DataRoot Labs vs Growexx: full comparison for 2026
Quick verdict
DataRoot Labs (4.4/5) edges ahead of Growexx (3.9/5) overall. DataRoot Labs is the better choice for startups needing applied ML research capacity. Growexx is the stronger option for startups wanting fast-growing engineering capacity with AI. The right choice depends on your project size, budget, and required tech stack.
DataRoot Labs vs Growexx: head-to-head summary
| Criterion | DataRoot Labs | Growexx |
|---|---|---|
| Founded | 2016 | 2020 |
| HQ | Kyiv, Ukraine | Ahmedabad, India |
| Team size | 11-50 | 240-260 |
| Rating | 4.4 / 5 | 3.9 / 5 |
| Primary differentiator | Research-oriented engagement style built for startup speed, not enterprise procurement | Younger, fast-scaling team actively expanding a dedicated AI division |
| 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, AWS, Node.js |
| Industries served | Healthtech, Fintech, Retail & e-commerce | SaaS, Fintech, Retail & e-commerce |
DataRoot Labs vs Growexx: 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.
Growexx
Growexx was founded in 2020 by Vikas Agarwaal and Ruchit Jani and is based in Ahmedabad, India, with a headcount reported between roughly 240 and 260 employees. As one of the younger agencies on this list, Growexx built its practice around product engineering with machine learning and data engineering woven in rather than carrying years of AI-specific case studies. A separate, more recently reported entity called Growexx AI Solutions suggests active investment in expanding this side of the business.
Services and capabilities: DataRoot Labs vs Growexx
| Capability | DataRoot Labs | Growexx |
|---|---|---|
| Generative AI | ✗ | ✗ |
| Machine learning | ✓ | ✓ |
| AI agents | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| AI consulting | ✓ | ✗ |
| Fixed-price projects | ✓ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: DataRoot Labs vs Growexx
| Framework / platform | DataRoot Labs | Growexx |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | ✓ | N/A |
| TensorFlow | N/A | N/A |
| LangChain | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: DataRoot Labs vs Growexx
| Criterion | DataRoot Labs | Growexx |
|---|---|---|
| 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 Growexx
| Dimension | DataRoot Labs | Growexx |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthtech, Fintech, Retail & e-commerce | SaaS, Fintech, 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. | Working with a fast-growing team on a startup product that needs both engineering and ML capacity., Getting product engineering and machine learning from one team as a company scales quickly. |
| Typical project type | Dedicated team | Fixed project |
DataRoot Labs vs Growexx: 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 |
| Growexx | |
|---|---|
| + | Rapid headcount growth since 2020 suggests strong client demand and reinvestment. |
| + | Actively expanding a dedicated AI division, evidenced by the separate Growexx AI Solutions entity. |
| + | Founder-led team still closely involved at this stage of growth. |
| + | Competitive Ahmedabad-based delivery pricing. |
| - | Founded in 2020, so has less AI-specific track record than most agencies on this list |
| - | Public information on named AI client projects is limited so far |
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 Growexx?
A typical fit: working with a fast-growing team on a startup product that needs both engineering and ML capacity.
Younger, fast-scaling team actively expanding a dedicated AI division. Minimum engagement is not publicly disclosed. Works best with clients in SaaS, Fintech, Retail & e-commerce.
Decision matrix: DataRoot Labs vs Growexx
| 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 Growexx (Not disclosed) |
| You need specialist depth in a specific vertical | DataRoot Labs |
| 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 Growexx
| Use case | DataRoot Labs fit | Growexx 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 |
| Working with a fast-growing team on a startup product that needs both engineering and ML capacity. | Limited | Strong | Growexx |
| Getting product engineering and machine learning from one team as a company scales quickly. | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: DataRoot Labs vs Growexx
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.
Growexx (3.9/5) is worth a look if you need getting product engineering and machine learning from one team as a company scales quickly. If your situation matches that, Growexx is a competitive option.
Related comparisons
DataRoot Labs vs Growexx FAQ
Is DataRoot Labs better than Growexx?
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. Growexx's strongest advantage: rapid headcount growth since 2020 suggests strong client demand and reinvestment.
How do DataRoot Labs and Growexx differ in pricing?
DataRoot Labs uses dedicated team or fixed project pricing. Growexx 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 Growexx?
Growexx 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 Growexx?
DataRoot Labs's primary differentiator is: research-oriented engagement style built for startup speed, not enterprise procurement. Growexx's primary differentiator is: Younger, fast-scaling team actively expanding a dedicated AI division. They also differ in team size (11-50 vs 240-260), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Healthtech, Fintech vs SaaS, Fintech).
Verify all details directly with each agency before making a decision.