, IoT devices, fitness gadgets, and car devices.
Then, banks and large enterprises became interested in speech recognition. For example, financial institutions are still considering the possibility of authenticating customers by voice. Perhaps in the future, to sign a payment document or approve a transaction, you’ll simply just have to call the bank and talk with the automated system. Developers minimized voice recognition errors by up to 2%, a record number ensuring high reliability.
Voice technologies are applied not only in banks, but also in other business processes. For example, in client services for the sale of goods or services and technical support. There, voice recognition technology helps to simplify the performance of various operations. For example, online customers may spell their credit card information to the system to make a purchase. The recognition accuracy of a single digit is 99.1%, the accuracy of the text information recognition on a card is 93.3%.
A similar voice recognition technology is also used for call centers. With its help, it is possible to ensure recognition of a user's request, routing to the necessary employee, and performing simple actions through the voice menu.
Today, voice systems do a good job with deciphering distinct speech during such tasks as generating television subtitles or translating voice to text for messaging. At the same time, the recognition systems are still not ready for simple hearing tests.
In the near future, speech recognition could be an important technology in conjunction with actively developing global satellite Internet projects. In conditions of a limited communication channel, people could make voice calls in the form of a text, which would then turn back to a voice on the receiving side.
From the point of view of machine learning, speech recognition consists of many stages. First of all, noise and interference must be removed from the original audio stream. In the cleared speech recording, phonemes are distinguished – perceptually distinct units in a language, which then can be assembled more or less clearly into the text of words, phrases, and sentences. For greater accuracy, other data sources are used, such as the image of the speaker’s face, or other voice recordings with known transcripts.
Recognizing the meaning of what is said is a separate big task. For this reason, the role of voice assistants is still limited to simple commands. Understanding the meaning has a much greater complexity and is currently implemented only in individual components, such as an object, emotion, or tonality.
The reverse process, speech synthesis, thanks to machine learning, allows you to quickly and efficiently generate speech using specified samples of real people’s voices. Already today there are startups that allow substituting voices for dubbing texts with voices of historical personalities.
As for the language support, English and Chinese dominate speech recognition technologies. This is due to the volume of investments in the speech recognition technology from Chinese companies and the US. However, there are free solutions, voice engines, which allow other companies to be included in the technology race. Mozilla DeepSpeech and, a completely open source solution, Kaldi are among the open solutions.
However, in order to add support for a language other than English or Chinese to free solutions, you need about 10 thousand hours of speech for training. And it should be marked data and the recording of various dialogues – only then acoustic language models can be well-trained.
Difficulties in the development process
There are many speech recognition services today and most of them are focused on English speech recognition. The main problem is the lack of additional mechanisms for the interpretation of recognition, which is why such systems provide several options, one of which may be correct, but it may not be the most probable one offered by these services.
As a result, people are uncomfortable using these technologies since they have to speak unnaturally and slowly. If the program can’t recognize what has been said, then the text need to be repeated again and again, which can be annoying. A person gets the feeling the technology is flawed; this negative effect could influence the success implementation factor if people refuse to communicate with the robot. Moreover, for those tasks where it could be applied, often, the alternative is low-skilled human work, where the cost of work may not be so high that it would be beneficial to apply.
Developers today lack user experience on how to properly build a dialogue between a person and a machine. For example, an interesting pattern can be noted – adults conduct a dialogue with the robot as with, to put it mildly, a silly person. In response to questions, they make a lot of explanations, start speaking slowly, hence there are various problems in building a dialogue, although they behave in the usual way with live operators having the same dialogue. In this case, children behave as naturally as possible, and they do not have problems in communication.
Speech recognition technologies are actively developing. Tasks that were previously considered impracticable have already been solved. For example, the voice recognition technology with simultaneous conversation has already been implemented; smooth speech synthesis is applied, suitable for the level of human speech. Experts believe that in the next three years, significant technological growth associated with speech recognition will be observed. As a result, there will be many solutions with voice technologies in the field of business automation.
Speech recognition, voice biometrics and voice control have become reliable tools, thanks to the development of the technologies. For most tasks, speech recognition copes with its work. Difficulties remain with the recognition of telephone conversations or the separation of mono-recordings in stereo, but there is progress in this direction as well.
Today’s popular voice assistants are unlikely to become so massive, as it was thought a year ago, but the task of processing people’s call recordings remains relevant and will gain value in the service economy.
Mar 21 2019
Artezio Joins Two New Business Platforms in the US
Dmitry Rodionov, Country Manager Artezio USA: “We would like to become active members of the business and tech communities in the US to be able to share experiences, exchange information, take part in educational initiatives and finally establish trade relations with other members of the local market.”
“Our goal is to support the growth of US technology companies by applying our 19 years of expertise in the technology and custom software space. Partnership with industry-specific associations and technology hubs allows us to be directly involved in such initiative. We are sincerely happy to be a part of the technology council of New Jersey as well as PRCC and are grateful for the huge support from these organizations.”
Today Artezio USA is an official R&D partner to such incumbents as Microsoft, Amazon and SalesForce, as well as to various ISV’s in the mid-market space.
“We are open to cooperation with all industry-specific companies that are interested in applying the latest technologies,” added Pavel Adylin, Artezio Founder and CEO.
