DataArt vs Modak: full comparison for 2026
Last updated: July 2026
Quick verdict
DataArt (3.9/5) edges ahead of Modak (3.7/5) overall. DataArt is the better choice for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth. Modak is the stronger option for large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption. The right choice depends on your project size, budget, and required tech stack.
DataArt vs Modak: head-to-head summary
| Criterion | DataArt | Modak |
|---|---|---|
| Founded | 1997 | 2016 |
| HQ | New York, NY | San Jose, CA |
| Team size | 5,700+ | 100–200 |
| Rating | 3.9 / 5 | 3.7 / 5 |
| Best for | Enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth | Large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption |
| Pricing model | T&M, dedicated team | T&M, retainer |
| Min. engagement | $50K+ | $50K+ |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, Apache Spark, Databricks |
| Industries served | fintech, healthcare, travel, media, retail | financial, healthcare, manufacturing, logistics, saas |
DataArt vs Modak: 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.)
Modak
Modak is an AI-native data engineering company headquartered in San Jose, California, founded in 2016. The company uses machine learning techniques to transform how structured and unstructured enterprise data is prepared, consumed, and shared — focusing on AI-driven data modernisation for large organisations. Global consulting services help enterprises modernise data infrastructure, accelerate AI readiness, and drive measurable business outcomes. (Founding year and approach per Modak official website and ZoomInfo.)
Services and capabilities: DataArt vs Modak
| Capability | DataArt | Modak |
|---|---|---|
| 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 Modak
| Framework / platform | DataArt | Modak |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
Pricing comparison: DataArt vs Modak
| Criterion | DataArt | Modak |
|---|---|---|
| Minimum engagement | $50K+ | $50K+ |
| Engagement models | T&M, Dedicated team, Retainer | T&M, Retainer |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: DataArt vs Modak
| Dimension | DataArt | Modak |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | fintech, healthcare, travel | financial, healthcare, manufacturing |
| Best use cases | ML feature integration into existing fintech platform, Travel recommendation engine | Enterprise data modernisation for AI readiness, ML-powered ETL and data prep pipeline |
| Typical project type | T&M | T&M |
DataArt vs Modak: 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 |
| Modak | |
|---|---|
| + | ML applied to data engineering itself — accelerates data prep for ML programmes |
| + | AI-native from inception — not a repositioned data warehouse firm |
| + | Strong on unstructured data processing for AI readiness |
| + | San Jose HQ with enterprise client focus |
| - | Data engineering focus — not suited to custom ML model development or computer vision |
| - | Minimum engagement oriented toward large enterprise programmes |
| - | Less suited to companies without an existing large data estate |
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 Modak?
Modak is the right choice for large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption.
ML-powered data engineering — uses ML itself to accelerate data prep and modernisation at enterprise scale. Minimum engagement starts at $50K+. Works best with clients in financial, healthcare, manufacturing, logistics, saas.
Decision matrix: DataArt vs Modak
| 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 | DataArt |
| 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 Modak
| Use case | DataArt fit | Modak fit | Winner |
|---|---|---|---|
| ML feature integration into existing fintech platform | Strong | Strong | Both equally |
| Travel recommendation engine | Strong | Limited | DataArt |
| Enterprise data modernisation for AI readiness | Strong | Strong | Both equally |
| ML-powered ETL and data prep pipeline | Limited | Strong | Modak |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: DataArt vs Modak
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.
Modak (3.7/5) is the better choice when large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption. If your situation matches those criteria, Modak is a competitive option.
Related comparisons
DataArt vs Modak FAQ
Is DataArt better than Modak?
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. Modak is better for large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption.
How do DataArt and Modak differ in pricing?
DataArt uses t&m, dedicated team pricing with a minimum engagement of $50K+. Modak uses t&m, retainer pricing with a minimum engagement of $50K+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: DataArt or Modak?
Modak 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 Modak?
DataArt's primary differentiator is: 1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ml and software in fintech and travel. Modak's primary differentiator is: ml-powered data engineering — uses ml itself to accelerate data prep and modernisation at enterprise scale. They also differ in team size (5,700+ vs 100–200), minimum engagement ($50K+ vs $50K+), and primary industries served (fintech, healthcare vs financial, healthcare).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.