Best AI Development Firms

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 AI at global scale. Infosys is the stronger option for global enterprises needing 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, AWS, Azure Python, AWS, Azure
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 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.

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 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 and consulting layer on top. At this scale, AI development is one thread inside one of the world's largest IT services organizations rather than a boutique specialty.

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
PyTorch N/A N/A
TensorFlow N/A N/A
LangChain N/A N/A
AWS
Azure
Kubernetes

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 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. Running an 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 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
Infosys
+ Massive global scale (330,000-plus employees) supports the largest enterprise 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.
- 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 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.

Who should choose Infosys?

A typical fit: running an 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 AI-driven analytics platforms for finance or healthcare clients with strict compliance needs. Strong Limited DataArt
Running a long-term AI and data engineering program with a financially established vendor. Strong Strong Both equally
Running an 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 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 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 firm 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 firm before making a decision.