InData Labs vs Cleveroad: full comparison for 2026
Quick verdict
InData Labs (4.1/5) edges ahead of Cleveroad (4.0/5) overall. InData Labs is the better choice for teams needing data science depth before an AI build. Cleveroad is the stronger option for startups needing AI features inside a mobile or web product. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs Cleveroad: head-to-head summary
| Criterion | InData Labs | Cleveroad |
|---|---|---|
| Founded | 2014 | 2011 |
| HQ | Limassol, Cyprus | Krakow, Poland |
| Team size | 51-200 | 113-200 |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Primary differentiator | Data-science-first heritage that predates the generative AI branding wave | Production-deployment discipline carried over from a decade of mobile and web delivery |
| Pricing model | Fixed project or dedicated team | Fixed project or dedicated team |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, scikit-learn, TensorFlow | Python, React Native, AWS |
| Industries served | Retail & e-commerce, Gaming, Fintech, Healthcare | Retail & e-commerce, Healthcare, Logistics |
InData Labs vs Cleveroad: overview
InData Labs
InData Labs traces its founding to 2014 and gaming-industry veteran Marat Karpeko, with headquarters in Cyprus and additional offices reported in Lithuania and the US. Reported staff counts swing between roughly 65 and 200 across different trackers, common for firms mixing core employees with project-based contractors. The firm's practice centers on data science: predictive analytics, natural language processing, computer vision, and large-scale data analytics, positioning it closer to a data-first consultancy than a generative-AI-branded shop.
Cleveroad
Cleveroad has operated since 2011, though public sources disagree on where: LinkedIn lists Claymont, Delaware, while other trackers point to Krakow, Poland as the working base. Employee counts vary similarly, from roughly 113 up to a LinkedIn-reported 201-500. The firm's roots are in mobile and web development for startups and enterprise clients alike, with safe, production-grade AI deployment positioned as a newer strength built on that existing delivery discipline.
Services and capabilities: InData Labs vs Cleveroad
| Capability | InData Labs | Cleveroad |
|---|---|---|
| Generative AI | ✗ | ✓ |
| Machine learning | ✓ | ✓ |
| AI agents | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| AI consulting | ✗ | ✗ |
| Fixed-price projects | ✓ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: InData Labs vs Cleveroad
| Framework / platform | InData Labs | Cleveroad |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | N/A | N/A |
| TensorFlow | ✓ | ✓ |
| LangChain | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: InData Labs vs Cleveroad
| Criterion | InData Labs | Cleveroad |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed project, Dedicated team | Fixed project, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: InData Labs vs Cleveroad
| Dimension | InData Labs | Cleveroad |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Retail & e-commerce, Gaming, Fintech | Retail & e-commerce, Healthcare, Logistics |
| Best use cases | Building predictive models from an existing data warehouse or event stream., Adding computer vision to a product that already produces image or video data. | Adding AI features to a mobile app already in production., Getting a startup MVP built with AI as one feature among several, not the entire product. |
| Typical project type | Fixed project | Fixed project |
InData Labs vs Cleveroad: pros and cons
| InData Labs | |
|---|---|
| + | Founder's gaming background brings real-time data processing experience to computer vision work. |
| + | Cyprus headquarters (EU-based) can simplify GDPR-aligned data handling for European clients. |
| + | Predictive analytics and NLP expertise predates the current generative AI wave. |
| + | More than a decade of track record in a narrower, more defensible specialty. |
| - | Reported team size varies close to 3x across public sources |
| - | Less generative AI and LLM-specific public case work than firms built specifically around that |
| Cleveroad | |
|---|---|
| + | Mobile and web development roots translate into disciplined production deployment practices. |
| + | Over a decade of delivery history across startup and enterprise clients. |
| + | Operates across four continents, giving flexible timezone coverage. |
| + | AI is positioned as an addition to, not a replacement for, established delivery skills. |
| - | Headquarters and employee count are reported inconsistently across public sources |
| - | AI-specific case studies are less prominent than the firm's mobile and web development portfolio |
Who should choose InData Labs?
A typical fit: building predictive models from an existing data warehouse or event stream.
Data-science-first heritage that predates the generative AI branding wave. Minimum engagement is not publicly disclosed. Works best with clients in Retail & e-commerce, Gaming, Fintech, Healthcare.
Who should choose Cleveroad?
A typical fit: adding AI features to a mobile app already in production.
Production-deployment discipline carried over from a decade of mobile and web delivery. Minimum engagement is not publicly disclosed. Works best with clients in Retail & e-commerce, Healthcare, Logistics.
Decision matrix: InData Labs vs Cleveroad
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | InData Labs |
| You need a large dedicated team for an ongoing programme | InData Labs |
| Your budget is at the lower end | Compare: InData Labs (Not disclosed) vs Cleveroad (Not disclosed) |
| You need specialist depth in a specific vertical | InData Labs |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: InData Labs vs Cleveroad
| Use case | InData Labs fit | Cleveroad fit | Winner |
|---|---|---|---|
| Building predictive models from an existing data warehouse or event stream. | Strong | Limited | InData Labs |
| Adding computer vision to a product that already produces image or video data. | Strong | Strong | Both equally |
| Adding AI features to a mobile app already in production. | Strong | Strong | Both equally |
| Getting a startup MVP built with AI as one feature among several, not the entire product. | Limited | Strong | Cleveroad |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: InData Labs vs Cleveroad
InData Labs (4.1/5) is the stronger overall choice for most AI Development projects. Data-science-first heritage that predates the generative AI branding wave.
Cleveroad (4.0/5) is worth a look if you need getting a startup MVP built with AI as one feature among several, not the entire product. If your situation matches that, Cleveroad is a competitive option.
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InData Labs vs Cleveroad FAQ
Is InData Labs better than Cleveroad?
InData Labs (4.1/5) scores higher overall, but "better" depends on your use case. InData Labs's strongest advantage: Founder's gaming background brings real-time data processing experience to computer vision work. Cleveroad's strongest advantage: mobile and web development roots translate into disciplined production deployment practices.
How do InData Labs and Cleveroad differ in pricing?
InData Labs uses fixed project or dedicated team pricing. Cleveroad 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: InData 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 firm before shortlisting.
What are the main differences between InData Labs and Cleveroad?
InData Labs's primary differentiator is: data-science-first heritage that predates the generative AI branding wave. Cleveroad's primary differentiator is: production-deployment discipline carried over from a decade of mobile and web delivery. They also differ in team size (51-200 vs 113-200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Retail & e-commerce, Gaming vs Retail & e-commerce, Healthcare).
Verify all details directly with each firm before making a decision.