DataRoot Labs vs LeewayHertz: full comparison for 2026
Quick verdict
DataRoot Labs (4.4/5) edges ahead of LeewayHertz (4.1/5) overall. DataRoot Labs is the better choice for startups needing applied ML research capacity. LeewayHertz is the stronger option for buyers wanting broad AI service coverage in one agency. The right choice depends on your project size, budget, and required tech stack.
DataRoot Labs vs LeewayHertz: head-to-head summary
| Criterion | DataRoot Labs | LeewayHertz |
|---|---|---|
| Founded | 2016 | 2007 |
| HQ | Kyiv, Ukraine | San Francisco, United States |
| Team size | 11-50 | 150-300 |
| Rating | 4.4 / 5 | 4.1 / 5 |
| Primary differentiator | Research-oriented engagement style built for startup speed, not enterprise procurement | Backed by The Hackett Group's consulting network following its 2024 acquisition |
| Pricing model | Dedicated team or fixed project | Fixed project or dedicated team |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, PyTorch, scikit-learn | Python, PyTorch, OpenAI API |
| Industries served | Healthtech, Fintech, Retail & e-commerce | Financial services, Healthcare, Retail & e-commerce, Manufacturing |
DataRoot Labs vs LeewayHertz: overview
DataRoot Labs
DataRoot Labs runs out of Kyiv and has focused on applied data science research since founding in 2016. Public staff counts vary widely, from about 11 to nearly 200 depending on the source, likely a function of how contractors get counted differently across trackers. What's consistent is the specialty: machine learning models, computer vision pipelines, and hands-on AI R&D for startups that need research capability without hiring a full internal team.
LeewayHertz
LeewayHertz has operated from San Francisco since 2007, though its ownership changed in September 2024 when The Hackett Group acquired the company. That's relevant to anyone evaluating long-term strategic direction, since the agency now answers to a larger consulting parent. Public employee counts have also shifted, from roughly 300 in earlier reporting to about 182 by mid-2026, worth confirming directly given the volume of content marketing the agency publishes relative to its actual team size.
Services and capabilities: DataRoot Labs vs LeewayHertz
| Capability | DataRoot Labs | LeewayHertz |
|---|---|---|
| Generative AI | ✗ | ✓ |
| Machine learning | ✓ | ✓ |
| AI agents | ✗ | ✓ |
| MLOps | ✗ | ✗ |
| AI consulting | ✓ | ✗ |
| Fixed-price projects | ✓ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: DataRoot Labs vs LeewayHertz
| Framework / platform | DataRoot Labs | LeewayHertz |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| TensorFlow | N/A | N/A |
| LangChain | N/A | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: DataRoot Labs vs LeewayHertz
| Criterion | DataRoot Labs | LeewayHertz |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Dedicated team, Fixed project | Fixed project, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: DataRoot Labs vs LeewayHertz
| Dimension | DataRoot Labs | LeewayHertz |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthtech, Fintech, Retail & e-commerce | Financial services, Healthcare, Retail & e-commerce |
| Best use cases | Standing up an ML proof of concept ahead of a seed round., Getting a second, independent build on a computer vision pipeline. | Consolidating several AI workstreams under one vendor relationship., Working with an agency backed by a larger consulting parent for enterprise credibility. |
| Typical project type | Dedicated team | Fixed project |
DataRoot Labs vs LeewayHertz: pros and cons
| DataRoot Labs | |
|---|---|
| + | Research culture suits startups needing genuine experimentation over templated builds. |
| + | Small team keeps direct communication between founders and the engineers doing the work. |
| + | Kyiv talent pool offers strong ML fundamentals at lower cost than US or Western European teams. |
| + | Named computer vision projects back up the firm's stated specialty. |
| - | Employee counts differ substantially across public sources, making capacity hard to verify |
| - | Little public evidence of enterprise-scale delivery experience |
| LeewayHertz | |
|---|---|
| + | Broad coverage across generative AI, machine learning, and AI agents under one agency. |
| + | The Hackett Group acquisition adds access to a larger consulting and benchmarking network. |
| + | Close to two decades of operating history predating the current AI boom. |
| + | High volume of published technical content makes its approach easy to evaluate before hiring. |
| - | Now owned by The Hackett Group as of 2024, which may shift long-term positioning |
| - | Reported headcount has roughly halved across recent public data, worth confirming directly |
Who should choose DataRoot Labs?
A typical fit: standing up an ML proof of concept ahead of a seed round.
Research-oriented engagement style built for startup speed, not enterprise procurement. Minimum engagement is not publicly disclosed. Works best with clients in Healthtech, Fintech, Retail & e-commerce.
Who should choose LeewayHertz?
A typical fit: consolidating several AI workstreams under one vendor relationship.
Backed by The Hackett Group's consulting network following its 2024 acquisition. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail & e-commerce, Manufacturing.
Decision matrix: DataRoot Labs vs LeewayHertz
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | DataRoot Labs |
| You need a large dedicated team for an ongoing programme | DataRoot Labs |
| Your budget is at the lower end | Compare: DataRoot Labs (Not disclosed) vs LeewayHertz (Not disclosed) |
| You need specialist depth in a specific vertical | LeewayHertz |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | DataRoot Labs |
Use case fit: DataRoot Labs vs LeewayHertz
| Use case | DataRoot Labs fit | LeewayHertz fit | Winner |
|---|---|---|---|
| Standing up an ML proof of concept ahead of a seed round. | Strong | Limited | DataRoot Labs |
| Getting a second, independent build on a computer vision pipeline. | Strong | Strong | Both equally |
| Consolidating several AI workstreams under one vendor relationship. | Limited | Strong | LeewayHertz |
| Working with an agency backed by a larger consulting parent for enterprise credibility. | Limited | Strong | LeewayHertz |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: DataRoot Labs vs LeewayHertz
DataRoot Labs (4.4/5) is the stronger overall choice for most AI Development projects. Research-oriented engagement style built for startup speed, not enterprise procurement.
LeewayHertz (4.1/5) is worth a look if you need working with an agency backed by a larger consulting parent for enterprise credibility. If your situation matches that, LeewayHertz is a competitive option.
Related comparisons
DataRoot Labs vs LeewayHertz FAQ
Is DataRoot Labs better than LeewayHertz?
DataRoot Labs (4.4/5) scores higher overall, but "better" depends on your use case. DataRoot Labs's strongest advantage: research culture suits startups needing genuine experimentation over templated builds. LeewayHertz's strongest advantage: broad coverage across generative AI, machine learning, and AI agents under one agency.
How do DataRoot Labs and LeewayHertz differ in pricing?
DataRoot Labs uses dedicated team or fixed project pricing. LeewayHertz uses fixed project or dedicated team pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: DataRoot Labs or LeewayHertz?
LeewayHertz is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between DataRoot Labs and LeewayHertz?
DataRoot Labs's primary differentiator is: research-oriented engagement style built for startup speed, not enterprise procurement. LeewayHertz's primary differentiator is: backed by The Hackett Group's consulting network following its 2024 acquisition. They also differ in team size (11-50 vs 150-300), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Healthtech, Fintech vs Financial services, Healthcare).
Verify all details directly with each agency before making a decision.