Xenoss vs X-Team: full comparison for 2026
Quick verdict
Xenoss (4.3/5) edges ahead of X-Team (4.0/5) overall. Xenoss is the better choice for ad-tech and high-volume data teams. X-Team is the stronger option for media and gaming teams adding long-term remote developers. The right choice depends on your project size, budget, and required tech stack.
Xenoss vs X-Team: head-to-head summary
| Criterion | Xenoss | X-Team |
|---|---|---|
| Founded | 2013 | 2006 |
| HQ | New York, USA | Remote (no central office) |
| Team size | 50–249 | 5,000+ developer network |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Primary differentiator | Data engineers with ad-tech throughput experience | Developer-community model aimed at long placements |
| Pricing model | Time and materials; staff augmentation; rates on request | Monthly per developer; squads; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, Apache Spark, Kafka | Python, TensorFlow, PyTorch |
| Industries served | Ad tech, Media, Fintech, Retail and e-commerce | Media, Gaming, Education, Fintech |
Xenoss vs X-Team: overview
Xenoss
Xenoss was founded in 2013 by ad-tech veterans led by CEO Dmitry Sverdlik and is based in New York, with offices in London and Kyiv. It describes itself as a specialized AI and data-engineering company, and Clutch places it in the 50–249 employee band. Client reviews describe staff augmentation in practice: one London ad-tech client hired Xenoss after failing to find engineers locally, and Xenoss sourced candidates from Ukraine and integrated them into the in-house team. Its background in high-throughput ad-tech systems shows in its data-engineering work.
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).
Services and capabilities: Xenoss vs X-Team
| Capability | Xenoss | X-Team |
|---|---|---|
| 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: Xenoss vs X-Team
| Framework / platform | Xenoss | X-Team |
|---|---|---|
| PyTorch | N/A | ✓ |
| TensorFlow | N/A | ✓ |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | ✓ |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
| Databricks | ✓ | N/A |
| MLflow | N/A | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: Xenoss vs X-Team
| Criterion | Xenoss | X-Team |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Xenoss vs X-Team
| Dimension | Xenoss | X-Team |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Ad tech, Media, Fintech | Media, Gaming, Education |
| Best use cases | Adding streaming-data engineers ahead of an ML launch, Placing ML engineers in a bidding or attribution product | Adding a Python ML developer to a media company's product team, Long-term squad for a gaming platform with recommendation features |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
Xenoss vs X-Team: pros and cons
| Xenoss | |
|---|---|
| + | Strong on real-time data infrastructure that ML features depend on |
| + | Has placed engineers into UK teams that struggled to hire locally |
| + | Senior leadership comes from the industry it serves most |
| + | Covers both data engineering and model work |
| - | Ad-tech focus is narrower than general AI staffing |
| - | Mid-sized bench |
| - | Rates are not public |
| 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 |
Who should choose Xenoss?
A typical fit: adding streaming-data engineers ahead of an ML launch.
Data engineers with ad-tech throughput experience. Minimum engagement is not publicly disclosed. Works best with clients in Ad tech, Media, Fintech, Retail and e-commerce.
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.
Decision matrix: Xenoss vs X-Team
| 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 | Xenoss |
| Your budget is at the lower end | Compare: Xenoss (Not disclosed) vs X-Team (Not disclosed) |
| You need specialist depth in a specific vertical | Xenoss |
| 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: Xenoss vs X-Team
| Use case | Xenoss fit | X-Team fit | Winner |
|---|---|---|---|
| Adding streaming-data engineers ahead of an ML launch | Strong | Strong | Both equally |
| Placing ML engineers in a bidding or attribution product | Strong | Limited | Xenoss |
| 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 | Limited | Strong | X-Team |
Verdict: Xenoss vs X-Team
Xenoss (4.3/5) is the stronger overall choice for most AI Staffing projects. Data engineers with ad-tech throughput experience.
X-Team (4.0/5) is worth a look if you need long-term squad for a gaming platform with recommendation features. If your situation matches that, X-Team is a competitive option.
Related comparisons
Xenoss vs X-Team FAQ
Is Xenoss better than X-Team?
Xenoss (4.3/5) scores higher overall, but "better" depends on your use case. Xenoss's strongest advantage: strong on real-time data infrastructure that ML features depend on. X-Team's strongest advantage: built for long engagements, with high reported retention.
How do Xenoss and X-Team differ in pricing?
Xenoss uses time and materials; staff augmentation; rates on request pricing. X-Team uses monthly per developer; squads; 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: Xenoss or X-Team?
Xenoss 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 Xenoss and X-Team?
Xenoss's primary differentiator is: data engineers with ad-tech throughput experience. X-Team's primary differentiator is: developer-community model aimed at long placements. They also differ in team size (50–249 vs 5,000+ developer network), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Ad tech, Media vs Media, Gaming).
Verify all details directly with each agency before making a decision.