10Clouds vs KORE1: full comparison for 2026
Quick verdict
10Clouds (4.1/5) edges ahead of KORE1 (3.9/5) overall. 10Clouds is the better choice for Banks, insurers and fintechs building AI features. KORE1 is the stronger option for U.S. companies that want to hire AI engineers onto payroll. The right choice depends on your project size, budget, and required tech stack.
10Clouds vs KORE1: head-to-head summary
| Criterion | 10Clouds | KORE1 |
|---|---|---|
| Founded | 2009 | 2005 |
| HQ | Warsaw, Poland | Irvine, California, USA |
| Team size | 100–200 | Not disclosed |
| Rating | 4.1 / 5 | 3.9 / 5 |
| Primary differentiator | Financial-services AI focus with Claude partner status | Direct-hire and contract-to-hire paths for AI roles |
| Pricing model | Time and materials; fixed-term staff augmentation; rates on request | Contract bill rate or direct-hire placement fee; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, Claude, OpenAI | Python, PyTorch, TensorFlow |
| Industries served | Fintech, Banking, Insurance, SaaS | Healthcare, SaaS, Fintech, Manufacturing |
10Clouds vs KORE1: overview
10Clouds
10Clouds was founded in 2009 in Warsaw by Maciej Cielecki and others, and employs somewhere between 100 and 200 people depending on the source. It keeps an in-house product team and also supplies developers or designers to clients for fixed periods, a model it has used with U.S. clients such as Rippling. In 2026 it announced a merger with 10Clouds Financial Institutions, creating an AI unit for banks, insurers and fintechs, and it is a Select partner in the Claude Partner Network services track.
KORE1
KORE1 was founded in 2005 and is headquartered in Irvine, California, serving clients in more than 30 U.S. metro areas. Unlike most companies on this list, it is a traditional staffing and recruiting firm: it places AI and ML engineers as contractors, contract-to-hire or direct employees of the client. It says it fills AI roles in an average of 17 days with 92% twelve-month retention (per company website; independently unverifiable).
Services and capabilities: 10Clouds vs KORE1
| Capability | 10Clouds | KORE1 |
|---|---|---|
| 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: 10Clouds vs KORE1
| Framework / platform | 10Clouds | KORE1 |
|---|---|---|
| PyTorch | N/A | ✓ |
| TensorFlow | N/A | ✓ |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | N/A |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | ✓ |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: 10Clouds vs KORE1
| Criterion | 10Clouds | KORE1 |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Full-time dedicated engineers, Managed delivery | Contract-to-hire, Full-time dedicated engineers |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: 10Clouds vs KORE1
| Dimension | 10Clouds | KORE1 |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Fintech, Banking, Insurance | Healthcare, SaaS, Fintech |
| Best use cases | Adding an agent developer to a bank's internal automation team, Staffing an LLM engineer for an insurer's claims product | Hiring a U.S.-based ML engineer as a permanent employee, Contract-to-hire for an MLOps role |
| Typical project type | Full-time dedicated engineers | Contract-to-hire |
10Clouds vs KORE1: pros and cons
| 10Clouds | |
|---|---|
| + | Clear industry focus on regulated financial services |
| + | Claude Partner Network status for teams building on Anthropic models |
| + | Has worked as an embedded team for U.S. scale-ups |
| - | The 2026 merger means leadership and structure are still settling |
| - | Small bench for large placements |
| - | Rates not published |
| KORE1 | |
|---|---|
| + | Only company here built around converting contractors into your own employees |
| + | U.S.-based candidates for roles that need on-site or domestic staff |
| + | Stated 17-day average fill time |
| - | Recruiter-led screening; technical vetting relies on your interviews |
| - | U.S. salaries make it the costliest option per engineer |
| - | Performance claims are self-reported |
Who should choose 10Clouds?
A typical fit: adding an agent developer to a bank's internal automation team.
Financial-services AI focus with Claude partner status. Minimum engagement is not publicly disclosed. Works best with clients in Fintech, Banking, Insurance, SaaS.
Who should choose KORE1?
A typical fit: hiring a U.S.-based ML engineer as a permanent employee.
Direct-hire and contract-to-hire paths for AI roles. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, SaaS, Fintech, Manufacturing.
Decision matrix: 10Clouds vs KORE1
| 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 | 10Clouds |
| Your budget is at the lower end | Compare: 10Clouds (Not disclosed) vs KORE1 (Not disclosed) |
| You need specialist depth in a specific vertical | 10Clouds |
| 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: 10Clouds vs KORE1
| Use case | 10Clouds fit | KORE1 fit | Winner |
|---|---|---|---|
| Adding an agent developer to a bank's internal automation team | Strong | Limited | 10Clouds |
| Staffing an LLM engineer for an insurer's claims product | Strong | Limited | 10Clouds |
| Hiring a U.S.-based ML engineer as a permanent employee | Limited | Strong | KORE1 |
| Contract-to-hire for an MLOps role | Limited | Strong | KORE1 |
Verdict: 10Clouds vs KORE1
10Clouds (4.1/5) is the stronger overall choice for most AI Staffing projects. Financial-services AI focus with Claude partner status.
KORE1 (3.9/5) is worth a look if you need contract-to-hire for an MLOps role. If your situation matches that, KORE1 is a competitive option.
Related comparisons
10Clouds vs KORE1 FAQ
Is 10Clouds better than KORE1?
10Clouds (4.1/5) scores higher overall, but "better" depends on your use case. 10Clouds's strongest advantage: clear industry focus on regulated financial services. KORE1's strongest advantage: only company here built around converting contractors into your own employees.
How do 10Clouds and KORE1 differ in pricing?
10Clouds uses time and materials; fixed-term staff augmentation; rates on request pricing. KORE1 uses contract bill rate or direct-hire placement fee; 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: 10Clouds or KORE1?
10Clouds 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 10Clouds and KORE1?
10Clouds's primary differentiator is: financial-services AI focus with Claude partner status. KORE1's primary differentiator is: direct-hire and contract-to-hire paths for AI roles. They also differ in team size (100–200 vs Not disclosed), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Fintech, Banking vs Healthcare, SaaS).
Verify all details directly with each agency before making a decision.