Persistent Systems vs DataArt: full comparison for 2026
Last updated: July 2026
Quick verdict
DataArt (3.9/5) edges ahead of Persistent Systems (3.8/5) overall. DataArt is the better choice for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner.. Persistent Systems is the stronger option for very large enterprises that want AI/ML delivered by the same vendor already running their broader IT estate.. The right choice depends on your project size, budget, and required tech stack.
Persistent Systems vs DataArt: head-to-head summary
| Criterion | Persistent Systems | DataArt |
|---|---|---|
| Founded | 1990 | 1997 |
| HQ | Pune, India | New York, USA |
| Team size | 10,000+ | 5,001–10,000 |
| Rating | 3.8 / 5 | 3.9 / 5 |
| Best for | Very large enterprises that want AI/ML delivered by the same vendor already running their broader IT estate. | Enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner. |
| Pricing model | Managed services and fixed project | Fixed project, dedicated team, staff augmentation |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Azure OpenAI, AWS | Python, Azure OpenAI, AWS |
| Industries served | Financial Services, Healthcare, Technology/SaaS, Government | Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality |
Persistent Systems vs DataArt: overview
Persistent Systems
Persistent Systems is an Indian multinational technology company founded in 1990 by Anand Deshpande, headquartered in Pune, with roughly 24,600 employees as of March 2025. Its AI/ML offerings, including the Persistent GenAI Hub, sit within a much larger portfolio spanning enterprise software, cloud, and digital engineering services rather than being the company's core specialization.
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.
Services and capabilities: Persistent Systems vs DataArt
| Capability | Persistent Systems | DataArt |
|---|---|---|
| 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: Persistent Systems vs DataArt
| Framework / platform | Persistent Systems | DataArt |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | N/A | N/A |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| Databricks | N/A | ✓ |
| LangChain | N/A | N/A |
Pricing comparison: Persistent Systems vs DataArt
| Criterion | Persistent Systems | DataArt |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Managed services, Fixed project, Staff augmentation | Fixed project, Dedicated team, Staff augmentation |
| Rate transparency | Not public | Not public |
| Price tier | Enterprise / not published | Enterprise / not published |
Target audience comparison: Persistent Systems vs DataArt
| Dimension | Persistent Systems | DataArt |
|---|---|---|
| Best company size | Enterprise | Enterprise |
| Best industries | Financial Services, Healthcare, Technology/SaaS | Financial Services, Media & Entertainment, Healthcare |
| Best use cases | Enterprises already using Persistent for core IT services wanting to add AI/ML from the same vendor, Very large, multi-year digital transformation programs where AI is one workstream among many | Enterprises wanting AI strategy consulting bundled with long-term software engineering delivery, Media or travel companies needing broad-based data and AI/ML capability |
| Typical project type | Managed services | Fixed project |
Persistent Systems vs DataArt: pros and cons
| Persistent Systems | |
|---|---|
| + | 35 years of operating history and one of the largest headcounts on this list (24,000+) |
| + | AI capability delivered alongside a company's existing broader IT services relationship, reducing vendor sprawl |
| + | 16,000+ AI-trained staff cited internally, suggesting significant AI upskilling investment (per company website) |
| + | Public-company scale supports very large, multi-year enterprise transformation programs |
| - | AI/ML is one offering within a much larger, more generalist IT services portfolio rather than the firm's core focus |
| - | Buyers seeking cutting-edge ML specialization may find deeper expertise at AI-first boutiques on this list |
| - | Very large organization can mean slower response times and more layered account management than smaller firms |
| 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 |
Who should choose Persistent Systems?
Persistent Systems is the right choice for very large enterprises that want AI/ML delivered by the same vendor already running their broader IT estate..
Enterprise-wide scale (24,000+ employees) supporting AI/ML as part of a full IT services portfolio, not a standalone specialty.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Healthcare, Technology/SaaS, Government.
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.
Decision matrix: Persistent Systems vs DataArt
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Persistent Systems |
| You need a large dedicated team for an ongoing programme | DataArt |
| Your budget is at the lower end | Compare: Persistent Systems (Not published) vs DataArt (Not published) |
| You need specialist depth in a specific vertical | DataArt |
| You need staff augmentation or team extension | Persistent Systems |
| You need consulting before committing to a build | Persistent Systems |
Use case fit: Persistent Systems vs DataArt
| Use case | Persistent Systems fit | DataArt fit | Winner |
|---|---|---|---|
| Enterprises already using Persistent for core IT services wanting to add AI/ML from the same vendor | Strong | Strong | Both equally |
| Very large, multi-year digital transformation programs where AI is one workstream among many | Strong | Strong | Both equally |
| 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 | Limited | Strong | DataArt |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Persistent Systems vs DataArt
DataArt (3.9/5) is the stronger overall choice for most Machine Learning Development projects. 28 years of operating history across 30+ global delivery locations, with a newer (2024) dedicated AI strategy consulting service line.. It is best for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner..
Persistent Systems (3.8/5) is the better choice when very large enterprises that want AI/ML delivered by the same vendor already running their broader IT estate.. If your situation matches those criteria, Persistent Systems is a competitive option.
Related comparisons
Persistent Systems vs DataArt FAQ
Is Persistent Systems better than DataArt?
DataArt (3.9/5) scores higher overall, but "better" depends on your use case. Persistent Systems is better for very large enterprises that want AI/ML delivered by the same vendor already running their broader IT estate.. DataArt is better for enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner..
How do Persistent Systems and DataArt differ in pricing?
Persistent Systems uses managed services and fixed project pricing with a minimum engagement of Not published. DataArt uses fixed project, dedicated team, staff augmentation 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: Persistent Systems or DataArt?
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 Persistent Systems and DataArt?
Persistent Systems's primary differentiator is: enterprise-wide scale (24,000+ employees) supporting ai/ml as part of a full it services portfolio, not a standalone specialty.. 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.. They also differ in team size (10,000+ vs 5,001–10,000), minimum engagement (Not published vs Not published), and primary industries served (Financial Services, Healthcare vs Financial Services, Media & Entertainment).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.