Machine Learning

Machine Learning (ML) is a data analysis technology that allows systems to learn how to solve different problems. It is based on the idea that analytical systems can learn to recognize patterns and make decisions without human involvement.

Machine Learning is becoming one of the most popular technologies in the world bringing its capabilities to people’s work and lives. The ideas and prospects of Machine Learning we realize in Natural Language fields. We are going to show here how do we work with Machine Learning algorithms, which techniques we utilize, what kind of tasks we solve and tell you about our project. Let’s go!

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We mainly work in Machine Learning fields: NLP (Natural Language Processing) and NLU (Natural Language Understanding).

We have a big experience in natural language understanding because we work in this field for about 3 years. The number of tasks we solve in this field grows constantly.

NLP

NLP is a wide list of text processing tasks. It is designed to help the computer to understand, analyze, manipulate, and even generate natural human language.

NLU

NLU is the process of understanding the meaning of the user’s inputs. According to these inputs (words, phrases or questions), we make profitable and predictable results for him.

Tasks that we solve in our Machine Learning cases:

Named-entity recognition/classification
Information extraction
Topic modeling
Summarizing
Paraphrase identification
Question answering
Searching engine
Text classification

About open-source models that we utilize

Nowadays there a lot of powerful open-source Machine Learning libraries and models that are freely available on the market. We don’t hesitate to use them to improve our Machine Learning algorithms and NLU potential. Here are some of them:

Bidirectional Encoder Representations from Transformers (BERT)
Multilingual Universal Sentence Encoder for Semantic Retrieval
Tensorflow and Simple Tensorflow Serving
FAISS by Facebook
ElasticSearch
gRPC for the API

Here you can check the more detailed article in which we described how to build a semantic search pipeline using open-source components and a little bit of coding (based on our project OneBar).

OneBar

In addition to consulting services, we are all working on Onebar. OneBar is a search tool (based on Machine Learning) for teams that helps them boost productivity and promote knowledge sharing. It integrates with Slack and provides a seamless search experience through a convenient interface. Here we try to use and experiment with the most progressive features of Machine Learning in the field of NLP. Read more about OneBar via this link https://onebar.io/.

Machine Learning has a really borderless potential for business, science, human lives, and humanity in general. For instance, we develop Slack bot development based on Machine Learning algorithms and the circle of our interests in ML is constantly growing.

Our development process

Clarify and set project requirements

Create a system design and UX/UI wireframes

Define and prioritize development tasks, create a backlog, prioritize all the tasks and provide estimates

Select the tasks from the top of the backlog for a 2-week sprint cycle

Deliver sprint results and iterate based on the feedback

Finally, deploy the project after all goals were met

Our projects

USA

Carggo - Finding the best way of delivering your goods

Visualization for right business decisions

Kazakhstan

Data visualization for making right business decisions

USA

ThoughtSpot - Developing internal resource management application

Industries we excel at

Our clients are businesses of different types and sizes. We developed projects for companies in a range of industries: finance, media, healthcare, education, government, real estate/property, social media, travel/transport, e-business, e-commerce, to name a few.

Other services we provide

Get in touch

Communication is the key. Let's discuss your project together.

We will respond to you within 24 hours

Dmitry Tsybin

Director of Engineering, Carggo

Upsilon provided front- and backend development for an online logistics platform. The team designed and launched a business intelligence platform and ensured scalability according to customer requirements. We were most impressed by the technical background of the specialists, their meaningful approach to task accomplishment, and aspiration to deliver the results in due time. We’re also pleased with how fast the team started the development.

Kenny R. Lienhard

CTO, Medignition Inc

We wanted to implement a new education platform that offered online courses in finance. The scope focused on the implementation of multiple user interfaces. UpsilonIT used React, GraphQL, and GatsbyJS. UpsilonIT had strong coding skills. The app had a clean codebase and complied with all specifications. They complied with our requirements for the UI. We communicated daily via Slack.

Matt Wong

CTO, Civic Connect

Upsilon’s work was always on time and met all customer expectations. Their team had an ease of communication but what was the most impressive about them is the integrity and work ethic of each member. We had a business manager, a lead architect, and a mix of senior and regular engineers. The workflow was extremely effective - the teams had a regular cadence for communication.

Zhanar Serikpayeva

Creative Consultant, Etage Group

We needed help with mobile app development, data analytics, and beacon installation to be able to collect, store, and analyze our customer data. The finished application met the requirements perfectly, with the team finding an excellent solution to collect, analyze, and store customer data. They were highly professional throughout the work, always making themselves available, and responding well to any changes.

Dmitry Tsybin

Director of Engineering, Carggo

Kenny R. Lienhard

CTO, Medignition Inc

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