DataRoot Labs vs Cleveroad: full comparison for 2026
Quick verdict
DataRoot Labs (4.5/5) edges ahead of Cleveroad (3.9/5) overall. DataRoot Labs is the better choice for Startups, direct access to senior ML engineers. Cleveroad is the stronger option for Healthcare, logistics, fintech — Estonia-based full-stack firm. The right choice depends on your project size, budget, and required tech stack.
DataRoot Labs vs Cleveroad: head-to-head summary
| Criterion | DataRoot Labs | Cleveroad |
|---|---|---|
| Founded | 2016 | 2011 |
| HQ | Kyiv, Ukraine | Tallinn, Estonia |
| Team size | 27–50 | 51–200 |
| Rating | 4.5 / 5 | 3.9 / 5 |
| Primary differentiator | Runs its own free ML/data-engineering school (DataRoot University, 6,000+ graduates) as a self-built talent pipeline | Named to the 2025 Clutch 1000, placing it in the global top 30 highest-rated B2B service providers on the platform |
| Pricing model | Project-based, dedicated team | Project-based, dedicated team |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, Hugging Face | TensorFlow, OpenCV, Python |
| Industries served | Startups (cross-industry), FinTech, Healthcare | Healthcare, Logistics & Supply Chain, FinTech, Retail & E-commerce |
DataRoot Labs vs Cleveroad: overview
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.
Cleveroad
Cleveroad was founded in 2011 and is headquartered in Tallinn, Estonia, with an R&D center there and additional delivery staff across five countries. The company has built more than a decade of experience in healthcare, logistics, fintech, and retail, delivering web and mobile applications alongside AI/ML solutions and dedicated development teams. Cleveroad was named to the 2025 Clutch 1000 — placing it among the top 30 highest-rated B2B service providers globally on the platform — though reported employee counts vary between roughly 50 and 200.
Services and capabilities: DataRoot Labs vs Cleveroad
| Capability | DataRoot Labs | Cleveroad |
|---|---|---|
| Custom ML Models | ✓ | ✓ |
| Computer Vision | ✗ | ✓ |
| NLP | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| Generative AI | ✓ | ✓ |
| AI Consulting | ✗ | ✗ |
Tech stack comparison: DataRoot Labs vs Cleveroad
| Framework / platform | DataRoot Labs | Cleveroad |
|---|---|---|
| TensorFlow | N/A | ✓ |
| PyTorch | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Google Cloud | N/A | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | ✓ | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: DataRoot Labs vs Cleveroad
| Criterion | DataRoot Labs | Cleveroad |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Project-based, Dedicated team | Project-based, Dedicated team, Fixed project |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: DataRoot Labs vs Cleveroad
| Dimension | DataRoot Labs | Cleveroad |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Startups (cross-industry), FinTech, Healthcare | Healthcare, Logistics & Supply Chain, FinTech |
| Best use cases | 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. | Healthcare or logistics company wants an AI feature built by a Clutch 1000-recognized full-stack development firm., Fintech startup needs both application development and ML modeling from a single Estonia-based vendor. |
| Typical project type | Project-based | Project-based |
DataRoot Labs vs Cleveroad: pros and cons
| DataRoot Labs | |
|---|---|
| + | Team of roughly 27 keeps overhead low, which typically translates into lower blended rates than 500+ person firms. |
| + | Exclusive AI/R&D focus since 2016 with no general software-development sideline diluting expertise. |
| + | DataRoot University (6,000+ graduates) gives the firm a homegrown, vetted junior-to-mid talent pipeline instead of relying purely on open-market hiring. |
| + | Cost/accessibility standout among the researched companies for startups with constrained AI budgets. |
| - | 27–50 person team size limits capacity for multiple large concurrent enterprise engagements. |
| - | Small headcount means less bench depth if a key engineer rotates off a project mid-engagement. |
| - | Thinner public enterprise case-study base than larger Ukraine-headquartered peers like N-iX or ELEKS. |
| Cleveroad | |
|---|---|
| + | 2025 Clutch 1000 placement (top 30 highest-rated global B2B providers) is a strong, independently verified distinction. |
| + | 13+ years of operating history (since 2011) with consistent focus on healthcare, logistics, and fintech verticals. |
| + | AI-assisted development services line reflects the firm keeping pace with modern AI-augmented delivery practices, not just AI as a client-facing product line. |
| - | Employee-count sources conflict meaningfully (50 vs. 51–200), so confirm current AI-specific team size before contracting. |
| - | AI/ML is one of several service lines (alongside general web/mobile development) rather than the firm's primary identity. |
Who should choose DataRoot Labs?
