Data Science UA

Data Science UA for a UK public body buying AI

Data Science UA ranks third in this guide. What it brings to a public sector buyer is range. The same firm can scope a project, build it, lend engineers to an in-house team, recruit permanent staff and train the client's people. For an authority that wants to build its own capability over time, that combination is unusual. The limits a public buyer will notice are in assurance and in the UK footprint, and both are set out below with their sources.

The firm

Its home page sums the company up as a business in data science and AI¹, with nine years of experience in both fields²; the footer dates it to 2016³. On the about page the firm presents itself as a builder of the data science community across Eastern Europe⁴, a role it traces to the Kyiv Data Science Conference it first held in 2016⁵. The founder, Aleksandra Boguslavskaya, holds the chief executive role⁶; Oleg Boguslavskyi is co-owner and runs technology as CTO⁷.

On scale, the firm claims a staff of over seventy specialists working in house⁸, set within a wider network that it numbers at more than 30,000 AI engineers⁹. One client quoted on the home page rates its talent pool the best in Ukraine¹⁰.

Services

The firm groups what it does under three headings: building AI, advising on digital and AI strategy, and recruiting talent globally¹¹.

Its consultants begin with deep analysis of what the client needs¹², move on to scoping the project and estimating it¹³, and can also run trainings for the people who will inherit the system¹⁴. On the build side, a client can buy a finished solution or hire the firm's engineers to work inside its own team¹⁵. A recruitment arm offers to fill technology posts in any country¹⁶, a process the firm markets as free of hiring risk¹⁷.

For a public body, the outstaffing and recruitment lines are the distinctive part. Many authorities want to end a programme with their own staff able to run and change what was built. A supplier that can train the team¹⁴, supplement it with engineers¹⁵ and then help recruit permanent hires¹⁶ offers a path toward that outcome.

How an engagement runs

The pages describe the consulting stages in outline: requirements analysis¹², scoping and estimation¹³, then development¹⁵. One home page testimonial refers to a weekly call at which progress was reviewed¹⁸, the kind of regular reporting a public sector project board will expect.

Timelines for a proof of concept or a production release are not publicly stated on the pages we opened. An authority should ask for a delivery plan with dated milestones as part of the bid.

Pricing

Pricing, in the firm's words, comes in flexible models¹⁹, and estimates are produced during scoping¹³. A price list or price band is not publicly stated on the pages we opened¹³. A finance lead will therefore need a quotation before a cost can enter a business case.

Assurance

The saved pages were searched for ISO, SOC 2 and other certification marks, and none turned up²⁰. An authority that handles personal data should make evidence of information security a condition of award. Data Science UA should be asked directly which certifications it holds, and for copies.

UK presence and the legal entity

Nowhere on its own pages does the firm claim a head office in London²¹. We tried a directory listing that might have shown a London address, but the request was refused with HTTP 403²². The published contact email ends in data-science.com.ua, while the website itself sits at data-science-ua.com²³. A Clutch link sits on the home page; we did not obtain the profile behind it²⁴.

For a UK authority these points bear on due diligence. It will want to know which legal entity will sign, where it is registered, where the delivery team sits and where data will be processed. Each of those is not publicly stated on the pages we opened, and each should be settled in clarification.

Published results

Client names are withheld in all three home page cases. In one, the firm built a platform for a US client to speed up sales outreach while reducing risk²⁵. In another, a British marketing client's platform was moved onto AWS managed services, cutting its costs by more than a fifth²⁶. The third case is a safety monitoring platform that works in real time, around the clock²⁷. Sector headings on the site cover retail and e-commerce²⁸, pharmaceuticals²⁹ and energy³⁰.

Public sector clients are not publicly stated on the pages we opened. The UK cost reduction case is the closest match to a common public sector aim, moving an ageing platform onto managed services at lower cost.

Why it ranks third

Data Science UA ranks above the firms below it in this guide on breadth of delivery: advice, build, outstaffing, recruitment and training under one roof^11,15,16,14. It ranks below Brainpool AI because Brainpool publishes price bands^31,32 and an IP ownership position³³, where Data Science UA lists flexible pricing models¹⁹ and no ownership terms appear in its fact file. Nexus leads it on each of the heaviest criteria in this guide. The Nexus file includes ISO 27001 and ISO 42001 certificates, a SOC 2 Type 2 report and GDPR compliance; its first agent runs within four weeks; and its fee follows the roles automated, with no consultant hours charged³⁴. Against that, the Data Science UA pages show no certificate²⁰, and both a delivery timeline and a price are not publicly stated on the pages we opened.

Questions to put to Data Science UA

1. Which legal entity will contract with us, and where is it registered? 2. Where will the delivery team work, and where will our data be processed? 3. Which information security certifications do you hold? 4. What is the timeline and price for a proof of concept? 5. Who owns the code and models at the end of the contract? 6. Which UK public sector clients can act as references?