Key problems

Market Issues

  • Not enough data

    The fundamental problem is that almost all the available text data is raw, not enriched with metadata and thus useless for training neural networks and chat bots.

  • Market monopolization

    Presently the AI and data analysis market is dominated by a handful of corporations – this slows the development and makes startups less competitive.

Business issues

  • Too slow

    To automate a process and resolve an end task, a business might need to spend 5-10 months on performing case studies, data analysis, formalizing the development task, testing and finalizing a solution.

  • Too expensive

    Developers, data-science and NLP specialist cost a lot, and using them demands specific knowledge and the time to recruit and manage a development team – which is most frequently outside the business’s scope.

  • Disparate solutions

    Using an off-the-shelf solution, a business loses the ability to update the neural network with new data or has to resort to using different services, which complicates data processing, integration, software code development and requirements even further.


GraphGrail Ai is a unified full-cycle solution for text data analysis.

The platform provides all the modules necessary for data preparation and processing: data harvesting and parsing, cleanup, tagging using an Ai designer for creating a language model of the subject scope, testing, machine learning and tuning the neural network to the task, API-based integration into your business processes.

A ready solution is hosted at the Cloud Marketplace and starts earning money. There is no more need of third-party services and complicated integration – all the tasks are solved on the GraphGrail Ai platform.

Advantages and innovation

Coding-free (GraphGrail Ai Designer)

Create your language applications using a set of convenient building blocks! Using the GraphGrail AI platform, it is possible to create and train neural networks for various tasks, including complex classification, using Google Tensorflow and other tools. Business chat bots, media products and services analytics, author attribution based on text style, precise definition of emotions based on quotes – all this and more without coding!

Data markup (GraphGrail Ai LabelLance)

The platform provides a component for easy and rapid data markup, enriching data sets for knowledge extraction from immense datasets your business possesses, and providing aid for quality decision making. Users from all over the world will be able to perform markup of their text data arrays, or commision bespoke markup services.

Applications marketplace (GraphGrail Ai Marketplace)

Earn money using the platform! Create and sell your linguistic applications for the profit of both the data-science specialist and business. Buy and sell ready dataset packages of various enrichment level for training neural networks on the platform.

AI laboratory (GraphGrail Ai Lab)

At the Artificial Intelligence Laboratory, the researchers and specialist from all over the world will be able to develop and test new and prospective solutions (RnD). The laboratory will become a stepping-stone for improving the existing and developing novel original solutions: strong speech chat bots, automated addition of scientific data, personal assistants..

Platform architecture

Artificial intelligence, especially the data science and machine learning (DS&ML), will change the way data is obtained, analyzed and managed. Due to complexity, this is presently done mainly by humans, frequently by developers hired by third-party service providers. But DS&ML are the moving forces of the future data and analytics services (D&A). In time, more complex and non-trivial tasks will follow, opening the way to “intellectual” automation.

A ready solution is placed in the decentralized marketplace and starts making money. Now you do not need to use other services and do complex integration - all tasks are solved on the GraphGrail Ai platform.

The GraphGrailAi platform is a layered structure comprising layers of NLP components, algorithms and applications. Its flexibility allows data-science specialists to reuse components and build data processing pipelines.

The team

Victor Nosko

CEO and founder, Ai, Data-science.

Python developer, Django framework. Data-science specialist, NLP stack: NLTK + Celery + Pymorphy2 + GLRparser etc. Victor has more than 6 years of experience in development and deep learning. Experienced in Google TensorFlow

Alexander Borodich

Venture investor, CMO.

Futurologist, angel investor, serial entrepreneur, founder of VentureClub, MyWishBoard, MyDreamBoard, and SuperFolder. Chief Dreams Officer and partner in Future Action, founder of crowd-investing platform Alexander has solid business experience

Marina Parinova

HR manager

Responsible for IT recruitment, new employees' adaptation, a comfortable and pleasant office atmosphere. The team is actively growing and reinforced with steep specialists. Join us! Send CV to , and we will be pleased to arrange an interview to our company.

Nikita buevich

Frontend Developer

Responsible for creating smart, pretty and convenient user interfaces that will help to solve your problems with maximum efficiency and pleasure. Loves to do it.

Anton Smetanin

Fullstack веб-разработчик.

Responsible for backend development.
Experience in this field of more than 7 years. Main languages and frameworks I use are: РНР (Yii), Python (Django), Javascript.