Mar 18 2019
Blockchain in the Financial Sector: Today and Tomorrow
What is blockchain? It is a distributed database that contains information about transactions carried out by system participants. Its main feature is the exclusion of the human factor which ensures a high level of trust. Today retail and investment banks, brokerage firms, and payment networks actively use this technology. Payment transactions now can be automated, which means intermediaries can be excluded while any system participant verifies the authenticity of a transaction. Additionally, blockchain could help in securities management, and it could be used in the development of payment systems using digital currencies, which would greatly simplify the interaction between central banks.
The main opportunities blockchain opens up in the financial sector are reducing bureaucratic costs, minimizing corruption, increasing security of operations through complex mathematical algorithms and special cryptographic programs, and eliminating unnecessary or redundant operations.
Blockchain is based on the principle "promised — fulfilled” and a violation of this principle is impossible. Due to the fact that the entered data cannot be changed, blockchain becomes an effective financial tool. Additional benefit from implementing blockchain solutions is trust in the information and reliability of its storage, which is especially valuable in the financial sector. Blockchain for financial market participants is not only a path to new niches, but also a step towards new market relations based on the transparency and impossibility of cheating. Even if certain blockchain developments do not replace all their standard counterparts, they still provide an overall opportunity for improvement in this sector.
International payments are still the main and most widely recognized implementation of blockchain in the financial sector. Such technology allows payments to be made in seconds, with minimal costs. Unlike plastic debit cards and SWIFT transfers, blockchain services automate currency control procedures and search for the most profitable transaction route. Over 200 companies are already connected to the payment ecosystem Ripple, among them banks and even the international money transfer service Western Union. The speed of settlements in turn accelerates international trade and makes financial transactions available to ordinary citizens. And for a number of large companies and entire countries, blockchain payments allow the opening of additional business channels.
In fact, the reason why blockchain is still very popular, but not the most used technology, is quite simple. There is the possibility that it is a technology fad that will fade in fintech, similar to what happened with WiMax. The wireless data transmission technology did not become widespread, and LTE replaced it.
Blockchain also has a successor—Tangle, a faster technology that is designed based on the widespread use of the Internet of Things. It is possible that blockchain in its current technological form will not become widespread in the financial sector, and other solutions will be applied for safe data storage.
Blockchain in the Financial Sector of Tomorrow
In the coming years, the spread of blockchain technology will most likely be relevant in the field of financial systems and insurance. Experts believe that the first thing to do is to implement blockchain in all publicly verifiable transactions, contracts, registries and decision-making systems, secondarily, in multilateral operations. At the same time, the introduction of blockchain in projects where control is required for unstructured, unparsed information is not justified.
For example, banks invest too many resources in support of processes that aren’t directly linked to profits, so fintech is focused on finding new tools to influence fundamental indicators. Blockchain could become a cheap solution for banks.
If we talk about the disadvantages associated with this technology, it is necessary to highlight the market demand for experts in this field as well as a small number of completed business cases. Financial institutions are very cautious about the introduction of blockchain projects. For fintech, the risks associated with deficiencies in consensus algorithms and incorrectly written code of smart contracts could be quite expensive. During a bank transfer it is possible to dispute the transaction, but for the time being, it is not clear how to implement such a process in blockchain.
It is worth mentioning the data protection issues as well. Blockchain has been around for about 10 years, and data protection is one of the most pressing issues in this area. Entrusting finance to algorithms, financial organizations want to make sure that they are reliably protected from various types of attacks such as capturing decentralized nodes or selecting a cryptographic key.
Security and standardization issues are other problems hindering the implementation of blockchain in finance. Today, many countries have almost no regulatory legislation that would allow blockchain to be widely used in banks, when dealing with securities or registering transactions. Therefore, the future of blockchain in finance largely depends on legislators and regulators.
Mar 11 2019
When Will the Internet of Things Become the Internet of Anything?
For technologies to be in demand by businesses, they must have a significant impact on the economy. An effective competitive strategy is to reduce costs by automating business processes. Two years ago, it was expected that there would be a revolutionary breakthrough in the area of IoT. Today, IoT is mainly used to automate logistics and track production processes. With the development of NB-IoT, new mobile sensors and devices are likely to appear, which will not be as dependent on network settings as they are now.
Those who believe that a technical revolution should take place in IoT are both right and wrong at the same time. The Internet of Things itself is a logical step in the evolution of information and communication technologies, a continuation of the logic of the automated process control system and M2M, but at a qualitatively different level. The principle of “internetization” of interaction, transferred from the regular Internet to “things” or devices, has opened up new companies, new business processes, and new business models to the world. Using the Internet of Things, artificial intelligence systems, machine learning, augmented and virtual reality in solutions and products – this is the daily technical revolution. Moreover, we often no longer notice how commonplace “connected” or “smart” things have become in the last couple of years. Barriers in yards are now opened not by duty assistants, but via a phone call. Payment information can be accessed in a few strokes on a smartphone. The temperature of a room can be changed remotely via an app. Such examples are endless. This means that the next “revolutionary” change - the transition to the “Internet of Anything,” IoA, could easily be overlooked in the future.
In developed countries, the IoT technology is no longer an innovation, moving from the innovative to everyday solutions. The most advanced developments are concentrated primarily in the industries where IoT and algorithmization can bring the effect of instant savings and fast monetization, and the industry itself is large in size. For example, agriculture or transport and logistics are full of innovations that affect ordinary people. At the same time, today there is already a question not about the creation of innovation, but its implementation on a large scale. Much of what is needed for the widespread change of established operations and actions is already there, but these technologies need to be integrated and implemented.
