Fractal Analytics vs DataArt: full comparison for 2026
Last updated: July 2026
Quick verdict
Fractal Analytics (4.4/5) edges ahead of DataArt (3.9/5) overall. Fractal Analytics is the better choice for large enterprises wanting a publicly-listed, financially transparent AI/analytics partner with two-decade track record.. 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.
Fractal Analytics vs DataArt: head-to-head summary
| Criterion | Fractal Analytics | DataArt |
|---|---|---|
| Founded | 2000 | 1997 |
| HQ | Mumbai, India / New York, USA | New York, USA |
| Team size | 5,001–10,000 | 5,001–10,000 |
| Rating | 4.4 / 5 | 3.9 / 5 |
| Best for | Large enterprises wanting a publicly-listed, financially transparent AI/analytics partner with two-decade track record. | Enterprises across finance, media, healthcare, and retail wanting AI/ML from a long-established, globally distributed software engineering partner. |
| Pricing model | Fixed project and managed analytics engagements | Fixed project, dedicated team, staff augmentation |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, Azure OpenAI, AWS |
| Industries served | Retail, Financial Services, Healthcare, Technology/SaaS | Financial Services, Media & Entertainment, Healthcare, Retail, Travel & Hospitality |
Fractal Analytics vs DataArt: overview
Fractal Analytics
Fractal Analytics is a multinational AI and data analytics company founded in 2000 in Mumbai by Srikanth Velamakanni, Pranay Agrawal, Nirmal Palaparthi, Pradeep Suryanarayan, and Ramakrishna Reddy, with dual headquarters in Mumbai and New York. The company completed an initial public offering on India's National Stock Exchange and Bombay Stock Exchange in February 2026, becoming the first Indian AI company to go public, and reports roughly 5,000–6,900 employees across 18 global locations.
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: Fractal Analytics vs DataArt
| Capability | Fractal Analytics | 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: Fractal Analytics vs DataArt
| Framework / platform | Fractal Analytics | DataArt |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | 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: Fractal Analytics vs DataArt
| Criterion | Fractal Analytics | DataArt |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Fixed project, Managed services | Fixed project, Dedicated team, Staff augmentation |
| Rate transparency | Not public | Not public |
| Price tier | Enterprise / not published | Enterprise / not published |
Target audience comparison: Fractal Analytics vs DataArt
| Dimension | Fractal Analytics | DataArt |
|---|---|---|
| Best company size | Enterprise | Enterprise |
| Best industries | Retail, Financial Services, Healthcare | Financial Services, Media & Entertainment, Healthcare |
| Best use cases | Enterprise AI and analytics transformation programs at global scale, Buyers who specifically want a publicly-listed AI vendor for procurement/compliance reasons | 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 | Fixed project | Fixed project |
Fractal Analytics vs DataArt: pros and cons
| Fractal Analytics | |
|---|---|
| + | 25 years of continuous operation, among the longest track records on this list |
| + | Public listing (NSE/BSE, Feb 2026) adds a level of financial disclosure most private competitors lack |
| + | 5,000+ employees across 18 countries supports very large, globally distributed programs |
| + | Founding team has remained core to the company since 2000 |
| - | Enterprise scale and public-company overhead can mean longer sales cycles than boutique competitors |
| - | Broad analytics positioning means ML-specialist depth is one part of a wider data/AI portfolio |
| - | Minimum engagement size not publicly disclosed |
| 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 Fractal Analytics?
Fractal Analytics is the right choice for large enterprises wanting a publicly-listed, financially transparent AI/analytics partner with two-decade track record..
First Indian AI company to complete an IPO (NSE/BSE, February 2026), adding public financial transparency.. Minimum engagement starts at Not published. Works best with clients in Retail, Financial Services, Healthcare, Technology/SaaS.
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: Fractal Analytics vs DataArt
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Fractal Analytics |
| You need a large dedicated team for an ongoing programme | DataArt |
| Your budget is at the lower end | Compare: Fractal Analytics (Not published) vs DataArt (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 | Fractal Analytics |
Use case fit: Fractal Analytics vs DataArt
| Use case | Fractal Analytics fit | DataArt fit | Winner |
|---|---|---|---|
| Enterprise AI and analytics transformation programs at global scale | Strong | Strong | Both equally |
| Buyers who specifically want a publicly-listed AI vendor for procurement/compliance reasons | Strong | Limited | Fractal Analytics |
| Enterprises wanting AI strategy consulting bundled with long-term software engineering delivery | Limited | Strong | DataArt |
| 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: Fractal Analytics vs DataArt
Fractal Analytics (4.4/5) is the stronger overall choice for most Machine Learning Development projects. First Indian AI company to complete an IPO (NSE/BSE, February 2026), adding public financial transparency.. It is best for large enterprises wanting a publicly-listed, financially transparent AI/analytics partner with two-decade track record..
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
Fractal Analytics vs DataArt FAQ
Is Fractal Analytics better than DataArt?
Fractal Analytics (4.4/5) scores higher overall, but "better" depends on your use case. Fractal Analytics is better for large enterprises wanting a publicly-listed, financially transparent AI/analytics partner with two-decade track record.. 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 Fractal Analytics and DataArt differ in pricing?
Fractal Analytics uses fixed project and managed analytics engagements 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: Fractal Analytics or DataArt?
Fractal Analytics 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 Fractal Analytics and DataArt?
Fractal Analytics's primary differentiator is: first indian ai company to complete an ipo (nse/bse, february 2026), adding public financial transparency.. 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 (5,001–10,000 vs 5,001–10,000), minimum engagement (Not published vs Not published), and primary industries served (Retail, Financial Services vs Financial Services, Media & Entertainment).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.