BairesDev vs DataArt: full comparison for 2026
Quick verdict
BairesDev (4.5/5) edges ahead of DataArt (4.0/5) overall. BairesDev is the better choice for U.S. companies needing several engineers in American time zones. DataArt is the stronger option for financial and travel firms needing long-lived dedicated 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, USA (delivery across Latin America) | New York, USA |
| Team size | 1,001–5,000 | 5,000–6,000 |
| Rating | 4.5 / 5 | 4.0 / 5 |
| Primary differentiator | Largest employed LatAm engineering bench on this list | Dedicated development centers with nearly 30 years of history |
| Pricing model | Monthly per engineer; dedicated teams; rates on request | Dedicated development center; time and materials; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, Azure ML, AWS |
| Industries served | Fintech, Healthcare, SaaS, E-commerce, Media | Fintech, Travel, Healthcare, Media |
BairesDev vs DataArt: overview
BairesDev
BairesDev was founded in 2009 in Buenos Aires and lists its headquarters in San Francisco. It employs its own engineers across Latin America, with more than 4,000 on staff according to the company; LinkedIn places it in the 1,001–5,000 employee band. Its staff-augmentation service typically stands up teams in about two weeks, and a separate AI-augmented engineer option targets teams in two to four weeks (per company website; independently unverifiable). Engineers work U.S.-aligned hours, which is the main reason hiring managers in North America choose it over Eastern European firms.
DataArt
DataArt was founded in New York in 1997 by Eugene Goland and now employs between 5,000 and 6,000 people across more than 40 locations. Its Dedicated Development Center model staffs a team that works on one client's project only. An AI/ML group is actively hiring, with recent roles including a lead AI/ML engineer for an HR copilot built for a French SaaS client.
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 | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | ✓ |
| AWS SageMaker | ✓ | N/A |
| Azure ML | ✓ | ✓ |
| Databricks | ✓ | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | ✓ |
Pricing comparison: BairesDev vs DataArt
| Criterion | BairesDev | DataArt |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | 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 | Fintech, Healthcare, SaaS | Fintech, Travel, Healthcare |
| Best use cases | Building a mixed team of ML, data and backend engineers on U.S. hours, Scaling an existing AI product team by several seats within a month | Setting up a long-term dedicated team that includes ML engineers, Adding an LLM engineer to a SaaS copilot project |
| Typical project type | Full-time dedicated engineers | Dedicated team |
BairesDev vs DataArt: pros and cons
| BairesDev | |
|---|---|
| + | Can fill five or ten seats at once, which most AI specialists on this list cannot |
| + | Engineers are BairesDev employees, so contracts and payroll stay off your books |
| + | Full working-day overlap for U.S. teams |
| + | Covers data engineering and DevOps around the ML work |
| - | AI is one practice among many; depth varies by individual engineer |
| - | Heavy marketing presence can overstate how specialized any given placement will be |
| - | Rates are not published |
| DataArt | |
|---|---|
| + | Long-running dedicated teams with low churn |
| + | Strong presence in finance and travel |
| + | Wide location choice |
| - | Built for multi-year centers more than quick single hires |
| - | AI/ML group is still growing |
| - | Enterprise pricing |
Who should choose BairesDev?
A typical fit: building a mixed team of ML, data and backend engineers on U.S. hours.
Largest employed LatAm engineering bench on this list. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, Healthcare, SaaS, E-commerce, Media.
Who should choose DataArt?
A typical fit: setting up a long-term dedicated team that includes ML engineers.
Dedicated development centers with nearly 30 years of history. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, Travel, Healthcare, Media.
Decision matrix: BairesDev vs DataArt
| 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 | BairesDev |
| Your budget is at the lower end | Compare: BairesDev (Not disclosed) vs DataArt (Not disclosed) |
| You need specialist depth in a specific vertical | BairesDev |
| 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: BairesDev vs DataArt
| Use case | BairesDev fit | DataArt fit | Winner |
|---|---|---|---|
| Building a mixed team of ML, data and backend engineers on U.S. hours | Strong | Limited | BairesDev |
| Scaling an existing AI product team by several seats within a month | Strong | Limited | BairesDev |
| Setting up a long-term dedicated team that includes ML engineers | Limited | Strong | DataArt |
| Adding an LLM engineer to a SaaS copilot project | Strong | Strong | Both equally |
Verdict: BairesDev vs DataArt
BairesDev (4.5/5) is the stronger overall choice for most AI Staffing projects. Largest employed LatAm engineering bench on this list.
DataArt (4.0/5) is worth a look if you need adding an LLM engineer to a SaaS copilot project. If your situation matches that, DataArt is a competitive option.
Related comparisons
BairesDev vs DataArt FAQ
Is BairesDev better than DataArt?
BairesDev (4.5/5) scores higher overall, but "better" depends on your use case. BairesDev's strongest advantage: can fill five or ten seats at once, which most AI specialists on this list cannot. DataArt's strongest advantage: long-running dedicated teams with low churn.
How do BairesDev and DataArt differ in pricing?
BairesDev uses monthly per engineer; dedicated teams; rates on request pricing. DataArt uses dedicated development center; time and materials; 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 agency before shortlisting.
What are the main differences between BairesDev and DataArt?
BairesDev's primary differentiator is: largest employed LatAm engineering bench on this list. DataArt's primary differentiator is: dedicated development centers with nearly 30 years of history. They also differ in team size (1,001–5,000 vs 5,000–6,000), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Fintech, Healthcare vs Fintech, Travel).
Verify all details directly with each agency before making a decision.