Cleveroad vs DataArt: full comparison for 2026
Quick verdict
Cleveroad (4.0/5) edges ahead of DataArt (3.9/5) overall. Cleveroad is the better choice for startups needing AI features inside a mobile or web product. DataArt is the stronger option for enterprises in finance or healthcare needing AI at global scale. The right choice depends on your project size, budget, and required tech stack.
Cleveroad vs DataArt: head-to-head summary
| Criterion | Cleveroad | DataArt |
|---|---|---|
| Founded | 2011 | 1997 |
| HQ | Krakow, Poland | New York, United States |
| Team size | 113-200 | 5,700+ |
| Rating | 4.0 / 5 | 3.9 / 5 |
| Primary differentiator | Production-deployment discipline carried over from a decade of mobile and web delivery | Nearly 30 years of engineering history across 30-plus global delivery locations |
| Pricing model | Fixed project or dedicated team | Dedicated team or retainer |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, React Native, AWS | Python, AWS, Azure |
| Industries served | Retail & e-commerce, Healthcare, Logistics | Financial services, Healthcare, Media & entertainment, Travel & hospitality |
Cleveroad vs DataArt: overview
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.
DataArt
DataArt goes back to 1997, founded by Eugene Goland, and is headquartered in New York City with roughly 5,700 employees spread across more than 30 locations in the US, Europe, the UK, Latin America, and the UAE. The firm delivers data, analytics, and AI platforms for finance, media and entertainment, healthcare and life sciences, retail, and travel and hospitality clients. Nearly three decades of history gives it a longer track record than almost every other firm here, though AI is delivered as part of a broader software engineering practice rather than a standalone specialty.
Services and capabilities: Cleveroad vs DataArt
| Capability | Cleveroad | DataArt |
|---|---|---|
| Generative AI | ✓ | ✗ |
| Machine learning | ✓ | ✓ |
| AI agents | ✗ | ✗ |
| MLOps | ✗ | ✓ |
| AI consulting | ✗ | ✗ |
| Fixed-price projects | ✓ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: Cleveroad vs DataArt
| Framework / platform | Cleveroad | DataArt |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | N/A | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Kubernetes | N/A | ✓ |
Pricing comparison: Cleveroad vs DataArt
| Criterion | Cleveroad | DataArt |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed project, Dedicated team | Dedicated team, Retainer |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Cleveroad vs DataArt
| Dimension | Cleveroad | DataArt |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Retail & e-commerce, Healthcare, Logistics | Financial services, Healthcare, Media & entertainment |
| Best use cases | 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. | Building AI-driven analytics platforms for finance or healthcare clients with strict compliance needs., Running a long-term AI and data engineering program with a financially established vendor. |
| Typical project type | Fixed project | Dedicated team |
Cleveroad vs DataArt: pros and cons
| 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 |
| DataArt | |
|---|---|
| + | Nearly three decades of software engineering history, among the longest reviewed here. |
| + | 5,700-plus employees across 30-plus locations globally. |
| + | Named industry focus areas (finance, healthcare, travel) show real vertical depth. |
| + | Data and analytics platform experience supports AI work that needs solid data foundations. |
| - | AI sits inside a much broader software engineering practice rather than being the firm's core identity |
| - | Enterprise scale typically means slower onboarding than smaller, more agile AI boutiques |
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.
Who should choose DataArt?
A typical fit: building AI-driven analytics platforms for finance or healthcare clients with strict compliance needs.
Nearly 30 years of engineering history across 30-plus global delivery locations. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Media & entertainment, Travel & hospitality.
Decision matrix: Cleveroad vs DataArt
| 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 | Cleveroad |
| Your budget is at the lower end | Compare: Cleveroad (Not disclosed) vs DataArt (Not disclosed) |
| You need specialist depth in a specific vertical | DataArt |
| 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: Cleveroad vs DataArt
| Use case | Cleveroad fit | DataArt fit | Winner |
|---|---|---|---|
| Adding AI features to a mobile app already in production. | Strong | Limited | Cleveroad |
| Getting a startup MVP built with AI as one feature among several, not the entire product. | Strong | Limited | Cleveroad |
| Building AI-driven analytics platforms for finance or healthcare clients with strict compliance needs. | Limited | Strong | DataArt |
| Running a long-term AI and data engineering program with a financially established vendor. | Limited | Strong | DataArt |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Cleveroad vs DataArt
Cleveroad (4.0/5) is the stronger overall choice for most AI Development projects. Production-deployment discipline carried over from a decade of mobile and web delivery.
DataArt (3.9/5) is worth a look if you need running a long-term AI and data engineering program with a financially established vendor. If your situation matches that, DataArt is a competitive option.
Related comparisons
Cleveroad vs DataArt FAQ
Is Cleveroad better than DataArt?
Cleveroad (4.0/5) scores higher overall, but "better" depends on your use case. Cleveroad's strongest advantage: mobile and web development roots translate into disciplined production deployment practices. DataArt's strongest advantage: nearly three decades of software engineering history, among the longest reviewed here.
How do Cleveroad and DataArt differ in pricing?
Cleveroad uses fixed project or dedicated team pricing. DataArt uses dedicated team or retainer pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Cleveroad or DataArt?
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 Cleveroad and DataArt?
Cleveroad's primary differentiator is: production-deployment discipline carried over from a decade of mobile and web delivery. DataArt's primary differentiator is: nearly 30 years of engineering history across 30-plus global delivery locations. They also differ in team size (113-200 vs 5,700+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Retail & e-commerce, Healthcare vs Financial services, Healthcare).
Verify all details directly with each firm before making a decision.