Evolution of LoRaWAN
The Internet of Things has evolved from the technology of the automated enterprise management system that has existed since the last century. Such costly automated enterprise management systems are currently available only to large corporations. The evolution in the design of sensors and actuators, the emergence of new communication standards and communication channels, machine-to-machine interaction, the emergence of software for connecting this infrastructure to existing systems, and other technologies, all have enriched automated enterprise management systems and made automation accessible to a large number of enterprises.
IoT is now developing, although not as fast as previously expected. Innovations occur regularly, but they are often subtle. One of the most significant breakthroughs is the distribution of LoRaWAN data transfer protocol among IoT devices. Low power consumption of LoRaWAN devices and a large communication range allow sensors and equipment to be installed in places where wires cannot be laid. For example, the infrastructure of IoT devices could be deployed even in a forest — say, for warning of forest fires.
The development of LoRaWAN networks with low power consumption of end user devices will allow IoT to become a truly Internet of Things. The presence of a publicly accessible “transmission medium” opens up the possibility for integrators and solution providers to focus directly on the hardware level (field level) and application level. As a result, the number of IoT devices themselves and the volume of processed data - archived and current - would significantly increase. Then, application of cloud computing resources, Big Data, machine learning, and neural networks at the application and services level will become more common.
The following were mentioned in the Forrester Reseach study ( published report) “10 IoT predictions for 2018” and are noteworthy. Among other things, the use of voice control systems in IoT services will increase; developers of IoT platforms, as well as those who provide services to them, will go further towards industrial or functional specialization; Blockchain technologies will be increasingly used in IoT products, and—the most troubling—cyber attacks through various “connected” devices will be among the most common and destructive.
What’s next: success or failure?
According to Software AG, about 50% of projects related to IoT fail because developers are more interested in releasing new solutions to the market that they simply do not assess possible risk factors.
Now the situation has begun to change. More and more technologies have been developed to interact with IoT. These are, above all, cryptocurrency projects. In the near future, they are expected to grow in number, and in five years, the automation of various business processes will be able to be discussed. According to expert Theo Hildjard, three stages will be completed in implementing the Internet of Things. During the first stage, individual projects that have not reached their optimum will be improved. At the second stage, the integration of all processes will be planned, in other words - digital optimization. Only at the last stage will it be possible to fully implement all the developments, create new “Internet things,” and expand the market.
We can assume that the revolution in IoT is actually taking place, it is just happening in the area of business solutions. In the consumer solutions market, IoT has hardly been developed. But within the framework of the industrial Internet of Things, the range of requests is much more diverse. The probability is high that automation in production will turn IoT into IoA.
Feb 27 2019
3 Tips for Digital Transformation in Healthcare
With that, every day there are new trends, data transmission formats, standards, regulations, and solutions for distributed databases. Healthcare faces the ongoing challenge of how to make sense of data and how to handle issues of its secure storage, processing, and exchange. With that, the question still remains, “is the risk worth the reward when using third-party solutions”?
As a custom software development company, Artezio is vendor neutral. We’ve dealt with clients who preferred to use third-party solutions, as well as those who have made a choice to build the whole system from scratch. One thing is certain for both, in order to make this decision, you need to take into account all critical aspects. Let’s look at a few examples of using third-party solutions/providers and see how they worked out.
1. TrueVault – a simple solution that allows you to become HIPAA / GDPR compliant without overhauling your entire application and migrating your infrastructure. Sounds great, right?
Especially if most of the work you need to do is on the application side, and healthcare data repository is just a part of your solution. We’ve had examples like that. One of our clients built a web application that provides a user-friendly interface for health practitioners, doctors, and caregivers. Giving them the ability to create, as well as manage medical landing pages in strict compliance with e-health standards. The app has a site wizard to design and build landing pages. It also includes a dashboard to track and manage the page's performance. Being a client/patient facing web application, it deals with a lot of PHI, which is distributed between different users. In essence, it is a React JS application built over HIPAA compliant storage, represented by TrueVault.
In another case, we used TrueVault to solve a different issue. Imagine a doctor who needs to request tests for patients on a daily basis. Some are standard, others are specialized. How frustrating can that be to make thousands of requests in various systems? How complicated can this process become due to all the required paperwork and missing pieces? What if the tests you need are in small laboratories who are not present in your EHR? Suddenly, a simple routine task becomes an overwhelming dragging torture. We were able to simplify this process for both the lab service providers and the doctors by creating an uber-like multi-tenant portal with a simple interface. The labs and lab services providers subscribe to the portal to have their services featured. Clinicians can make a request to have a set of tests done and get the results to share with their clients/patients using one single platform. The lab requests are automatically routed to participant laboratories in accordance with HL7 data transfer principles. The environment of this solution is HIPAA and GDPR compliant. It was easy to set it this way with TrueVault.
What’s in TrueVault for you?
Consider using it if you need to get a secure database for your solutions quickly. Another case would be if you have a legacy system and the task of migrating infrastructure is not suitable for your situation.
TrueVault has a plugin API which is well documented and supported. It’s pretty simple, even if your tech knowledge is limited. They also have a very educating blog with valuable tips on GDPR and HIPAA compliance. All you need is to get good UX/UI designers and developers to build your app and you’re all set.
2. Think!EHR Platform – Is a big data solution based on the latest release of OpenEHR specifications. It is designed to store, manage, query, retrieve, and exchange structured electronic health record data. All data is stored in vendor-independent archetypes and templates.
