DataArt vs Revelo: full comparison for 2026
Quick verdict
DataArt (4.0/5) edges ahead of Revelo (3.8/5) overall. DataArt is the better choice for finance and healthcare firms extending data and AI teams. Revelo is the stronger option for hiring Latin American developers through a marketplace. The right choice depends on your project size, budget, and required tech stack.
DataArt vs Revelo: head-to-head summary
| Criterion | DataArt | Revelo |
|---|---|---|
| Founded | 1997 | 2014 |
| HQ | New York, New York, USA | São Paulo, Brazil |
| Team size | 5,000+ | 400,000+ developer network (per company) |
| Rating | 4.0 / 5 | 3.8 / 5 |
| Primary differentiator | Nearly three decades of domain work in finance, healthcare and travel | A very large Latin American pool with payroll and compliance included |
| Pricing model | Time and materials; dedicated teams; rates on request | Marketplace placement with monthly billing; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Spark, Databricks | Python, OpenAI, Hugging Face |
| Industries served | Financial services, Healthcare & life sciences, Travel, Media | Software & SaaS, AI research labs, Financial services |
DataArt vs Revelo: overview
DataArt
DataArt was founded in New York in 1997 by Eugene Goland, who still leads it. Reported headcount ranges from about 4,000 to more than 6,000 across 30 to 40 locations. The firm builds data, analytics and AI platforms and works heavily in finance, healthcare and travel. Clients can bring in DataArt engineers as part of their own team or contract a full delivery team.
Revelo
Revelo was founded in late 2014 in Brazil (some sources say 2015) and began as a domestic hiring platform called Contratado. It now runs a network of more than 400,000 Latin American developers and handles hiring and payment for U.S. customers. TechCrunch reported that work on foundation models made up 22% of Revelo's revenue in 2024. Revelo is a marketplace, so engineers are matched through its platform rather than employed in a delivery center.
Services and capabilities: DataArt vs Revelo
| Capability | DataArt | Revelo |
|---|---|---|
| LLM / GenAI engineers | ✗ | ✓ |
| MLOps & deployment | ✗ | ✗ |
| Computer vision | ✗ | ✗ |
| Data engineering | ✓ | ✗ |
| AI agent development | ✗ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Risk-free trial period | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✓ |
Tech stack comparison: DataArt vs Revelo
| Framework / platform | DataArt | Revelo |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | ✓ |
| OpenAI | N/A | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Databricks | ✓ | N/A |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: DataArt vs Revelo
| Criterion | DataArt | Revelo |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: DataArt vs Revelo
| Dimension | DataArt | Revelo |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Healthcare & life sciences, Travel | Software & SaaS, AI research labs, Financial services |
| Best use cases | Extending a trading firm's data team with ML engineers, Building a clinical data platform before adding models | Hiring LLM data specialists for a model-training effort, Adding a Brazilian developer to a U.S. SaaS team |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
DataArt vs Revelo: pros and cons
| DataArt | |
|---|---|
| + | Deep domain knowledge in regulated sectors |
| + | Strong data-platform engineering supports AI work |
| + | Long client relationships suggest stable delivery |
| - | AI specialists are a small share of a broad workforce |
| - | Headcount figures vary considerably between sources |
| - | Engagements often lean toward managed delivery |
| Revelo | |
|---|---|
| + | Very large pool across Latin America |
| + | Handles hiring, payroll and compliance |
| + | Foundation-model work gives some engineers LLM training experience |
| - | Marketplace matching means quality varies by candidate |
| - | Founding year is reported as both 2014 and 2015 |
| - | Less hands-on management than employer-based firms |
Who should choose DataArt?
A typical fit: extending a trading firm's data team with ML engineers.
Nearly three decades of domain work in finance, healthcare and travel. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare & life sciences, Travel, Media.
Who should choose Revelo?
A typical fit: hiring LLM data specialists for a model-training effort.
A very large Latin American pool with payroll and compliance included. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, AI research labs, Financial services.
Decision matrix: DataArt vs Revelo
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | DataArt |
| You want the supplier to own delivery as well as staffing | DataArt |
| You need one expert part-time | Neither lists part-time experts; ask about reduced hours |
| You want to test an engineer before signing for months | Neither publishes a trial; ask for a short first term |
| Your budget is at the lower end | Compare: DataArt (Not published) vs Revelo (Not published) |
| You need overlap with U.S. working hours | Revelo |
| You need specialist depth in a specific vertical | DataArt |
Use case fit: DataArt vs Revelo
| Use case | DataArt fit | Revelo fit | Winner |
|---|---|---|---|
| Extending a trading firm's data team with ML engineers | Strong | Limited | DataArt |
| Building a clinical data platform before adding models | Strong | Limited | DataArt |
| Hiring LLM data specialists for a model-training effort | Limited | Strong | Revelo |
| Adding a Brazilian developer to a U.S. SaaS team | Strong | Strong | Both equally |
Verdict: DataArt vs Revelo
DataArt (4.0/5) is the stronger overall choice for most AI Staff Augmentation projects. Nearly three decades of domain work in finance, healthcare and travel.
Revelo (3.8/5) is worth a look if you need adding a Brazilian developer to a U.S. SaaS team. If your situation matches that, Revelo is a competitive option.
Related comparisons
DataArt vs Revelo FAQ
Is DataArt better than Revelo?
DataArt (4.0/5) scores higher overall, but "better" depends on your use case. DataArt's strongest advantage: deep domain knowledge in regulated sectors. Revelo's strongest advantage: very large pool across Latin America.
How do DataArt and Revelo differ in pricing?
DataArt uses time and materials; dedicated teams; rates on request pricing. Revelo uses marketplace placement with monthly billing; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: DataArt or Revelo?
Revelo 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 Revelo?
DataArt's primary differentiator is: nearly three decades of domain work in finance, healthcare and travel. Revelo's primary differentiator is: a very large Latin American pool with payroll and compliance included. They also differ in team size (5,000+ vs 400,000+ developer network (per company)), minimum engagement (Not published vs Not published), and primary industries served (Financial services, Healthcare & life sciences vs Software & SaaS, AI research labs).
Verify all details directly with each company before making a decision.