DataArt vs Infosys: full comparison for 2026
Quick verdict
DataArt (3.9/5) edges ahead of Infosys (3.9/5) overall. DataArt is the better choice for enterprises in finance or healthcare needing generative AI at global scale. Infosys is the stronger option for global enterprises needing generative AI inside a full IT services contract. The right choice depends on your project size, budget, and required tech stack.
DataArt vs Infosys: head-to-head summary
| Criterion | DataArt | Infosys |
|---|---|---|
| Founded | 1997 | 1981 |
| HQ | New York, United States | Bengaluru, India |
| Team size | 5,700+ | 330,000+ |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Primary differentiator | Nearly 30 years of engineering history across 30-plus global delivery locations | One of the world's largest IT services firms with a dedicated London-based consulting arm |
| Pricing model | Dedicated team or retainer | Retainer, enterprise contracting |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, OpenAI API, AWS | Python, OpenAI API, AWS |
| Industries served | Financial services, Healthcare, Media & entertainment, Travel & hospitality | Financial services, Manufacturing, Retail & e-commerce, Telecom |
DataArt vs Infosys: overview
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 generative AI platforms for finance, media and entertainment, healthcare, retail, and travel and hospitality clients. Nearly three decades of history gives it a longer track record than almost every other firm here, though generative AI is delivered as part of a broader software engineering practice rather than a standalone specialty.
Infosys
Infosys was founded in 1981 and is headquartered in Bengaluru, India, employing approximately 330,429 people worldwide as of March 2026. The company delivers a comprehensive suite of enterprise generative AI development services alongside automation, cybersecurity, and advanced data analytics, and its wholly-owned subsidiary Infosys Consulting, founded in 2004 and headquartered in London, adds a dedicated strategy layer on top. At this scale, generative AI development is one thread inside one of the world's largest IT services organizations.
Services and capabilities: DataArt vs Infosys
| Capability | DataArt | Infosys |
|---|---|---|
| Generative AI | ✓ | ✓ |
| Machine learning | ✗ | ✗ |
| AI agents | ✗ | ✗ |
| MLOps | ✓ | ✗ |
| AI consulting | ✗ | ✓ |
| Fixed-price projects | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: DataArt vs Infosys
| Framework / platform | DataArt | Infosys |
|---|---|---|
| Python | ✓ | ✓ |
| OpenAI API | ✓ | ✓ |
| PyTorch | N/A | N/A |
| LangChain | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Kubernetes | N/A | ✓ |
Pricing comparison: DataArt vs Infosys
| Criterion | DataArt | Infosys |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Dedicated team, Retainer | Retainer, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: DataArt vs Infosys
| Dimension | DataArt | Infosys |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Healthcare, Media & entertainment | Financial services, Manufacturing, Retail & e-commerce |
| Best use cases | Building generative AI-driven analytics platforms for finance or healthcare clients., Running a long-term generative AI and data engineering program with a financially established vendor. | Running a generative AI initiative as part of a much larger enterprise IT services contract., Needing a globally recognized vendor for board-level procurement approval. |
| Typical project type | Dedicated team | Retainer |
DataArt vs Infosys: pros and cons
| 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 generative AI work that needs solid data foundations. |
| - | Generative 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 |
| Infosys | |
|---|---|
| + | Massive global scale (330,000-plus employees) supports the largest enterprise generative AI programs. |
| + | Dedicated Infosys Consulting subsidiary adds a strategy layer alongside technical delivery. |
| + | Four decades of operating history and deep enterprise procurement relationships. |
| + | Broad cloud and enterprise software partnerships reduce platform risk. |
| - | Generative AI is one part of an enormous general IT services business, not a specialized focus |
| - | Scale typically means slower engagement setup than smaller, more agile firms |
Who should choose DataArt?
A typical fit: building generative AI-driven analytics platforms for finance or healthcare clients.
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.
Who should choose Infosys?
A typical fit: running a generative AI initiative as part of a much larger enterprise IT services contract.
One of the world's largest IT services firms with a dedicated London-based consulting arm. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Manufacturing, Retail & e-commerce, Telecom.
Decision matrix: DataArt vs Infosys
| 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 | DataArt |
| Your budget is at the lower end | Compare: DataArt (Not disclosed) vs Infosys (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 | Infosys |
Use case fit: DataArt vs Infosys
| Use case | DataArt fit | Infosys fit | Winner |
|---|---|---|---|
| Building generative AI-driven analytics platforms for finance or healthcare clients. | Strong | Limited | DataArt |
| Running a long-term generative AI and data engineering program with a financially established vendor. | Strong | Strong | Both equally |
| Running a generative AI initiative as part of a much larger enterprise IT services contract. | Strong | Strong | Both equally |
| Needing a globally recognized vendor for board-level procurement approval. | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: DataArt vs Infosys
DataArt (3.9/5) is the stronger overall choice for most Generative AI Development projects. Nearly 30 years of engineering history across 30-plus global delivery locations.
Infosys (3.9/5) is worth a look if you need needing a globally recognized vendor for board-level procurement approval. If your situation matches that, Infosys is a competitive option.
Related comparisons
DataArt vs Infosys FAQ
Is DataArt better than Infosys?
DataArt (3.9/5) scores higher overall, but "better" depends on your use case. DataArt's strongest advantage: nearly three decades of software engineering history, among the longest reviewed here. Infosys's strongest advantage: massive global scale (330,000-plus employees) supports the largest enterprise generative AI programs.
How do DataArt and Infosys differ in pricing?
DataArt uses dedicated team or retainer pricing. Infosys uses retainer, enterprise contracting pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: DataArt or Infosys?
Infosys is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between DataArt and Infosys?
DataArt's primary differentiator is: nearly 30 years of engineering history across 30-plus global delivery locations. Infosys's primary differentiator is: one of the world's largest IT services firms with a dedicated London-based consulting arm. They also differ in team size (5,700+ vs 330,000+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Financial services, Manufacturing).
Verify all details directly with each company before making a decision.