OpenEHR is a standard that describes the management and storage, retrieval, and exchange of electronic health records. It’s also a virtual community working on means of turning healthcare data from the physical form into electronic form as well as ensuring universal interoperability among all forms of electronic data.
One of our large clients needed to create an enterprise scale comprehensive EHR. The system included medical appointments scheduling capabilities and BI dashboard. The main task was to aggregate electronic information and records across healthcare system of a large city following interoperability and safety standards, automate processes, and provide efficient analytics to allow making information-based decisions.
The challenge here was in the complexity of the task and the organizational structure. Every organizational level has its own rules and follows its own procedures. It took a while to really dig into the OpenEHR solutions and capabilities they provide. We chose Think!EHR and it helped us to streamline the project and get the client going with the MVP to test it at one of the organizations in a matter of a few months. Then based on the feedback collected and the roadmap, we’ve created a modular solution covering all processes and aspects across all levels of the healthcare system. The modules include EMR and electronic documents workflow, patients record management, medical institutions and doctors information, the online appointment for patients, and complex scheduling based on the doctors’ workload.
What’s in Think!EHR Platform for you?
Consider using it if you need an enterprise scale solution and have developers to help you. It’s a complex tool so you need someone who has mastered it.
Use it if your primary focus is on electronic health records (EHR) and related systems. The platform has an array of interfaces including REST, SMART, HL7, FHIR, and IHE.XDS. One of the benefits is in the integration of external terminologies like ICD, LOINC, and SNOMED-CT.
Another advantage is the OpenEHR community where you can find a lot of answers and help. Even though it’s a complicated solution it provides unmatched capabilities for you to automate all processes. So you will need to be looking for an experienced developer to help you with that. First of all, they need to understand the principles of OpenEHR. Secondly, it’s very likely you will need someone who can customize and tailor the solution specifically to your needs.
3. SpiritARCHIVE (PACS) by Tiani is a software solution for handling, storing, printing and transmitting of medical imaging and pictures (DICOM – Digital Imaging and Communications in Medicine).
So, speaking about various data formats to deal with (documents, papers, images, test results, etc.). While it’s more or less clear with text, what do we do with pictures, scans, MRIs, CTs? We solved this task for one of our clients and SpiritARCHIVE helped us do it effectively. We built a HIS platform for unified patient records and documents workflow management. The client needed to obtain results from digital radiography, magnetic resonance imaging, computer tomography, and sonography, and get them matched as well as attached to their patient records.
Patients’ data is stored in a highly standardized and protected environment and includes DICOM images, 2D/3D objects, PDFs, JPEGs, video files (MP4, MPEG, AVI), CDA files, and other data formats. The system unifies different formats and presents them to the users on a single interface in accordance with IHE standard. It allows doctors the ability to quickly retrieve and modify patients’ records and documents. SpiritARCHIVE, in this case, enables integration of medical imaging devices – modalities, scanners, servers, workstations, printers, network hardware, picture archiving, and Communication Systems (PACS) from multiple manufacturers.
What’s in SpiritARCHIVE for you?
Consider using it if you need to store, handle, print, and transmit medical imaging (including digital images, results of digital radiography, CT, MRI, and sonography). This solution observes strict adherence to IHE criteria and it’s also compatible with systems of different manufacturers (modalities, scanners, servers, workstations, printers, and network hardware). Use it if you work with 2D and 3D objects or video files.
That’s just a couple of examples. Think about it, how often do you find yourself torn between the latest technology and the regulations in healthcare? Knowing the standards or just the technology is no longer enough anymore, is it?
Getting a consultant or a company to help you sort everything out is often viable. If you do think about it, pick someone who has already done this with different solutions. Someone who is fluent in the latest technology and familiar with the healthcare standards. Someone who can offer effective solution taking into account all these rules you have to follow and the results you would like to achieve.
We could be your guys for that. Drop us a line to firstname.lastname@example.org, let’s talk.
Feb 18 2019
A Robot Lawyer and Robot President: Considering a World Run by AI and Big Data
The concepts of robotics and artificial intelligence are often mixed in technology development forecasts. People imagine that robots will replace lawyers, clerks, and even high-ranking officials. But robots are often considered to be mechanisms allowing people to automate a particular process, while artificial intelligence is able to make major decisions. Thus, Big Data processing technology and machine learning are at the heart of the progress that will free humans from routine.
A key factor in automating professional functions would be the use of Big Data, based on which AI would make decisions. Law is one of the priority areas for the introduction of AI. Working with Big Data already allows an idea of the potential development within the legal sphere. For example, the software used for automated analysis of a large number of specific judicial precedents and world court practices could help in the prediction of a court decision for single cases. On the other hand, the analysis of a large amount of socio-economic data could allow the prediction of emergence of controversial situations or the need for new regulators.
Online justice and, in general, “digitization” of the legal practice would significantly save lawyers time and ensure the involvement of the most competent and unique specialists in the industry. With new automation tools, people's work would be limited only to responding to online monitoring results and AI tips. Talking about the development of AI automation systems, experts predict the further wide distribution of solutions based on the analysis of Big Data which would be able to give people clear instructions for actions in certain situations (low-quality products in stores, accidents, conclusion of contracts, and much more).
However, AI would not be able to completely replace lawyers. Rather, automation of routine functions and processes related to office work and the implementation of simple, single-variant actions would most likely occur. Today there are many automated systems for the preparation of contracts, dispute protocols, and other documents. More informatization allows going further and creating an automatic system for drafting court decisions.
