DataRoot Labs
Kyiv-based AI R&D shop, exclusively focused on generative AI, ML, and data engineering since 2016.
Founded 2016 | Kyiv, Ukraine | 27–50 employees
custom-ml-modelsgenerative-aidata-engineeringdeep-learning
What is DataRoot Labs?
DataRoot Labs was founded in 2016 in Kyiv, Ukraine and has worked exclusively in AI and R&D since inception, building generative AI, machine learning, and data engineering systems for startups and enterprises. The company is notably lean — roughly 27 employees across three continents as of late 2025 — and also runs DataRoot University, a free ML and data engineering school with more than 6,000 graduates, which doubles as its own technical talent pipeline. Its small size and academic ties make it a lower-cost, highly specialized option relative to larger regional peers.
DataRoot Labs was founded in 2016 and is headquartered in Kyiv, Ukraine. The firm employs 27–50 people and works primarily with clients in Startups (cross-industry), FinTech, Healthcare sectors. Its primary differentiator is: Runs its own free ML/data-engineering school (DataRoot University, 6,000+ graduates) as a self-built talent pipeline.
DataRoot Labs tech stack and services
PythonPyTorchHugging FaceLangChainAWSDocker
| Service area |
|---|
| Custom ML Models |
| Generative AI |
| Data Engineering |
| Deep Learning |
DataRoot Labs use cases
Short answer: DataRoot Labs is best suited for Startups, direct access to senior ML engineers.
| Use case |
|---|
| Startup with a limited AI budget needs senior-level generative AI or ML engineering without enterprise agency overhead. |
| Company wants a lean, R&D-focused partner for an experimental ML feature rather than a large staffing engagement. |
| Team needs data engineering plus ML modeling from a single small, senior group. |
DataRoot Labs pricing
Short answer: DataRoot Labs uses a project-based, dedicated team pricing approach. Minimum engagement starts at Not published.
| Engagement model | Typical range | Best for |
|---|---|---|
| Project-based | Variable; depends on team size | Large programmes or team augmentation |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
DataRoot Labs does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
DataRoot Labs pros and cons
| Advantages | Things to consider |
|---|---|
| +Team of roughly 27 keeps overhead low, which typically translates into lower blended rates than 500+ person firms. | -27–50 person team size limits capacity for multiple large concurrent enterprise engagements. |
| +Exclusive AI/R&D focus since 2016 with no general software-development sideline diluting expertise. | -Small headcount means less bench depth if a key engineer rotates off a project mid-engagement. |
| +DataRoot University (6,000+ graduates) gives the firm a homegrown, vetted junior-to-mid talent pipeline instead of relying purely on open-market hiring. | -Thinner public enterprise case-study base than larger Ukraine-headquartered peers like N-iX or ELEKS. |
| +Cost/accessibility standout among the researched companies for startups with constrained AI budgets. |
DataRoot Labs vs alternatives
How DataRoot Labs compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Neurons Lab | Enterprises needing senior AI advisory, not a staffing... | Founder-led AI strategy-to-production consultancy with no junior-heavy delivery layer. | 4.9 | Full comparison |
| Provectus | Mid-market and enterprise companies, production-grade MLOps. | AI-first systems integrator built around running production ML/AI infrastructure long-term. | 4.8 | Full comparison |
| Tensorway | Fintech, healthcare, retail — boutique EU-based ML vendor. | AI boutique backed by 20+ years of software delivery experience via parent company. | 4.6 | Full comparison |
| InData Labs | FinTech, healthcare, SaaS — decade-old AI specialist. | Ten-plus years as a pure-play AI/data-science firm with no general software-development sideline. | 4.5 | Full comparison |
| XenonStack | Companies building agentic AI, real-time data platforms. | Multi-cloud certified (AWS, Azure, GCP) platform-engineering specialist for real-time and agentic AI. | 4.4 | Full comparison |
| Grid Dynamics | Fortune 1000 enterprises, public-company transparency, large-scale delivery. | Nasdaq-listed enterprise AI engineering firm with public financial reporting and Fortune 1000 client base. | 4.4 | Full comparison |
| MobiDev | US/EU companies, dedicated AI practice since 2018. | Clutch's #1-ranked Machine Learning development company (2021), with a dedicated AI practice since 2018. | 4.3 | Full comparison |