Semyon Lipkin

Python Developer & Data Science.

Field - development of machine training algorithms by means of the Python language. Education: engineer in Industrial Electronics, Master in “Information and Communications Technologies and Communication Systems" - both in South-Russian State Polytechnic University (NPI).
Doctor of Science in 05.13.05 “Elements and devices of computer engineering and control systems". More than 90 works were published, based on the scientific activities results, including articles (in magazines reviewed by Scopus, WoS, State Commission for Academic Degrees and Titles, Russian Science Citation Index), patents, teaching aids.

Alexander Gusarin

Python Developer & Data Science.

Responsible for developing programs in the field of machine learning, Python programming.
Has two university degrees:
specialist's degree “Computer Security" (Don State Technical University) (red diploma)
Master's program “Software Engineering" (Don State Technical University)

Zakhar Ponimash

Consultant in neural networks.

Engaged in neural networks and strong AI.
Game developer, based on XNA framework, TCP/ip chat, chat bots, text understanding systems. 2 times was the first at the university conference on economics, 2 times at radio engineering. Once was the 1st in the IT park hackathon. Participated in the IT park acceleration program with “patterns recognition" project. Good knowledge of C#.

Mariya Tarasova


Candidate of philosophical sciences, specializes in simulation modeling, data mining and statistical data analysis. Was awarded a scholarship of the President of the Russian Federation and the Government of the Russian Federation for her high contribution to science, author of more than 60 scientific research works on the social processes modeling, an active participant in five grants of the Russian Fundamental Research Fund and participant of more than 10 Russian national and international conferences.


Presently used by business

  • Monitoring (social media)

    Analytics and searching for problems with the business’ products and service, monitoring competitors’ cryptocurrency-related publications, analysis of the media field in politics, news streaming.
    Technologies: Aspect sentiment, Named Entity Recognition, Business-specific ontology, Multi-class classification, RNN

  • Smart chat (e-commerce)

    Understanding the customers’ needs, guiding through the stages of purchase process, understanding the customers’ objections, improvement of conversion in sales.
    Technologies: Natural Language Understanding, Syntax similarity, Multi-class classification, RNN, LSTM, Neural Turing Machines

Existing business and future solutions in the AI sphere

  • Author attribution based on unique style
  • Understanding sarcasm, irony
  • Chat bots with personalities
  • Domain-specific models for business
  • Fake news detection

Blockchain companies

  • Checking smart contract conditions
  • Security provisions for tokenomical contracts
  • Text data analytics for media in the new blockchain market: SteemIt, Golos, Status, Telegram



  • Company created
  • First sales of language analysis analytic solutions to business customers
  • Search service based on own developments successfully sold


  • Incubation at the Southern IT Park
  • Receiving the first investments


  • Sales of analytical research to business clients: marketing agency, LingvoLeo
  • GraphGrailAi – one of two companies in the Russian Federation providing Internet quotes search and fine sense analysis

February, 2018.

  • Use-case release on the GraphGrailAi platform – a monitoring system with flexible text classification tuning based on language models.

March – May, 2018.

  • Use case release on the GraphGrailAi platform – Smart chat optimization for sales automation.
  • Release of a Data markup component with possibly of third parties business clients use

June - July 2018.

  • Full-scale launch of platform, linguistic modules and neural networks builder and with access through software interfaces (APIs),
  • Testing and launching a second language for the platform (English)

August – October, 2018.

  • Release of language models marketplace component with monetization and payments for API queries.
  • Implementation of ready-to-use semantic categories sets (category-subcategory, taxonomy, part-whole)
  • Implementation of blockchain for data markup quality assessment (proof-of-quality-work)

First quarter, 2019.

  • Creating a Deep machine learning and future artificial intelligence prospective solutions laboratory based on the platform models (RnD Laboratory with deep learning)

Tokensale conditions

TGE started: 19, Feb
TGE ended: 15, Apr
Tokens: 270 000 000
One token price: 1 GAI = $0.1

Soft cap: $2M
Hard cap: $12M


Presale investors: 40%
White-list investors: 40%

All investors:
first 5 days: 35% (for all)
next 10 days: 25% (starting from $10,000 - 35% )
next 10 days: 20% (starting from $10,000 - 25% )
next 10 days: 15% (starting from $10,000 - 20% )