As a result, lawyers would serve more as consultants - they would help choose the most convenient variants of behavior. But the legally significant decision itself would be prepared by a smart system based on the principles of a neural network. A lawyer would only agree or correct the draft of a legally relevant document.
Is absolutely honest digital justice possible? If we imagine that a judge impartially considers two similar (at first glance) cases, for example, theft, when a person stole food to save his children from starvation, and when a thief stole a pension - the last savings from a single elderly woman. What decision would AI make? It would probably bring the accused to around the same level of justice. After all, they would both be considered thieves from a legal perspective. It is unlikely that the program would be able to understand the difference between two different ethical situations and take into account additional factors. Of course, AI could be an impartial judge because a developer sets the program algorithm as such. It is enough to include an indulgence adjustment in the program code, for example, to representatives of authorities or to take into account certain patterns of human behavior. But the problem is not how well AI can handle court cases, but in the credibility of the people writing the code.
If the judiciary is in the area of responsibility of the state artificial intelligence, then the state would bear responsibility for all wrong decisions. And if there are living judges for whom artificial intelligence is only a consultant offering alternatives and a controller at the same time, then an individual person would be responsible.
AI as a Consultant
It is still difficult to entrust AI with the judge’s mantle, but it already does make an excellent adviser on key issues of jurisprudence. Artificial intelligence can use ready-made samples developed by humans, or be guided by certain criteria that serve as conditions for decision-making. For example, a person who got into an accident could address a lawyer for consultation. Another example – a simple dissolution of a marriage without sharing property and issues with children. A woman or man only needs to know what has to be done in order to dissolve the marriage and what actions to be taken.
This option is real and has already been implemented in most mobile devices. Ask a question to the voice assistant in a smartphone, and it will offer you answers based on online results. This is a counseling system based on the capabilities of artificial intelligence. Based on the same principle, a robot lawyer could also be created.
In the age of robotics and smart technologies, AI could replace the many functions of a lawyer. But this applies only to repetitive and routine tasks, such as court claims by Sberbank of Russia, which, by the way, plans to cut about 3,000 lawyers. In the case of non-typical, non-standard situations, the program would not be able to replace a human lawyer who has not only legal knowledge, but also a creative mindset and code of ethics.
A Robot President
To hand over the reins of state power to artificial intelligence is both an interesting, and dangerous idea. The main state position involves not only responsibility, but also a certain flexibility of thinking - the ability to work in unusual situations. Today, AI is not able to effectively solve global economic problems and manage people. Experts believe that the president is the face of the state, and it must be human. The issues of trust to a program remain. What if the AI president starts a war? The scenario from the science-fiction movies “Terminator” or “Matrix” may become real.
Blockchain and artificial intelligence are undoubtedly breakthrough technologies. At the same time, quantum computations are developing very rapidly. If scientists succeed in combining all these achievements together in the future, then we would receive unique software solutions that could solve many complex tasks.
Feb 13 2019
Artezio Pixel King Gets Valentine’s Day Themed Update
The previous update became available at Halloween. The app developed by Artezio is available for iOS devices and can be downloaded for free from the App Store.
The game received positive users’ feedback who appreciated the content quality and the possibility of the gradual development of the game character.
“ Themed updates for Pixel King have already become a good tradition. We strive to support the community and open access to new content for users,” said Dmitry Parshin, the Head of Artezio Development Center.
Pixel King is a new game in the genre of coloring by numbers that encourages players by gradually opening up interesting content and tools. Users can enjoy free content as well as special drawings and tools that are available by subscription. They allow speeding up playing through the game and character development.
Pixel King not only motivates children and adults to be creative, but is also a social platform for supporting gifted people. Developers collaborate with children who dream of making their work open to the world, and they add their pictures to the Pixel King library.
Feb 5 2019
How to Use Blockchain to Automate Business Processes
Blockchain is quite a new technology for business. Most often, its application is associated with the cryptocurrency market. However, blockchain technology is also suitable for traditional business. Classic databases are based on the Create-Read-Update-Delete (CRUD) process and imply that a user with administrative rights can change data at any time. Blockchain technology implies the opposite principle - data that enters the chain cannot be changed or edited. Moreover, this data is distributed and decentralized. Recently, this technology that began with the “digital gold” of Bitcoin and other cryptocurrencies has been applied in other aspects of accounting and data storage. Leading car manufacturers such as General Motors, Renault, BMW, Ford created a joint blockchain consortium MOBI (Mobility Open Blockchain Initiative) to automate the process of supplying components, accounting for cash flow, and logistics management.
Blockchain can be used in almost any sphere of production and service. The only question is where this technology will be most effective and necessary.
Healthcare and smart contracts
Blockchain technologies are universal and can be used almost anywhere where it makes sense. Blockchain is already being introduced in diamond industry, which allows distributors to quickly and clearly identify the origin of minerals. There are also many examples of implementation in the service sector. For example, the use of blockchain in the logistics for delivering goods allows visibility into the entire history of a transport chain. This ensures maximum transparency of the delivery process, increasing the processing speed through smart contracts, and improving quality control.
One of the most promising areas for blockchain implementation is healthcare.
Blockchain in healthcare would allow several processes to be improved at once. For example, it would save clinics from long lines at the registrar’s office. Currently, medical history is recorded by doctors in patients’ personal records. The introduction of blockchain would allow the storage of digitized information, which means it would be easier and faster to find, and patient data would not be lost. In addition, the automatic record of the results of all tests and previous examinations would allow the most accurate diagnoses, reducing medical errors to a minimum.
