X-Team vs DataArt: full comparison for 2026
Quick verdict
X-Team (4.0/5) edges ahead of DataArt (4.0/5) overall. X-Team is the better choice for media and gaming teams adding long-term remote developers. 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.
X-Team vs DataArt: head-to-head summary
| Criterion | X-Team | DataArt |
|---|---|---|
| Founded | 2006 | 1997 |
| HQ | Remote (no central office) | New York, USA |
| Team size | 5,000+ developer network | 5,000–6,000 |
| Rating | 4.0 / 5 | 4.0 / 5 |
| Primary differentiator | Developer-community model aimed at long placements | Dedicated development centers with nearly 30 years of history |
| Pricing model | Monthly per developer; squads; 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 | Media, Gaming, Education, Fintech | Fintech, Travel, Healthcare, Media |
X-Team vs DataArt: overview
X-Team
X-Team says it was founded in 2006 and operates as a fully remote company without a central office; one directory lists a 2020 date for its current Australian parent entity. It embeds long-term engineers and squads in client teams and lists clients such as Fox, Riot Games and Kaplan. Its AI developers cover Python, TensorFlow, PyTorch and LLM work, drawn from a pool it puts at more than 5,000 senior developers with retention of about 96–97% (per company website; independently unverifiable).
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: X-Team vs DataArt
| Capability | X-Team | 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: X-Team vs DataArt
| Framework / platform | X-Team | DataArt |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | ✓ |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | ✓ |
Pricing comparison: X-Team vs DataArt
| Criterion | X-Team | DataArt |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Full-time dedicated engineers, Dedicated team | Dedicated team, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: X-Team vs DataArt
| Dimension | X-Team | DataArt |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Media, Gaming, Education | Fintech, Travel, Healthcare |
| Best use cases | Adding a Python ML developer to a media company's product team, Long-term squad for a gaming platform with recommendation features | 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 |
X-Team vs DataArt: pros and cons
| X-Team | |
|---|---|
| + | Built for long engagements, with high reported retention |
| + | Named media and gaming clients |
| + | Can supply whole squads |
| - | General software focus; AI depth varies |
| - | Founding and entity details are inconsistent across sources |
| - | No published rates |
| 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 X-Team?
A typical fit: adding a Python ML developer to a media company's product team.
Developer-community model aimed at long placements. Minimum engagement is not publicly disclosed. Works best with clients in Media, Gaming, Education, Fintech.
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: X-Team 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 | X-Team |
| Your budget is at the lower end | Compare: X-Team (Not disclosed) vs DataArt (Not disclosed) |
| You need specialist depth in a specific vertical | X-Team |
| 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: X-Team vs DataArt
| Use case | X-Team fit | DataArt fit | Winner |
|---|---|---|---|
| Adding a Python ML developer to a media company's product team | Strong | Strong | Both equally |
| Long-term squad for a gaming platform with recommendation features | Strong | Strong | Both equally |
| 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: X-Team vs DataArt
X-Team (4.0/5) is the stronger overall choice for most AI Staffing projects. Developer-community model aimed at long placements.
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
X-Team vs DataArt FAQ
Is X-Team better than DataArt?
X-Team (4.0/5) scores higher overall, but "better" depends on your use case. X-Team's strongest advantage: built for long engagements, with high reported retention. DataArt's strongest advantage: long-running dedicated teams with low churn.
How do X-Team and DataArt differ in pricing?
X-Team uses monthly per developer; squads; 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: X-Team 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 X-Team and DataArt?
X-Team's primary differentiator is: developer-community model aimed at long placements. DataArt's primary differentiator is: dedicated development centers with nearly 30 years of history. They also differ in team size (5,000+ developer network vs 5,000–6,000), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Media, Gaming vs Fintech, Travel).
Verify all details directly with each agency before making a decision.