DataArt vs Codiant: full comparison for 2026
Last updated: July 2026
Quick verdict
DataArt (3.6/5) edges ahead of Codiant (3.6/5) overall. DataArt is the better choice for mid-market and enterprise companies in finance, healthcare, or media needing a large engineering firm with ML integrated into product delivery. Codiant is the stronger option for startups and mid-market companies on five continents needing ML development integrated with web and mobile product builds at accessible cost. The right choice depends on your project size, budget, and required tech stack.
DataArt vs Codiant: head-to-head summary
| Criterion | DataArt | Codiant |
|---|---|---|
| Founded | 1997 | 2011 |
| HQ | New York, NY, USA | Illinois, USA / India |
| Team size | 6,000+ | 200–300 |
| Rating | 3.6 / 5 | 3.6 / 5 |
| Best for | Mid-market and enterprise companies in finance, healthcare, or media needing a large engineering firm with ML integrated into product delivery | Startups and mid-market companies on five continents needing ML development integrated with web and mobile product builds at accessible cost |
| Pricing model | T&M, dedicated team | Fixed project, dedicated team, T&M |
| Min. engagement | $50K | $15K |
| Primary tech stack | Python, Scikit-learn, TensorFlow | Python, TensorFlow, PyTorch |
| Industries served | Fintech, Healthcare, SaaS, Logistics, E-commerce | Healthcare, Fintech, E-commerce, SaaS, Logistics |
DataArt vs Codiant: overview
DataArt
DataArt is a global engineering firm founded in 1997 and headquartered in New York, New York, with 6,000+ specialists across 20+ countries. The firm's AI and ML services deliver solutions in predictive analytics, natural language processing, data mining, and computer vision, integrated within product engineering and digital transformation delivery. DataArt serves financial services, healthcare, media, travel, and technology clients. The firm operates with a flat structure emphasising direct engineer-to-client interaction over multi-layer account management.
Codiant
Codiant is a software development company headquartered in Illinois, USA with a development centre in India and offices in the UK, Australia, and UAE, employing 240+ full-time professionals. The company is a subsidiary of Yash Technologies and delivers custom AI and ML solutions alongside web and mobile development for startups and enterprises across five continents. Codiant holds ISO 9001 and ISO/IEC 27001:2013 certifications and has completed 700+ projects for 200+ active clients. The ML practice covers data engineering, model development, and integration into web and mobile platforms.
Services and capabilities: DataArt vs Codiant
| Capability | DataArt | Codiant |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP & text analytics | ✓ | ✓ |
| MLOps & deployment | ✗ | ✗ |
| Generative AI | ✗ | ✓ |
| ML consulting & strategy | ✗ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: DataArt vs Codiant
| Framework / platform | DataArt | Codiant |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| Scikit-learn | ✓ | ✓ |
| AWS SageMaker | N/A | N/A |
| MLflow | N/A | N/A |
| Hugging Face | N/A | N/A |
| LangChain | N/A | N/A |
| Docker/Kubernetes | N/A | N/A |
| Databricks | N/A | N/A |
Pricing comparison: DataArt vs Codiant
| Criterion | DataArt | Codiant |
|---|---|---|
| Minimum engagement | $50K | $15K |
| Engagement models | Time & materials, Dedicated team | Fixed project, Dedicated team, Time & materials |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: DataArt vs Codiant
| Dimension | DataArt | Codiant |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Fintech, Healthcare, SaaS | Healthcare, Fintech, E-commerce |
| Best use cases | NLP-powered document analysis for financial services compliance and reporting, Predictive analytics for healthcare patient risk stratification and monitoring | ML features integrated into mobile and web application product builds, Predictive analytics for e-commerce product recommendation and personalisation |
| Typical project type | Time & materials | Fixed project |
DataArt vs Codiant: pros and cons
| DataArt | |
|---|---|
| + | 29-year engineering track record across financial services, healthcare, and media |
| + | 6,000+ specialists provide large programme delivery capacity across 20+ countries |
| + | Flat organisational structure provides direct senior ML engineer access on projects |
| + | Multi-country delivery network for global client timezone and language coverage |
| + | Strong NLP and predictive analytics capability within product engineering context |
| - | ML sits within a broad engineering firm — not a specialist ML company |
| - | T&M and dedicated team models less suited to clients seeking fixed-price delivery |
| - | Less emphasis on cutting-edge generative AI research than newer AI-first firms |
| Codiant | |
|---|---|
| + | ISO 9001 and 27001 certifications for quality and security process assurance |
| + | Yash Technologies parent provides financial stability and enterprise credibility |
| + | 240+ professionals with multi-continent delivery capability across 5 geographies |
| + | $15K minimum engagement is accessible for startup and small company budgets |
| + | 700+ completed projects provides delivery track record across multiple industries |
| - | AI/ML is one of multiple service lines at a broadly-positioned development company |
| - | Yash Technologies acquisition means company culture may differ from independent AI-first firms |
| - | Smaller team limits capacity for very large or complex enterprise ML programmes |
Who should choose DataArt?