Blockchain is also easy to use in production. For example, in the production of milk, it would be possible to see not only the basic parameters of the product and its composition, but also under what conditions it was produced, how and when it was transported, and other data. But most importantly, this information would not only be easy to access, but also reliable.
It is worth mentioning smart contracts which were first implemented in 2013 in the Ethereum network. A key feature of this type of cryptographic contract is the absence of a third party controlling the contract execution. For example, when renting a room, payment should arrive from the 10th to the 15th day of each month - if payment does not arrive or does not arrive in due amount - access to the room is automatically blocked. This principle could be applied to mortgages and credit cars as well. Theoretically, all contractual relations could be transferred to smart contracts. In trade, this could apply to purchases on the internet - until you get the goods in your hands and approve it, the seller does not receive payment. This could also be beneficial to international deliveries where payments and delivery terms need to clearly be controlled. In law, most disputes would be able to be resolved without participation of courts and notaries.
Industry and Agriculture
The introduction of blockchain technologies would create new conditions for the development of entire sectors of the economy. It would help manufacturers validate the product and keep track of all participants in the supply chain, since data would be impossible to replace. Blockchain introduction in the agricultural sector would minimize the number of intermediaries, which now account for most of the operating profit. The new technology could provide market transparency, since it would be possible to track each delivery of products, for example, a batch of low-quality meat and so on.
Blockchain is suitable for any business process in which many counterparties are involved, where each of them could somehow affect the entire chain. A simple example - documents confirming legal aspects with several signatories. It is important to understand here that each has put his/her signature according to the law and that nothing should been corrected or removed afterwards. This signature confirms the signing of the document before the final approval. Blockchain helps ensure the transparency of transactions or actions within the system. For business, these are huge opportunities.
Blockchain is not just another innovative paradigm that could be embedded in existing economic models. This is a paradigm shift, a transition to fundamentally different algorithms for building a global market. Today, such countries as the United States, Switzerland, Singapore, Korea, Japan, New Zealand, China, Estonia and Belarus are at the forefront of this trend. Estonia, for example, plans to transfer all state databases to the blockchain platform, as well as to issue licenses for crypto exchange operations, thus creating conditions for registering crypto exchange. They, in turn, would bring new financial flows, both investment and tax, into the country.
Despite many opportunities, blockchain brings serious risks that could lead to significant financial and reputational losses for businesses.
As already mentioned, blockchain technology is quite suitable for automating commercial processes. It allows tracking of all financial consumables of a company, actions with assets and liabilities—it actually reduces the company's “black” bookkeeping to zero, if it exists. However, it is not possible to fully automate commercial processes, since all company financial decisions are made by a person, even if based on the results obtained using digital analytics.
It is necessary to take into account the fact that when introducing automated systems based on blockchain technologies for commercial processes, the company exposes itself to additional risks. If the system is hacked, attackers will receive all information about the company's activities.
Also, the issue of storing large volumes of data that blockchain assumes in organizations, has not yet been resolved.
In addition, blockchain contradicts the laws of personal data, which require not only to store information, but also, to remove it from the chain at the request of the owner. And in this case, the main advantage of the blockchain is the reliability of data storage, and it also becomes the main drawback. Developers of the European regulations on personal data (GDPR) already believe the use of blockchain in individual projects related to the collection and storage of personal data could be the main reason for future trials and serious fines.
Businesses will decide with regard to its financial capabilities, risks and benefits which data storage to use. It is clear that this new technology allows problems in the field of reliable data storage to be solved and the automation of some processes. Blockchain technologies attract attention, first of all, by their versatility. They are actively used in the banking and financial sectors. In addition, blockchain could and most likely will be applied in different areas from copyright to managing the voting process and government. Because of this, it is necessary to create a good legislative base to ensure immunity from initiatives related to digital oblivion and the need to edit and delete data. It is possible that blockchain technology eventually will be introduced into all spheres of human life.
Jan 27 2019
PhotoVault by Artezio Gets TouchID and FaceID Support
PhotoVault by Artezio creates an extra level of protection for photos, videos, and documents. Users just need to move their private files to the folders offered by the app, and afterwards it will be impossible to find or view them without additional identification.
Creating PhotoVault, the development team sought to minimize the possibility of accessing files accidentally when the smartphone is unlocked or the password is known not only to the owner. In PhotoVault, you can use a symbolic password as well as modern identification systems – TouchID and FaceID.
“ PhotoVault is a solution for protecting user data. Therefore, we added new identification tools that were developed by Apple and are positioned by the corporation as reliable protection of devices against unauthorized access to data,” says Igor Esipovich, Head of Artezio Mobile Development Department.
The mobile app allows not only hiding files, but also has the features that reduce the possibility of unauthorized access. To do this, users can set a false password and track hacking attempts.
The app is available for all iOS devices on the Apple Store.
Jan 22 2019
Artezio and Sberbank Developed a Guide to Create Websites for People with Special Needs
“ In Russia, about 50 mln people have special needs, which is almost a third of the country’s citizens. They are people with disabilities, elderly people, and those who are temporarily in a special situation: parents with babies or people with broken arms or legs. The guide was developed for the Sberbank Group of companies. But we decided to share it with the professional community, because we want everyone to be able to contribute to the accessibility of the digital environment,” say the authors at the official site of the project.
