DataArt vs Yalantis: full comparison for 2026
Last updated: July 2026
Quick verdict
DataArt (3.9/5) edges ahead of Yalantis (3.9/5) overall. DataArt is the better choice for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth. Yalantis is the stronger option for healthcare and fintech companies needing compliance-aware ML consulting paired with IoT or embedded engineering. The right choice depends on your project size, budget, and required tech stack.
DataArt vs Yalantis: head-to-head summary
| Criterion | DataArt | Yalantis |
|---|---|---|
| Founded | 1997 | 2008 |
| HQ | New York, NY | Kyiv, Ukraine |
| Team size | 5,700+ | 200–400 |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Best for | Enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth | Healthcare and fintech companies needing compliance-aware ML consulting paired with IoT or embedded engineering |
| Pricing model | T&M, dedicated team | Fixed project, T&M |
| Min. engagement | $50K+ | $25K+ |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, PyTorch |
| Industries served | fintech, healthcare, travel, media, retail | healthcare, fintech, saas, logistics, manufacturing |
DataArt vs Yalantis: 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.)
Yalantis
Yalantis was founded in 2008 and operates with a focus on compliance-first IoT and software engineering alongside machine learning consulting. The company's ML team provides domain-specific consulting, model deployment, and ongoing support, with depth in regulated industries including healthcare and fintech. ML consultants hold master's degrees in machine learning and have production data science experience. (Founded year per Tracxn; specialisation per Yalantis official website.)
Services and capabilities: DataArt vs Yalantis
| Capability | DataArt | Yalantis |
|---|---|---|
| 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 Yalantis
| Framework / platform | DataArt | Yalantis |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
Pricing comparison: DataArt vs Yalantis
| Criterion | DataArt | Yalantis |
|---|---|---|
| Minimum engagement | $50K+ | $25K+ |
| Engagement models | T&M, Dedicated team, Retainer | Fixed project, T&M, Retainer |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: DataArt vs Yalantis
| Dimension | DataArt | Yalantis |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | fintech, healthcare, travel | healthcare, fintech, saas |
| Best use cases | ML feature integration into existing fintech platform, Travel recommendation engine | Compliance-aware ML model for healthcare data, Predictive analytics for fintech risk management |
| Typical project type | T&M | Fixed project |
DataArt vs Yalantis: 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 |
| Yalantis | |
|---|---|
| + | Compliance-first approach for regulated healthcare and fintech projects |
| + | Full-lifecycle ML: from consulting through deployment and support |
| + | Master's-qualified ML consultants — verifiable technical depth |
| + | IoT integration experience alongside ML — rare combination |
| - | Ukraine-based delivery carries geographic risk considerations for some clients |
| - | Less suited to pure data science research or exploratory projects |
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 Yalantis?
Yalantis is the right choice for healthcare and fintech companies needing compliance-aware ML consulting paired with IoT or embedded engineering.
Compliance-first ML delivery — particularly strong for healthcare and regulated fintech with IoT integration needs. Minimum engagement starts at $25K+. Works best with clients in healthcare, fintech, saas, logistics, manufacturing.
Decision matrix: DataArt vs Yalantis
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Yalantis |
| You need a large dedicated team for an ongoing programme | DataArt |
| Your budget is at the lower end | Yalantis |
| 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 | DataArt |
Use case fit: DataArt vs Yalantis
| Use case | DataArt fit | Yalantis fit | Winner |
|---|---|---|---|
| ML feature integration into existing fintech platform | Strong | Strong | Both equally |
| Travel recommendation engine | Strong | Limited | DataArt |
| Compliance-aware ML model for healthcare data | Limited | Strong | Yalantis |
| Predictive analytics for fintech risk management | Limited | Strong | Yalantis |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: DataArt vs Yalantis
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.
Yalantis (3.9/5) is the better choice when healthcare and fintech companies needing compliance-aware ML consulting paired with IoT or embedded engineering. If your situation matches those criteria, Yalantis is a competitive option.
Related comparisons
DataArt vs Yalantis FAQ
Is DataArt better than Yalantis?
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. Yalantis is better for healthcare and fintech companies needing compliance-aware ML consulting paired with IoT or embedded engineering.
How do DataArt and Yalantis differ in pricing?
DataArt uses t&m, dedicated team pricing with a minimum engagement of $50K+. Yalantis uses fixed project, t&m pricing with a minimum engagement of $25K+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: DataArt or Yalantis?
Yalantis 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 Yalantis?
DataArt's primary differentiator is: 1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ml and software in fintech and travel. Yalantis's primary differentiator is: compliance-first ml delivery — particularly strong for healthcare and regulated fintech with iot integration needs. They also differ in team size (5,700+ vs 200–400), minimum engagement ($50K+ vs $25K+), and primary industries served (fintech, healthcare vs healthcare, fintech).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.