10Pearls vs DataArt: full comparison for 2026
Quick verdict
10Pearls (3.9/5) edges ahead of DataArt (3.9/5) overall. 10Pearls is the better choice for enterprises wanting AI advisory bundled with digital transformation. DataArt is the stronger option for enterprises in finance or healthcare needing AI advisory at global scale. The right choice depends on your project size, budget, and required tech stack.
10Pearls vs DataArt: head-to-head summary
| Criterion | 10Pearls | DataArt |
|---|---|---|
| Founded | 2004 | 1997 |
| HQ | Vienna, United States | New York, United States |
| Team size | 1,800-1,950 | 5,700+ |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Primary differentiator | Two decades of digital transformation delivery with AI advisory as an established add-on | Nearly 30 years of engineering history across 30-plus global delivery locations |
| Pricing model | Dedicated team or retainer | Dedicated team or retainer |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, AWS, Azure | Python, AWS, Azure |
| Industries served | Financial services, Healthcare, Retail & e-commerce | Financial services, Healthcare, Media & entertainment, Travel & hospitality |
10Pearls vs DataArt: overview
10Pearls
10Pearls was founded in 2004 by brothers Imran and Zeeshan Aftab and is headquartered in Vienna, Virginia. The firm operates across six countries with roughly 1,800-1,950 employees, and one source cites 2024 revenue near $358 million. Its core business is software development, product design, and digital transformation broadly, with AI advisory positioned as one service line inside that larger practice.
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. The firm delivers data, analytics, and AI advisory for finance, media and entertainment, healthcare, retail, and travel and hospitality clients. Nearly three decades of history give it a longer track record than almost every other agency here, though AI advisory is delivered as part of a broader software engineering practice.
Services and capabilities: 10Pearls vs DataArt
| Capability | 10Pearls | DataArt |
|---|---|---|
| AI strategy consulting | ✓ | ✓ |
| Generative AI | ✗ | ✗ |
| Machine learning | ✗ | ✗ |
| Data engineering | ✓ | ✓ |
| MLOps | ✗ | ✓ |
| Fixed-price projects | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: 10Pearls vs DataArt
| Framework / platform | 10Pearls | DataArt |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | N/A | N/A |
| Kubernetes | ✓ | ✓ |
| LangChain | N/A | N/A |
| PyTorch | N/A | N/A |
Pricing comparison: 10Pearls vs DataArt
| Criterion | 10Pearls | DataArt |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Dedicated team, Retainer | Dedicated team, Retainer |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: 10Pearls vs DataArt
| Dimension | 10Pearls | DataArt |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Healthcare, Retail & e-commerce | Financial services, Healthcare, Media & entertainment |
| Best use cases | Bundling an AI strategy engagement into a larger digital transformation contract., Needing a financially stable US agency for a multi-year enterprise engagement. | Getting an AI strategy assessment for finance or healthcare clients with strict compliance needs., Running a long-term AI advisory and data engineering program with a financially established vendor. |
| Typical project type | Dedicated team | Dedicated team |
10Pearls vs DataArt: pros and cons
| 10Pearls | |
|---|---|
| + | Reported revenue near $358 million signals financial stability for long engagements. |
| + | Twenty-plus years of digital transformation delivery experience. |
| + | A US headquarters simplifies contracting for domestic enterprise buyers. |
| + | A six-country delivery footprint supports round-the-clock development cycles. |
| - | AI advisory is one of several service lines rather than the agency's primary specialty |
| - | Scale means engagement minimums are typically higher than boutique AI agencies |
| 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 advisory grounded in solid data foundations. |
| - | AI advisory sits inside a much broader software engineering practice rather than being the agency's core identity |
| - | Enterprise scale typically means slower onboarding than smaller, more agile AI boutiques |
Who should choose 10Pearls?
A typical fit: bundling an AI strategy engagement into a larger digital transformation contract.
Two decades of digital transformation delivery with AI advisory as an established add-on. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail & e-commerce.
Who should choose DataArt?
A typical fit: getting an AI strategy assessment 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: 10Pearls vs DataArt
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | 10Pearls |
| Your budget is at the lower end | Compare: 10Pearls (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 | 10Pearls |
Use case fit: 10Pearls vs DataArt
| Use case | 10Pearls fit | DataArt fit | Winner |
|---|---|---|---|
| Bundling an AI strategy engagement into a larger digital transformation contract. | Strong | Limited | 10Pearls |
| Needing a financially stable US agency for a multi-year enterprise engagement. | Strong | Strong | Both equally |
| Getting an AI strategy assessment for finance or healthcare clients with strict compliance needs. | Limited | Strong | DataArt |
| Running a long-term AI advisory and data engineering program with a financially established vendor. | Strong | Strong | Both equally |
| Fixed-price project | Limited | Limited | Both equally |
| Dedicated team model | Limited | Limited | Both equally |
Verdict: 10Pearls vs DataArt
10Pearls (3.9/5) is the stronger overall choice for most AI Consulting projects. Two decades of digital transformation delivery with AI advisory as an established add-on.
DataArt (3.9/5) is worth a look if you need running a long-term AI advisory and data engineering program with a financially established vendor. If your situation matches that, DataArt is a competitive option.
Related comparisons
10Pearls vs DataArt FAQ
Is 10Pearls better than DataArt?
10Pearls (3.9/5) scores higher overall, but "better" depends on your use case. 10Pearls's strongest advantage: reported revenue near $358 million signals financial stability for long engagements. DataArt's strongest advantage: nearly three decades of software engineering history, among the longest reviewed here.
How do 10Pearls and DataArt differ in pricing?
10Pearls uses dedicated team or retainer 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: 10Pearls or DataArt?
10Pearls 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 10Pearls and DataArt?
10Pearls's primary differentiator is: two decades of digital transformation delivery with AI advisory as an established add-on. DataArt's primary differentiator is: nearly 30 years of engineering history across 30-plus global delivery locations. They also differ in team size (1,800-1,950 vs 5,700+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Financial services, Healthcare).
Verify all details directly with each agency before making a decision.