The new information project is an example of an accessible resource. Artezio specialists have done a lot of work so that the information on the site is structured in accordance with the international standard WCAG 2.1 and is easy to read, including people with special needs.
“ When doing the page layout, we tried to use components that were already tested and met all the requirements of the information accessibility standard. It was necessary to adapt the navigation elements and, in general, all interactive and static objects on the pages for people who use special voice readers on the Internet,” says Andrey Shagalov, Artezio Quality Assurance Director.
Besides, people who were involved in the project testing were those for whom the availability of content and services on the Internet was of high importance.
“ A visually impaired testing specialist participated in the project on the part of Sberbank; it was very interesting experience that allowed us to understand how web apps are perceived by people with special needs as well as to take a different look at the design and creation of such apps. It is important to understand that by helping people with special needs to easily use digital services, we simultaneously make them easier and more accessible to all,” highlights Andrey Shagalov.
Work on creating accessible resources in Russia will continue. It is planned that in January 2019 Artezio team will hold a master class on the development of accessible services for Sberbank developers.
Jan 11 2019
How to Do Business with Аgile: Using IT Tools to Beat Competitors
Alexey Latinnik, the Head of Internal Development Department at Artezio
The rapidly changing market conditions and mass automation are forcing businesses to look for new methods of dealing with competitors. Many companies and entrepreneurs are trying to repeat the success and reveal the secret formula for the success of IT leaders: Amazon, Google, Facebook, Apple, Microsoft with revenues exceeding the GDP of some countries. What business practices can be learned from IT companies to beat competitors? Maybe Agile?
What makes successful companies successful?
We live in the era of the digital economy where new information products and services come to the fore, they are closely intertwined in all spheres of life, and therefore, this is the reason for success. Just look at the Fortune Global 500 list. At the forefront are WalMart, BP, Toyota Motor, and Volkswagen. The IT giant Apple takes only the ninth position. Thus, it turns out that it is not necessary to work with IT products to succeed.
There is no magic formula or “silver bullet”. However, common features and trends are easily traced in the actions of all successful companies. For example, flexibility, responsiveness and readiness for change; focus on creating a continuous stream of values; continuous improvement of the product, processes and team; short supply cycles, experiments to test ideas on the market. Such companies are said to be on the path of Agile transformation.
This can be described by the term Business Agility — this is a way of doing business in which an organization puts the interests of a client first and agrees to continuously adjust to their changing needs.
How does Agile work?
Obviously, the old planned model with a hierarchical or matrix structure has become obsolete and taken a back seat. The situation on the market can change at any second and following a clear plan, approved at the beginning of the year, can be a disastrous decision. Even if you try to quickly agree on a new course of action, bureaucratic procedures will slow down this process so much that the new plan may be irrelevant.
In the field of IT, the analogue of a planned economy is the so-called cascade (waterfall) software development model. It requires a clear detailed wording in the requirements and a consistent transition to other stages without the possibility of returning to the previous stage. Simply put, this is a sequential action plan. Therefore, an error that has crept into the tasks may initially become a serious problem at the development, testing, or implementation stage. In addition, the result, which is a working software solution, as a product, will be visible at the very end after going through all project stages. What is it possible to do in such a case, what alternatives are there?
Suppose a large customer has come to you with a multi-billion dollar contract. Will you refuse such a customer who will say: "I am ready to pay good money, but I want to see the result right away; I have no requirements, but I have a general concept." Is it possible to take on such a project? It may seem that implementing such a project is a utopia with a previously known sad end. This is not true if you are familiar with Agile.
Agile practices allow iteratively creating a product (Product Increment) under uncertainty, gradually enlarging it to the final state. By the end of the iteration (Sprint) equal, for example, to two weeks, you will have a ready-made working prototype with a basic set that you will be able to demonstrate to the client and immediately receive feedback. Work is built in such a way that the most important tasks (User Story) that have the highest priority from a business point of view are always taken into work. If the task becomes irrelevant, it is simply removed from the task list (Product Backlog) or roadmap. This allows you to quickly check the key concept, review the strategy and promptly deliver the product and services that meet modern realities.
Using the task board with statuses (Kanban board) allows you to visualize the current state of affairs and move tasks from the initial state to the "ready" state. To do this, you can use the Internet analogs of Kanban boards (Trello, Jira Agile, TFS, etc.) or physical boards, with lined columns of statuses (for example, “what to do”, “in operation”, “checked”, “done”, etc.) and stickers with the name of tasks, estimate, and executor.
What is the value of Agile?
The core values of Agile were formed by the independent IT specialists in February 2001 and are reflected in the Agile Manifesto, which consists of 4 key ideas and 12 principles.
The following Agile values are highlighted:
1. People and interaction are more important than processes and tools
Allow the team to organize themselves and solve work issues on the spot communicating with each other. No one in the team likes micromanagement and excessive bureaucracy.
2. Working product is more important than documentation
Better do than talk or write about what needs to be done. When you do a small piece of work and show the result, you will understand earlier if it works or not. Experiment, don’t be afraid to make mistakes, but correct them the next time (conduct regular retrospective analysis with the team).
3. Cooperation with the customer is more important than meeting the terms of the contract
Stay in touch with your clients. Give them what they need and what they want. Offer a ready-made working solution, and not just the fulfillment of a contract for obligations. The customer must be a part of the team.