| Addepto | Companies wanting a Forbes/Deloitte-recognized AI consultancy. | AI consulting boutique with third-party press recognition (Forbes, Deloitte, Financial Times), now part of KMS Technology. | 4.3 | Full comparison |
| LeewayHertz | Enterprises wanting AI consulting, publicly-traded parent (Hackett Group). | AI consultancy now operating as a Hackett Group company, combining startup-era agility with public-company backing. | 4.2 | Full comparison |
| Softermii | Product teams building AI agents, generative AI features. | 4.9/5 Clutch rating (34 reviews) with a specific focus on AI agents and real-time communication platforms. | 4.2 | Full comparison |
| Sigma Software Group | Automotive, aviation, AdTech — large vertical IT consultancy. | Deep, decade-plus domain expertise in AdTech, automotive, and aviation combined with enterprise-scale delivery capacity. | 4.2 | Full comparison |
| Master of Code Global | Enterprise brands, chat/voice AI, two decades' focus. | 20-year specialization in enterprise chat and voice AI, with named enterprise clients like T-Mobile and Burberry. | 4.1 | Full comparison |
| Markovate | Companies wanting AI agents/chatbots, ex-AT&T/IBM leadership. | CEO brings direct enterprise AI leadership experience (AT&T, IBM) rather than a purely technical or agency background. | 4.1 | Full comparison |
| SoluLab | Companies wanting AI development, blockchain/Web3 fluency. | Combines AI-native development with blockchain/Web3 expertise under one delivery team. | 4.1 | Full comparison |
| Zfort Group | Companies wanting a 24+ year firm's dedicated ML... | One of the longest-operating firms in this list (founded 2000) with a 5-star Clutch rating and broad ML sub-specialty coverage. | 4.0 | Full comparison |
| Yalantis | Compliance-sensitive industries, ML across all major clouds. | Compliance-first positioning combined with multi-cloud ML delivery (AWS, Azure, GCP) under one roof. | 4.0 | Full comparison |
| Space-O Technologies | Companies embedding ML into mobile or web apps. | 15 years of mobile/software product delivery experience (since 2010) with ML added as a production-application capability. | 4.0 | Full comparison |
| EPAM Systems | Large enterprises, $100K+ budgets, publicly-traded global partner. | Public-company (NYSE: EPAM) scale and compliance rigor, with 30+ years of engineering history predating the AI wave. | 4.0 | Full comparison |
| SoftServe | Enterprises wanting an established US/Ukraine dual-HQ firm. | 31 years of engineering history (since 1993) with dual US and Ukraine headquarters and 12,000+ employees. | 4.0 | Full comparison |
| DataArt | Regulated-industry enterprises, AI with built-in governance. | Artisyn, a proprietary AI-enabled operating model embedding governance and AI agents across the delivery lifecycle. | 3.9 | Full comparison |
| Cleveroad | Healthcare, logistics, fintech — Estonia-based full-stack firm. | Named to the 2025 Clutch 1000, placing it in the global top 30 highest-rated B2B service providers on the platform. | 3.9 | Full comparison |
| Existek | Mid-market companies, Clutch-recognized offshore AI add-on. | 4.9 Clutch rating with dual Ukraine/Romania Clutch top-developer recognition and a $25,000+ accessible entry point. | 3.9 | Full comparison |
| Konstant Infosolutions | Companies adding AI/ML to mobile or web products. | 175+ Clutch reviews — one of the highest review volumes in this list — from a 23-year mobile/web development track record. | 3.9 | Full comparison |
| Debut Infotech | Companies wanting ML development, blockchain engineering depth. | Blockchain-native since 2015, combining that engineering discipline with newer machine learning and AI automation services. | 3.9 | Full comparison |
| ValueCoders | Budget-conscious companies, 20-year Indian outsourcer, ML/AutoML. | 5.0 Clutch rating combined with a specific AutoML development service line, uncommon among generalist outsourcing firms. | 3.8 | Full comparison |
| OpenXcell | Companies wanting AI strategy plus custom LLM development. | 500–1,000 person scale combined with a specific custom-LLM development offering, not just general AI consulting. | 3.8 | Full comparison |
| Simform | Companies wanting AI/ML bundled with cloud and DevOps. | Ranked #2 worldwide among Clutch's Top B2B Service Providers of 2023 — one of the strongest third-party rankings in this list. | 3.8 | Full comparison |
