Best AI Staffing Agencies

Tensorway vs 10Clouds: full comparison for 2026

Quick verdict

Tensorway (4.8/5) edges ahead of 10Clouds (4.1/5) overall. Tensorway is the better choice for product teams adding AI engineers fast, two-week trial. 10Clouds is the stronger option for Banks, insurers and fintechs building AI features. The right choice depends on your project size, budget, and required tech stack.

Tensorway vs 10Clouds: head-to-head summary

Criterion Tensorway 10Clouds
Founded 2019 2009
HQ Alicante, Spain Warsaw, Poland
Team size 50–249 100–200
Rating 4.8 / 5 4.1 / 5
Primary differentiator Engineer-led screening with a free replacement if a hire doesn't fit Financial-services AI focus with Claude partner status
Pricing model Monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request Time and materials; fixed-term staff augmentation; rates on request
Min. engagement Not disclosed Not disclosed
Primary tech stack PyTorch, TensorFlow, LangChain Python, Claude, OpenAI
Industries served Healthcare, Legal services, SaaS, Fintech, E-commerce and retail, Manufacturing, Logistics Fintech, Banking, Insurance, SaaS

Tensorway vs 10Clouds: overview

Tensorway

Tensorway is an AI engineering company founded in 2019 and based in Alicante, Spain, with more than 20 years of software engineering experience in its leadership and delivery processes. Its staff-augmentation service places ML engineers, LLM engineers, AI agent developers, MLOps engineers, computer-vision and NLP specialists, data engineers and RAG specialists directly into a client's own team, where they work in the client's Slack, Jira and repositories. Candidates are screened by senior AI engineers through a code review, a practical task in their specialization and a communication check, so the client receives a shortlist of two or three people that is already technically vetted. Tensorway handles contracts and admin; the first engineer typically starts within one to two weeks and a full squad within three to four weeks (per company website; independently unverifiable). One published case study describes a U.S. law practice, Liner Legal, cutting medical-record processing from about a week to 5–15 minutes (per company website; independently unverifiable).

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.

Services and capabilities: Tensorway vs 10Clouds

Capability Tensorway 10Clouds
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: Tensorway vs 10Clouds

Framework / platform Tensorway 10Clouds
PyTorch ✓ N/A
TensorFlow ✓ N/A
LangChain ✓ ✓
Hugging Face ✓ N/A
OpenAI ✓ ✓
AWS SageMaker N/A N/A
Azure ML N/A N/A
Databricks N/A N/A
MLflow ✓ N/A
Kubernetes ✓ N/A

Pricing comparison: Tensorway vs 10Clouds

Criterion Tensorway 10Clouds
Minimum engagement Not disclosed Not disclosed
Engagement models Full-time dedicated engineers, Part-time fractional experts, Trial period Full-time dedicated engineers, Managed delivery
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: Tensorway vs 10Clouds

Dimension Tensorway 10Clouds
Best company size Startup to mid-market Startup to mid-market
Best industries Healthcare, Legal services, SaaS Fintech, Banking, Insurance
Best use cases Adding an LLM engineer and a RAG specialist to an existing SaaS product team, Trialing a single ML engineer for two weeks before committing to a monthly contract Adding an agent developer to a bank's internal automation team, Staffing an LLM engineer for an insurer's claims product
Typical project type Full-time dedicated engineers Full-time dedicated engineers

Tensorway vs 10Clouds: pros and cons

Tensorway
+ Candidates are screened by working AI engineers through a code review and a practical task, so your interviews can focus on team fit
+ A shortlist of two or three people usually arrives within a week of the discovery call
+ A poor fit is replaced at no cost, and the monthly commitment can be adjusted between sprints
+ All code, documentation and trained models stay in your repositories, which keeps vendor lock-in off the table
+ Contracts, local employment paperwork and benefits admin are handled by Tensorway rather than your HR team
- No public rate card, so budgeting starts with a sales call
- The bench is far smaller than the large talent networks, which matters if you need ten or more engineers at once
- AI and ML roles only; general full-stack or QA staffing is out of scope
- Time-zone overlap is arranged per engagement instead of guaranteed by a fixed nearshore location
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

Who should choose Tensorway?

A typical fit: adding an LLM engineer and a RAG specialist to an existing SaaS product team.

Engineer-led screening with a free replacement if a hire doesn't fit. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Legal services, SaaS, Fintech, E-commerce and retail, Manufacturing, Logistics.

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.

Decision matrix: Tensorway vs 10Clouds

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 Tensorway
Your budget is at the lower end Compare: Tensorway (Not disclosed) vs 10Clouds (Not disclosed)
You need specialist depth in a specific vertical Tensorway
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: Tensorway vs 10Clouds

Use case Tensorway fit 10Clouds fit Winner
Adding an LLM engineer and a RAG specialist to an existing SaaS product team Strong Strong Both equally
Trialing a single ML engineer for two weeks before committing to a monthly contract Strong Limited Tensorway
Adding an agent developer to a bank's internal automation team Strong Strong Both equally
Staffing an LLM engineer for an insurer's claims product Strong Strong Both equally

Verdict: Tensorway vs 10Clouds

Tensorway (4.8/5) is the stronger overall choice for most AI Staffing projects. Engineer-led screening with a free replacement if a hire doesn't fit.

10Clouds (4.1/5) is worth a look if you need staffing an LLM engineer for an insurer's claims product. If your situation matches that, 10Clouds is a competitive option.

Related comparisons

Tensorway vs 10Clouds FAQ

Is Tensorway better than 10Clouds?

Tensorway (4.8/5) scores higher overall, but "better" depends on your use case. Tensorway's strongest advantage: candidates are screened by working AI engineers through a code review and a practical task, so your interviews can focus on team fit. 10Clouds's strongest advantage: clear industry focus on regulated financial services.

How do Tensorway and 10Clouds differ in pricing?

Tensorway uses monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request pricing. 10Clouds uses time and materials; fixed-term staff augmentation; 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: Tensorway or 10Clouds?

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 Tensorway and 10Clouds?

Tensorway's primary differentiator is: engineer-led screening with a free replacement if a hire doesn't fit. 10Clouds's primary differentiator is: financial-services AI focus with Claude partner status. They also differ in team size (50–249 vs 100–200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Healthcare, Legal services vs Fintech, Banking).

Verify all details directly with each agency before making a decision.