CTO / CPO · Enterprise AI

Enterprise-grade AI systems,

built and shipped at national scale.

30M+ users · 95+ awards · 17+ years of enterprise experience

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SBERBANK·MERCEDES-BENZ·NLMK·RUSSIAN RAILWAYS·CATERPILLAR·NORNICKEL·GTLK·

Built by our founder, in production at these organisations

AI Ecosystem

Technology behind the systems

AI Systems

NLP & LLM

Citizen appeal classification and response generation, in federal production

Computer Vision

Document and image recognition in appeal processing

ML Ops

Retraining loops on operator-verified data, production monitoring at national scale

GenAI

Text-to-SQL and AI assistants in the BI+AI management platform

Big Data

Terabyte-scale receipt stream for the national Consumer Price Index

Neural Networks

Word2Vec+LSTM and PyTorch classifiers in federal production

Select a domain for details

30M+

Users impacted

95+

Industry awards

15+

Industries served

AI systems and platforms built and shipped across 15+ industries — at national scale.

Selected Work

Systems that shaped industries

Ministry of Construction (Minstroi)

AI-powered citizen request system

AIGovernment2023–2025

78% in research → 95%+ accuracy in production

Outcome

XXVI Golden Site Awards, 1st place 'Best AI-based solution for citizen-inquiry processing' (2023, awarded 2025)

Russian Railways

RZD Bonus Loyalty Platform — Highload

EnterpriseLoyalty2020–2023

33M passengers, 9.9M members

Outcome

XXVI Golden Site Awards, 1st place 'Best Corporate Programme' (2023, awarded 2025); Tagline 'Best Integration' 2020-21, 'Best Highload' 2022

Federal Statistics Service (Rosstat)

AI-powered Big Data system for Consumer Price Index

AI & DataGovernment2021

Terabyte-scale data, 90% accuracy in production, 150+ report templates

Outcome

Tagline 'Best Audience & Data' 2022 (1st place), 2023, 2024

Mercedes-Benz Bank

Online credit & leasing application

FinTechEnterprise2022

Outcome

Tagline Award 2022

State Transport Leasing Company + STLC Europe

International corporate omnichannel platform

EnterpriseInternational2020–2023

Outcome

Tagline 'Best International Site' 2020-21; 'Best Integration' 2023; 'Best International Digital Service' 2025

DigitalCEO

BI+AI digital management ecosystem

AI ProductAI Engineering2025

BI + AI platform

Outcome

CNews AI Industry Review 2024; #3 BI vendor by own-product licence revenue (TAdviser)

NLMK

Corporate portal for 60,000 employees

EnterpriseIntranet2019

Outcome

Tagline 'Best Intranet' 2019; StepTwo Intranet & Digital Workplace Awards — 2nd place worldwide (Silver)

Federal Alcohol Market Regulation Service

AI-powered citizen request processing system

AIGovernment2022–2023

Outcome

Tagline 'Best AI Technology' 2022 (Bronze); 'Best Gov Service' 2023

Sberbank

Cybersecurity education platform

EnterpriseCybersecurity2021

Outcome

Automated cyber literacy system

Caterpillar Financial

Online leasing applications

FinTechEnterprise2020–2021

Outcome

Tagline Award 'People's Choice' 2020–2021

Research

Peer-reviewed AI research

Four sole-authored papers on arXiv (DOI). Indexed in NASA ADS, Semantic Scholar & Google Scholar.

ORCID 0009-0004-7005-6242

arXiv · 2026

AI Appeals Processor: A Deep Learning Approach to Automated Classification of Citizen Appeals in Government Services

Behind the citizen-request AI (Ministry of Construction, Rosalkogol)

arXiv:2604.03672 DOI: 10.5281/zenodo.19393274

arXiv · 2026

Machine Learning for Coding Retail Product Names to Consumer-Price Categories: A Rule-plus-Bag-of-Words Pipeline with Reliability-Weighted Human-in-the-Loop Labeling

Behind the CPI big-data system (Rosstat)

arXiv:2606.02004 DOI: 10.5281/zenodo.20503356

arXiv · 2026

How Far Do On-Prem Open LLMs Get on Text-to-SQL? A Cross-Family Size × Technique Frontier on BIRD

Behind BI+AI / Text-to-SQL

arXiv:2606.29733 DOI: 10.5281/zenodo.20952794

arXiv · 2026

A machine-readable catalogue of the Tsiolkovsky papers (fond 555, Archive of the Russian Academy of Sciences), and a way to measure how well its handwriting can be read

Independent research: handwriting recognition (HTR) & archival cataloguing

arXiv:2608.03617 DOI: 10.5281/zenodo.21705221

In the media

Expert commentary in the media

TechRound · 2026

On chat as an AI interface and the limits of model capability

Cited as "Enterprise AI Architect & CTO, founder of Besk Tech"

The New Stack · 2026

On agent memory and Anthropic's "dreaming"

Cited as "Enterprise AI architect and founder of BESK TECH"

The New Stack · 2026

On CloudflareOS and agentic AI workspace security

Cited as "founder of BESK TECH"

GENZ TECH · 2026

On model rankings and switching AI coding assistants

Cited as an "enterprise AI architect" running open-weight coding models in production at BESK TECH

TechRound · 2026

On why Big Tech is designing its own AI chips

Cited as "Enterprise AI Architect & CTO"

Reworked · 2026

On AI reference architecture & vendor lock-in (Microsoft Frontier)

Cited as "enterprise AI architect & CTO"

Just AI News · 2026

Expert commentary on Claude Sonnet 5 and enterprise AI

Cited as "Enterprise AI Architect & CTO, founder of BESK TECH"

Founder

Vladimir Beskorovainyi

CTO / CPO · Enterprise AI Systems

Vladimir Beskorovainyi builds production AI and big-data systems at national scale. Over 17+ years he has led engineering for platforms serving tens of millions of users: from NLP systems classifying 50M+ citizen requests to big-data pipelines behind national statistics.

Full lifecycle: architecture, machine learning, and shipping models to reliable production. Products adopted by federal agencies and enterprises, with 95+ industry awards.

Founder's Portfolio

Contact

For collaboration, technical discussion, or speaking — reach out directly.

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