DataArt vs Turing: full comparison for 2026
Last updated: July 2026
Quick verdict
DataArt (3.9/5) edges ahead of Turing (3.8/5) overall. DataArt is the better choice for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth. Turing is the stronger option for companies needing rapid access to vetted ML engineers or data scientists for staff augmentation or team extension. The right choice depends on your project size, budget, and required tech stack.
DataArt vs Turing: head-to-head summary
| Criterion | DataArt | Turing |
|---|---|---|
| Founded | 1997 | 2018 |
| HQ | New York, NY | Palo Alto, CA |
| Team size | 5,700+ | 6,859 |
| Rating | 3.9 / 5 | 3.8 / 5 |
| Best for | Enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth | Companies needing rapid access to vetted ML engineers or data scientists for staff augmentation or team extension |
| Pricing model | T&M, dedicated team | Dedicated team, T&M |
| Min. engagement | $50K+ | Not disclosed |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, PyTorch |
| Industries served | fintech, healthcare, travel, media, retail | saas, fintech, healthcare, retail, financial |
DataArt vs Turing: overview
DataArt
DataArt was founded in 1997 by Eugene Goland and is headquartered in New York, with offices across 15 global locations and 5,700+ employees. The company delivers AI and ML services — predictive analytics, NLP, data mining, and computer vision — alongside broader software engineering for clients in fintech, healthcare, and travel. DataArt was named an Inc. 5000 honoree in 2024. ML is one service line among many in DataArt's broad software engineering portfolio. (Employee count and founding year per DataArt Wikipedia and official website.)
Turing
Turing was founded in 2018 by Jonathan Siddharth and Rohan Aroe and is headquartered in Palo Alto, California. The company operates as an AI-powered talent marketplace and technology services firm with a network of 4M+ vetted software engineers, data scientists, and STEM experts. Turing has raised $247M at a $2.2B valuation from WestBridge Capital and Foundation Capital, and serves 1,000+ clients including Fortune 500 companies and governments. Note: Turing is primarily a talent marketplace — clients provide direction; Turing supplies vetted engineers rather than owning ML delivery outcomes. (Funding, valuation, and client count per Turing official website and Crunchbase.)
Services and capabilities: DataArt vs Turing
| Capability | DataArt | Turing |
|---|---|---|
| Custom ML build | ✓ | ✓ |
| ML consulting | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP / LLM | ✓ | ✗ |
| Predictive analytics | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| Data engineering | ✓ | ✗ |
| Generative AI | ✗ | ✗ |
| Staff augmentation | ✗ | ✓ |
| Fixed-price projects | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: DataArt vs Turing
| Framework / platform | DataArt | Turing |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
Pricing comparison: DataArt vs Turing
| Criterion | DataArt | Turing |
|---|---|---|
| Minimum engagement | $50K+ | Not disclosed |
| Engagement models | T&M, Dedicated team, Retainer | T&M, Dedicated team |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Mid-market |
Target audience comparison: DataArt vs Turing
| Dimension | DataArt | Turing |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | fintech, healthcare, travel | saas, fintech, healthcare |
| Best use cases | ML feature integration into existing fintech platform, Travel recommendation engine | Staff augmentation for ML engineering team, Rapid placement of vetted data scientists |
| Typical project type | T&M | T&M |
DataArt vs Turing: pros and cons
| DataArt | |
|---|---|
| + | 5,700+ engineers — sufficient capacity for large parallel programmes |
| + | 29 years of software delivery history — low company risk |
| + | Strong fintech and travel sector domain depth |
| + | Inc. 5000 2024 — verified revenue growth |
| + | 15 global offices for enterprise procurement alignment |
| - | ML is one practice among many — not a pure ML specialist |
| - | Minimum engagement and overhead suited to enterprise, not startups |
| - | Large firm processes can reduce speed relative to boutique ML agencies |
| Turing | |
|---|---|
| + | 4M+ AI-vetted engineers — largest pre-screened ML talent pool in the category |
| + | $2.2B valuation with $247M raised — stable platform with institutional backing |
| + | 1,000+ clients including Fortune 500 and government organisations |
| + | Fastest path to pre-screened ML engineer placement |
| - | Talent marketplace model — Turing supplies engineers; client provides direction and owns outcomes |
| - | Less suited to projects needing a delivery firm with end-to-end accountability |
| - | Delivery quality depends on client PM capability — not owned by Turing |
Who should choose DataArt?
DataArt is the right choice for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth.
1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ML and software in fintech and travel. Minimum engagement starts at $50K+. Works best with clients in fintech, healthcare, travel, media, retail.
Who should choose Turing?
Turing is the right choice for companies needing rapid access to vetted ML engineers or data scientists for staff augmentation or team extension.
AI-vetted 4M+ developer network — fastest route to pre-screened ML talent for staff augmentation. Minimum engagement starts at Not disclosed. Works best with clients in saas, fintech, healthcare, retail, financial.
Decision matrix: DataArt vs Turing
| 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 ($50K+) vs Turing (Not disclosed) |
| You need specialist depth in a specific vertical | DataArt |
| You need staff augmentation or team extension | Turing |
| You need consulting before committing to a build | DataArt |
Use case fit: DataArt vs Turing
| Use case | DataArt fit | Turing fit | Winner |
|---|---|---|---|
| ML feature integration into existing fintech platform | Strong | Strong | Both equally |
| Travel recommendation engine | Strong | Limited | DataArt |
| Staff augmentation for ML engineering team | Limited | Strong | Turing |
| Rapid placement of vetted data scientists | Limited | Strong | Turing |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Strong | Turing |
Verdict: DataArt vs Turing
DataArt (3.9/5) is the stronger overall choice for most Machine Learning projects. 1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ML and software in fintech and travel. It is best for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth.
Turing (3.8/5) is the better choice when companies needing rapid access to vetted ML engineers or data scientists for staff augmentation or team extension. If your situation matches those criteria, Turing is a competitive option.
Related comparisons
DataArt vs Turing FAQ
Is DataArt better than Turing?
DataArt (3.9/5) scores higher overall, but "better" depends on your use case. DataArt is better for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth. Turing is better for companies needing rapid access to vetted ML engineers or data scientists for staff augmentation or team extension.
How do DataArt and Turing differ in pricing?
DataArt uses t&m, dedicated team pricing with a minimum engagement of $50K+. Turing uses dedicated team, t&m pricing with a minimum engagement of Not disclosed. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: DataArt or Turing?
Turing 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 Turing?
DataArt's primary differentiator is: 1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ml and software in fintech and travel. Turing's primary differentiator is: ai-vetted 4m+ developer network — fastest route to pre-screened ml talent for staff augmentation. They also differ in team size (5,700+ vs 6,859), minimum engagement ($50K+ vs Not disclosed), and primary industries served (fintech, healthcare vs saas, fintech).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.