A typical fit: startup with a limited AI budget needs senior-level generative AI or ML engineering without enterprise agency overhead.
Runs its own free ML/data-engineering school (DataRoot University, 6,000+ graduates) as a self-built talent pipeline. Minimum engagement starts at Not published. Works best with clients in Startups (cross-industry), FinTech, Healthcare.
Who should choose Cleveroad?
A typical fit: healthcare or logistics company wants an AI feature built by a Clutch 1000-recognized full-stack development firm.
Named to the 2025 Clutch 1000, placing it in the global top 30 highest-rated B2B service providers on the platform. Minimum engagement starts at Not published. Works best with clients in Healthcare, Logistics & Supply Chain, FinTech, Retail & E-commerce.
Decision matrix: DataRoot Labs vs Cleveroad
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Cleveroad |
| You need a large dedicated team for an ongoing programme | DataRoot Labs |
| Your budget is at the lower end | Compare: DataRoot Labs (Not published) vs Cleveroad (Not published) |
| You need specialist depth in a specific vertical | Cleveroad |
| You need production MLOps support after model launch | Both offer MLOps support |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: DataRoot Labs vs Cleveroad
| Use case | DataRoot Labs fit | Cleveroad fit | Winner |
|---|---|---|---|
| Startup with a limited AI budget needs senior-level generative AI or ML engineering without enterprise agency overhead. | Strong | Strong | Both equally |
| Company wants a lean, R&D-focused partner for an experimental ML feature rather than a large staffing engagement. | Strong | Strong | Both equally |
| Healthcare or logistics company wants an AI feature built by a Clutch 1000-recognized full-stack development firm. | Limited | Strong | Cleveroad |
| Fintech startup needs both application development and ML modeling from a single Estonia-based vendor. | Limited | Strong | Cleveroad |
| Fixed-scope ML build | Limited | Limited | Both equally |
| Ongoing model retraining | Limited | Limited | Both equally |
Verdict: DataRoot Labs vs Cleveroad
DataRoot Labs (4.5/5) is the stronger overall choice for most Machine Learning Development projects. Runs its own free ML/data-engineering school (DataRoot University, 6,000+ graduates) as a self-built talent pipeline.
Cleveroad (3.9/5) is worth a look if you need fintech startup needs both application development and ML modeling from a single Estonia-based vendor. If your situation matches that, Cleveroad is a competitive option.
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DataRoot Labs vs Cleveroad FAQ
Is DataRoot Labs better than Cleveroad?
DataRoot Labs (4.5/5) scores higher overall, but "better" depends on your use case. DataRoot Labs's strongest advantage: team of roughly 27 keeps overhead low, which typically translates into lower blended rates than 500+ person firms. Cleveroad's strongest advantage: 2025 Clutch 1000 placement (top 30 highest-rated global B2B providers) is a strong, independently verified distinction.
How do DataRoot Labs and Cleveroad differ in pricing?
DataRoot Labs uses project-based, dedicated team pricing with a minimum engagement of Not published. Cleveroad uses project-based, dedicated team pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: DataRoot Labs or Cleveroad?
Cleveroad is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between DataRoot Labs and Cleveroad?
DataRoot Labs's primary differentiator is: runs its own free ML/data-engineering school (DataRoot University, 6,000+ graduates) as a self-built talent pipeline. Cleveroad's primary differentiator is: named to the 2025 Clutch 1000, placing it in the global top 30 highest-rated B2B service providers on the platform. They also differ in team size (27–50 vs 51–200), minimum engagement (Not published vs Not published), and primary industries served (Startups (cross-industry), FinTech vs Healthcare, Logistics & Supply Chain).