BairesDev vs DataArt: full comparison for 2026
Quick verdict
BairesDev (4.3/5) edges ahead of DataArt (4.0/5) overall. BairesDev is the better choice for U.S. companies needing several AI engineers on matching hours. DataArt is the stronger option for finance and healthcare firms extending data and AI teams. The right choice depends on your project size, budget, and required tech stack.
BairesDev vs DataArt: head-to-head summary
| Criterion | BairesDev | DataArt |
|---|---|---|
| Founded | 2009 | 1997 |
| HQ | San Francisco, California, USA | New York, New York, USA |
| Team size | 4,000+ | 5,000+ |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Primary differentiator | A large salaried Latin American bench that works U.S. time zones | Nearly three decades of domain work in finance, healthcare and travel |
| Pricing model | Monthly per-engineer rates for staff augmentation; dedicated teams; project pricing; rates on request | Time and materials; dedicated teams; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, Spark, Databricks |
| Industries served | Software & SaaS, Financial services, Healthcare & life sciences, Media, Retail & e-commerce | Financial services, Healthcare & life sciences, Travel, Media |
BairesDev vs DataArt: overview
BairesDev
BairesDev was founded in Buenos Aires in 2009 and now lists its headquarters in San Francisco. The company says it employs more than 4,000 professionals working remotely from over 50 countries, most of them in Latin America. It offers staff augmentation, dedicated teams and full software outsourcing, with an AI and data science practice inside the wider engineering group. BairesDev hires engineers onto its own payroll, so clients deal with one vendor contract rather than individual freelancers.
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.
Services and capabilities: BairesDev vs DataArt
| Capability | BairesDev | DataArt |
|---|---|---|
| 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: BairesDev vs DataArt
| Framework / platform | BairesDev | DataArt |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | ✓ |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Databricks | ✓ | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: BairesDev vs DataArt
| Criterion | BairesDev | DataArt |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers, Dedicated team, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: BairesDev vs DataArt
| Dimension | BairesDev | DataArt |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Software & SaaS, Financial services, Healthcare & life sciences | Financial services, Healthcare & life sciences, Travel |
| Best use cases | Adding three ML engineers to a U.S. product team on Eastern time, Staffing data engineering and model serving together for a new AI feature | Extending a trading firm's data team with ML engineers, Building a clinical data platform before adding models |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
BairesDev vs DataArt: pros and cons
| BairesDev | |
|---|---|
| + | Full working-day overlap with U.S. teams makes pairing and live reviews easy |
| + | Can fill AI, data and the surrounding web roles from one contract |
| + | Engineers are salaried employees, so replacement is the vendor's problem |
| - | AI is one practice among many, so screening depth for ML research roles varies |
| - | Pricing is quoted per engagement and is reported to sit above smaller nearshore rivals |
| - | Heavy marketing makes it hard to separate its AI claims from its general engineering pitch |
| 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 |
Who should choose BairesDev?
A typical fit: adding three ML engineers to a U.S. product team on Eastern time.
A large salaried Latin American bench that works U.S. time zones. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Financial services, Healthcare & life sciences, Media, Retail & e-commerce.
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.
Decision matrix: BairesDev vs DataArt
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; BairesDev rates higher overall |
| You want the supplier to own delivery as well as staffing | Both; BairesDev rates higher overall |
| 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: BairesDev (Not published) vs DataArt (Not published) |
| You need overlap with U.S. working hours | BairesDev |
| You need specialist depth in a specific vertical | BairesDev |
Use case fit: BairesDev vs DataArt
| Use case | BairesDev fit | DataArt fit | Winner |
|---|---|---|---|
| Adding three ML engineers to a U.S. product team on Eastern time | Strong | Strong | Both equally |
| Staffing data engineering and model serving together for a new AI feature | Strong | Limited | BairesDev |
| Extending a trading firm's data team with ML engineers | Limited | Strong | DataArt |
| Building a clinical data platform before adding models | Limited | Strong | DataArt |
Verdict: BairesDev vs DataArt
BairesDev (4.3/5) is the stronger overall choice for most AI Staff Augmentation projects. A large salaried Latin American bench that works U.S. time zones.
DataArt (4.0/5) is worth a look if you need building a clinical data platform before adding models. If your situation matches that, DataArt is a competitive option.
Related comparisons
BairesDev vs DataArt FAQ
Is BairesDev better than DataArt?
BairesDev (4.3/5) scores higher overall, but "better" depends on your use case. BairesDev's strongest advantage: full working-day overlap with U.S. teams makes pairing and live reviews easy. DataArt's strongest advantage: deep domain knowledge in regulated sectors.
How do BairesDev and DataArt differ in pricing?
BairesDev uses monthly per-engineer rates for staff augmentation; dedicated teams; project pricing; rates on request pricing. DataArt uses time and materials; dedicated teams; 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: BairesDev or DataArt?
DataArt 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 BairesDev and DataArt?
BairesDev's primary differentiator is: a large salaried Latin American bench that works U.S. time zones. DataArt's primary differentiator is: nearly three decades of domain work in finance, healthcare and travel. They also differ in team size (4,000+ vs 5,000+), minimum engagement (Not published vs Not published), and primary industries served (Software & SaaS, Financial services vs Financial services, Healthcare & life sciences).
Verify all details directly with each company before making a decision.