4. Willingness to change is more important than following the original plan
Everything is changing fast, so let's be flexible, although it may be too late to become flexible. It is convenient to track changes during the regular review of the task list and “cleaning” of outdated irrelevant tasks (Backlog grooming). Review priorities with the customer, priorities are not static — in the next iteration, priorities for tasks may change. It should be noted that the Agile Manifesto does not at all deny the importance of tools, processes, plans, documentation, etc., it rather sets priorities aimed at obtaining high-quality operational results, which ultimately allows businesses to do business.
Where is Agile used other than IT?
Let's look at some examples of using Agile practices by non-IT companies.
- Amancio Ortega Goana, the owner of the world's largest retailer of fashion clothes Inditex that includes such brands as Zara, Zara Home, Bershka, Stradivarius, Oysho and others actively apply agile approaches in almost all his companies. Constant experimentation for hypothesis testing, quick entry of a new product with a short time-to-market cycle (Time to Market), and quick feedback from customers allow Zara to produce up to 40 collections per year, compared to other brands making just from 4 to 8 collections.
- Air Methods (the founder is Roy Morgan, over 6,000 employees), specializing in providing emergency medical care using air transport, faced the problem of staff training and did not understand how much time and effort it would take to create trainings and training projects.
The trainers adopted Agile practices, in particular the Scrum framework, using the task board (Trello tool), backlog management, and prioritization. Tasks from interested persons were collected on the board, each task was assigned a category: “green” tasks, the most important ones, can be performed now; “Red” are in the queue. Regularly, as the “green” tasks were resolved, the team and stakeholders gathered to identify new priorities and discussions.
- From 2008 to 2011, the Norwegian State Pension Fund implemented a large-scale project for domestic needs where 12 Scrum teams were involved. At various times, the number of participants reached from 80 to 180+ people. Without the support of the top management, this project could hardly be implemented.
Agile techniques established well in small and medium businesses: in recruiting companies, retail and commerce, restaurant and hotel business, companies organizing events, exhibitions, etc.
Agile is closer to you than you even think. You won’t believe it, but housing maintenance services also use Agile practices with daily planning meetings and the ability to increase the priority of tasks if the customer really insists. Some waiters still write down orders into notebooks and use stickers in the order queue in the kitchen for cooking.
Why doesn't Agile always work?
Once again, I want to note that Agile is not a panacea. Many companies failed to accept Agile for various reasons after several attempts to introduce it with the help of experienced Agile managers and coaches. The reasons are expensive implementation and training, revision of all processes, lack of qualified specialists, no understanding of implementation goals or implementation of Agile in a separate business area process, fear of making mistakes and experiments, lack of interest and lack of motivation, no confidence in the staff for the delegation of authority, a rigid hierarchical structure of the company and unnecessarily used legalized processes, psychological resistance to all innovations and changes, and much more. Besides, Agile should not be used in projects with a high degree of risk occurrence (development of life support systems, in the aerospace industry, atomic energy, etc.). Therefore, it is worth thinking several times and thoroughly examining the issue before introducing the Business Agility into your company.
How should Agile be used in everyday life?
Finally, I will share some life hacks: some elements of Agile can be useful in everyday life, for example, in a project called “celebrate the New Year”:
● Plan a sprint and rank the tasks. Make up a simple TO-DO list of tasks, more important ones are placed at the top of the list (go to sauna; buy champagne and food; invite Vasya, Vera, Nadya, Lyuba to the party; congratulate relatives; cook Olivier salad; decorate a Christmas tree, etc.).
Copy the task list to the stickers and specify the friends’ names. Use a Kanban board, a lined notebook, or just a wall with status columns (“Not Done”, “Someone is Doing Something”, “Done”), put our stickers on the wall.
● Have a daily scrum or brief meeting status with the team: what I did yesterday, what I’m planning for today, if there are any problems (in our case, the New Year chat in the messenger can be used).
During the sprint itself (it’s only 2 weeks left till the New Year!), look at the board, shift the task stickers as things progress (The girls did great job, and Vasya didn’t do anything! We’ll have to give this task to someone else and ask Nadya to buy tangerines and chairs).
● Conduct a demo and review of the sprint (everything seems to be ready as planned: everyone gathered at the table and TV, the Christmas tree and guests are dressed up; dishes, Olivier salad, slicing, champagne and everything is ready; the chiming clock; wait, someone is missing. .. it seems that we forgot Vasya in the car).
● Do a retrospective analysis (we hold a meeting and talk with the team on January 1. Vasya for some reason is not completely satisfied, we analyze why).
● De-Javu or planning a new sprint-2 (we are thinking over how to celebrate Old New Year again at Vasya's place).
And finally, I’d like to add: don’t be afraid to implement Agile, be careful not to introduce Agile.
Company information Artezio
Artezio delivers cost effective, high quality IT services to companies in the US, the United Kingdom, Germany, Switzerland, Japan, Austria, and CIS.
In addition to custom software development, Artezio continually invests in R&D activities and develops its own products: Software as a Service platform solutions, Mobile apps for iOS, Android, Desktop and tablet products.
Artezio assists its clients in analyzing and automating their business processes, as well as provides software solutions to achieve their operational goals:
- Rapid automation solutions implementation
- Getting software products to markets faster
- Porting and implementing web-enabled software from scratch, etc.
|Type of company||Head Office|
|Fax||+1 212 2201641|
Key figures Artezio
Mr. Dmitry Rodionov
Deputy MD/Chief Operating Officer (COO)
- Service provider
Other classifications (for some countries)
NAICS (US 2012) :
Custom Computer Programming Services (541511)
SIC (US 1987) :
Computer Programming Services (7371)