DataArt is the right choice for mid-market and enterprise companies in finance, healthcare, or media needing a large engineering firm with ML integrated into product delivery.
29-year global engineering firm with 6,000+ specialists and a flat structure providing direct access to senior ML engineers on client projects. Minimum engagement starts at $50K. Works best with clients in Fintech, Healthcare, SaaS, Logistics, E-commerce.
Who should choose Codiant?
Codiant is the right choice for startups and mid-market companies on five continents needing ML development integrated with web and mobile product builds at accessible cost.
Yash Technologies subsidiary with ISO 9001 and 27001 certifications, multi-continent delivery, and 700+ completed projects for 200+ active clients. Minimum engagement starts at $15K. Works best with clients in Healthcare, Fintech, E-commerce, SaaS, Logistics.
Decision matrix: DataArt vs Codiant
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Codiant |
| You need a large dedicated team for an ongoing programme | DataArt |
| Your budget is at the lower end | Codiant |
| 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 | Both may offer discovery engagements |
Use case fit: DataArt vs Codiant
| Use case | DataArt fit | Codiant fit | Winner |
|---|---|---|---|
| NLP-powered document analysis for financial services compliance and reporting | Strong | Limited | DataArt |
| Predictive analytics for healthcare patient risk stratification and monitoring | Strong | Strong | Both equally |
| ML features integrated into mobile and web application product builds | Strong | Strong | Both equally |
| Predictive analytics for e-commerce product recommendation and personalisation | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: DataArt vs Codiant
DataArt (3.6/5) is the stronger overall choice for most Machine Learning Development projects. 29-year global engineering firm with 6,000+ specialists and a flat structure providing direct access to senior ML engineers on client projects. It is best for mid-market and enterprise companies in finance, healthcare, or media needing a large engineering firm with ML integrated into product delivery.
Codiant (3.6/5) is the better choice when startups and mid-market companies on five continents needing ML development integrated with web and mobile product builds at accessible cost. If your situation matches those criteria, Codiant is a competitive option.
Related comparisons
DataArt vs Codiant FAQ
Is DataArt better than Codiant?
DataArt (3.6/5) scores higher overall, but "better" depends on your use case. DataArt is better for mid-market and enterprise companies in finance, healthcare, or media needing a large engineering firm with ML integrated into product delivery. Codiant is better for startups and mid-market companies on five continents needing ML development integrated with web and mobile product builds at accessible cost.
How do DataArt and Codiant differ in pricing?
DataArt uses t&m, dedicated team pricing with a minimum engagement of $50K. Codiant uses fixed project, dedicated team, t&m pricing with a minimum engagement of $15K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: DataArt or Codiant?
Codiant is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between DataArt and Codiant?
DataArt's primary differentiator is: 29-year global engineering firm with 6,000+ specialists and a flat structure providing direct access to senior ml engineers on client projects. Codiant's primary differentiator is: yash technologies subsidiary with iso 9001 and 27001 certifications, multi-continent delivery, and 700+ completed projects for 200+ active clients. They also differ in team size (6,000+ vs 200–300), minimum engagement ($50K vs $15K), and primary industries served (Fintech, Healthcare vs Healthcare, Fintech).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.