DataArt vs Exadel: full comparison for 2026
Last updated: July 2026
Quick verdict
Exadel (4.1/5) edges ahead of DataArt (3.9/5) overall. Exadel is the better choice for enterprises wanting model design through MLOps and production deployment from a firm with 25+ years of engineering history.. DataArt is the stronger option for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner.. The right choice depends on your project size, budget, and required tech stack.
DataArt vs Exadel: head-to-head summary
| Criterion | DataArt | Exadel |
|---|---|---|
| Founded | 1997 | 1998 |
| HQ | New York, USA | Walnut Creek, California, USA |
| Team size | 5,001–10,000 | 1,001–5,000 |
| Rating | 3.9 / 5 | 4.1 / 5 |
| Best for | Enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner. | Enterprises wanting model design through MLOps and production deployment from a firm with 25+ years of engineering history. |
| Pricing model | Fixed project, dedicated team, staff augmentation | Fixed project and managed services |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Azure OpenAI, AWS | Python, TensorFlow, Kubernetes |
| Industries served | Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality | Technology/SaaS, Financial Services, Healthcare, Retail |
DataArt vs Exadel: overview
DataArt
DataArt is a software engineering and consulting company founded in 1997 in New York by Eugene Goland, with roughly 5,400 employees across more than 30 locations spanning the US, Europe, Latin America, India, and the UAE. The firm added an Advanced AI Strategy Consulting service line in 2024, delivering data, analytics, and AI/ML work alongside its long-standing core software engineering practice.
Exadel
Exadel is a global software consulting and development company founded in Silicon Valley in 1998, headquartered in Walnut Creek, California, with roughly 2,000+ engineers across more than 30 delivery centers in 17 countries. The firm names AI and data management, including generative AI and MLOps, as one of five core service areas alongside strategy consulting, digital experience, and managed services.
Services and capabilities: DataArt vs Exadel
| Capability | DataArt | Exadel |
|---|---|---|
| Custom ML model development | ✓ | ✓ |
| Deep learning & computer vision | ✗ | ✗ |
| NLP & LLM / Generative AI | ✗ | ✓ |
| MLOps & production deployment | ✗ | ✓ |
| Data engineering | ✓ | ✓ |
| AI strategy consulting | ✓ | ✗ |
| Staff augmentation | ✓ | ✗ |
Tech stack comparison: DataArt vs Exadel
| Framework / platform | DataArt | Exadel |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | N/A | ✓ |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | ✓ |
| Databricks | ✓ | N/A |
| LangChain | N/A | N/A |
Pricing comparison: DataArt vs Exadel
| Criterion | DataArt | Exadel |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Fixed project, Dedicated team, Staff augmentation | Fixed project, Managed services |
| Rate transparency | Not public | Not public |
| Price tier | Enterprise / not published | Enterprise / not published |
Target audience comparison: DataArt vs Exadel
| Dimension | DataArt | Exadel |
|---|---|---|
| Best company size | Enterprise | Startup to mid-market |
| Best industries | Financial Services, Media & Entertainment, Healthcare | Technology/SaaS, Financial Services, Healthcare |
| Best use cases | Enterprises wanting AI strategy consulting bundled with long-term software engineering delivery, Media or travel companies needing broad-based data and AI/ML capability | Enterprises needing the full model lifecycle from design through MLOps and production integration, Generative AI application builds requiring responsible-AI governance |
| Typical project type | Fixed project | Fixed project |
DataArt vs Exadel: pros and cons
| DataArt | |
|---|---|
| + | 28 years of continuous operation under the same founder-led leadership |
| + | 30+ global delivery locations across five regions supports broad geographic coverage |
| + | Named AI Strategy Consulting service line launched in 2024 shows deliberate recent AI investment |
| + | Broad industry coverage spanning finance, media, healthcare, and travel |
| - | AI Strategy Consulting is a comparatively recent addition (2024) versus firms with a decade-plus dedicated AI/ML focus |
| - | 5,400-employee scale sits within a broad general software-engineering practice rather than an AI-first firm |
| - | Minimum engagement size not publicly disclosed |
| Exadel | |
|---|---|
| + | 27 years of continuous operation since its 1998 Silicon Valley founding |
| + | AI and Data Management is one of only five named core service lines, indicating strategic (not incidental) investment |
| + | 2,000+ engineers across 30+ delivery centers supports large, distributed programs |
| + | Named focus on responsible AI 'built for trust and scale' alongside technical delivery |
| - | AI/ML sits alongside four other core service lines (strategy, digital experience, digital products, managed services) rather than being the sole focus |
| - | Less boutique-style founder access than smaller specialist firms on this list |
| - | Minimum engagement size not publicly disclosed |
Who should choose DataArt?
DataArt is the right choice for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner..
28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated AI strategy consulting service line.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality.
Who should choose Exadel?
Exadel is the right choice for enterprises wanting model design through MLOps and production deployment from a firm with 25+ years of engineering history..
Explicit end-to-end scope 'from model design to MLOps and integration' as one of five named core service lines.. Minimum engagement starts at Not published. Works best with clients in Technology/SaaS, Financial Services, Healthcare, Retail.
Decision matrix: DataArt vs Exadel
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | DataArt |
| You need a large dedicated team for an ongoing programme | DataArt |
| Your budget is at the lower end | Compare: DataArt (Not published) vs Exadel (Not published) |
| You need specialist depth in a specific vertical | DataArt |
| You need staff augmentation or team extension | DataArt |
| You need consulting before committing to a build | DataArt |
Use case fit: DataArt vs Exadel
| Use case | DataArt fit | Exadel fit | Winner |
|---|---|---|---|
| Enterprises wanting AI strategy consulting bundled with long-term software engineering delivery | Strong | Strong | Both equally |
| Media or travel companies needing broad-based data and AI/ML capability | Strong | Limited | DataArt |
| Enterprises needing the full model lifecycle from design through MLOps and production integration | Strong | Strong | Both equally |
| Generative AI application builds requiring responsible-AI governance | Limited | Strong | Exadel |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: DataArt vs Exadel
Exadel (4.1/5) is the stronger overall choice for most Machine Learning Development projects. Explicit end-to-end scope 'from model design to MLOps and integration' as one of five named core service lines.. It is best for enterprises wanting model design through MLOps and production deployment from a firm with 25+ years of engineering history..
DataArt (3.9/5) is the better choice when enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner.. If your situation matches those criteria, DataArt is a competitive option.
Related comparisons
DataArt vs Exadel FAQ
Is DataArt better than Exadel?
Exadel (4.1/5) scores higher overall, but "better" depends on your use case. DataArt is better for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner.. Exadel is better for enterprises wanting model design through MLOps and production deployment from a firm with 25+ years of engineering history..
How do DataArt and Exadel differ in pricing?
DataArt uses fixed project, dedicated team, staff augmentation pricing with a minimum engagement of Not published. Exadel uses fixed project and managed services pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: DataArt or Exadel?
DataArt 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 DataArt and Exadel?
DataArt's primary differentiator is: 28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated ai strategy consulting service line.. Exadel's primary differentiator is: explicit end-to-end scope 'from model design to mlops and integration' as one of five named core service lines.. They also differ in team size (5,001–10,000 vs 1,001–5,000), minimum engagement (Not published vs Not published), and primary industries served (Financial Services, Media & Entertainment vs Technology/SaaS, Financial Services).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.