| ScienceSoft | Enterprises wanting AI/MLOps from a 35-year-old consultancy. | 35+ years of continuous operating history (since 1989), among the longest-established vendors in this list. | 3.8 | Full comparison |
| Belitsoft | Companies integrating AI into SaaS, two decades' depth. | 20+ years of dedicated SaaS product development experience, applied specifically to AI model integration for B2B SaaS. | 3.8 | Full comparison |
| N-iX | Enterprises wanting ML bundled with cloud and analytics. | Seven consecutive years of Clutch top global IT services company recognition, combined with dedicated ML and MLOps consulting content. | 3.8 | Full comparison |
| ELEKS | Enterprises wanting AI/ML from a long-running CEE firm. | 33+ years of operating history (since 1991) with 1,000+ delivered data-driven projects and Global Outsourcing 100 recognition. | 3.7 | Full comparison |
| Intellias | Automotive, mobility, IoT — deep embedded-systems heritage. | Strong automotive/mobility and IoT sector heritage, giving it differentiated depth in embedded and connected-device ML use cases. | 3.7 | Full comparison |
| Andersen | Enterprises wanting AI consulting within a broad engineering... | 3,600+ in-house experts across 20 office locations, giving it exceptional breadth across programming languages and delivery models. | 3.7 | Full comparison |
| Innowise | Companies wanting a dedicated 300-person AI/data hub. | A specifically named 300+ person Data and AI hub within a much larger 3,500+ engineer group, giving both focus and scale. | 3.7 | Full comparison |
| Accenture | Largest global enterprises, AI transformation plus management consulting. | Everest Group's highest-rated Leader in both Data & Analytics and AI/Generative AI PEAK Matrix Assessments (2024), at unmatched global scale. | 3.7 | Full comparison |
DataRoot Labs FAQ
What is DataRoot Labs?
DataRoot Labs was founded in 2016 in Kyiv, Ukraine and has worked exclusively in AI and R&D since inception, building generative AI, machine learning, and data engineering systems for startups and enterprises. The company is notably lean — roughly 27 employees across three continents as of late 2025 — and also runs DataRoot University, a free ML and data engineering school with more than 6,000 graduates, which doubles as its own technical talent pipeline. Its small size and academic ties make it a lower-cost, highly specialized option relative to larger regional peers.
How much does DataRoot Labs charge?
DataRoot Labs uses project-based, dedicated team pricing. Minimum engagement starts at Not published. A discovery call is required to get project-specific quotes.
What tech stack does DataRoot Labs use?
DataRoot Labs works with Python, PyTorch, Hugging Face, LangChain, AWS, Docker. Primary industries served include Startups (cross-industry), FinTech, Healthcare.
Is DataRoot Labs right for enterprise?
Startups, direct access to senior ML engineers. 27–50 team size. Key consideration: 27–50 person team size limits capacity for multiple large concurrent enterprise engagements.
What are the best DataRoot Labs alternatives?
The best alternatives to DataRoot Labs depend on your use case. Top options are:
- Neurons Lab: founder-led ai strategy-to-production consultancy with no junior-heavy delivery layer.
- Provectus: ai-first systems integrator built around running production ml/ai infrastructure long-term.
- Tensorway: ai boutique backed by 20+ years of software delivery experience via parent company.
Compare DataRoot Labs with other Machine Learning Development companies
DataRoot Labs vs Neurons Lab DataRoot Labs vs Provectus DataRoot Labs vs Tensorway DataRoot Labs vs InData Labs DataRoot Labs vs XenonStack DataRoot Labs vs Grid Dynamics DataRoot Labs vs MobiDev DataRoot Labs vs Addepto DataRoot Labs vs LeewayHertz DataRoot Labs vs Softermii DataRoot Labs vs Sigma Software Group DataRoot Labs vs Master of Code Global DataRoot Labs vs Markovate DataRoot Labs vs SoluLab DataRoot Labs vs Zfort Group DataRoot Labs vs Yalantis DataRoot Labs vs Space-O Technologies DataRoot Labs vs EPAM Systems DataRoot Labs vs SoftServe DataRoot Labs vs DataArt DataRoot Labs vs Cleveroad DataRoot Labs vs Existek DataRoot Labs vs Konstant Infosolutions DataRoot Labs vs Debut Infotech DataRoot Labs vs ValueCoders DataRoot Labs vs OpenXcell DataRoot Labs vs Simform DataRoot Labs vs ScienceSoft DataRoot Labs vs Belitsoft DataRoot Labs vs N-iX DataRoot Labs vs ELEKS DataRoot Labs vs Intellias DataRoot Labs vs Andersen DataRoot Labs vs Innowise DataRoot Labs vs Accenture