STX Next vs Revelo: full comparison for 2026
Quick verdict
STX Next (4.2/5) edges ahead of Revelo (3.9/5) overall. STX Next is the better choice for python product teams adding ML capacity. Revelo is the stronger option for companies hiring LatAm developers without a local entity. The right choice depends on your project size, budget, and required tech stack.
STX Next vs Revelo: head-to-head summary
| Criterion | STX Next | Revelo |
|---|---|---|
| Founded | 2005 | 2014 |
| HQ | Poznań, Poland | Miami, Florida, USA |
| Team size | 250–999 | 251–500 |
| Rating | 4.2 / 5 | 3.9 / 5 |
| Primary differentiator | Large Python bench with documented ML staff-augmentation work | Payroll and compliance handled for LatAm hires |
| Pricing model | Time and materials; team extension; rates on request | Monthly per developer including payroll and compliance; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, Django, PyTorch | Python, OpenAI, AWS |
| Industries served | Real estate tech, Healthcare, Fintech, SaaS | SaaS, Fintech, E-commerce, AI labs |
STX Next vs Revelo: overview
STX Next
STX Next was founded in 2005 in Poznań, Poland, and runs delivery centers in Poland and Mexico. It describes itself as Europe's largest Python-focused engineering partner for data, AI and cloud (per company website; independently unverifiable), and Clutch places it in the 250–999 employee band. A Clutch review covers a 2023–2024 staff-augmentation engagement for a real-estate technology client involving machine learning, computer vision and recommendation systems. Other reviews describe multi-year Python team extensions.
Revelo
Revelo traces its start to late 2014 and is headquartered in Miami, with 251–500 employees according to one directory. It runs a platform of more than 400,000 Latin American developers and handles sourcing, compliance, local payroll and benefits, so clients can hire individuals or whole teams without opening a local entity. It has also moved into LLM post-training work, supplying developers for supervised fine-tuning and RLHF projects. It has raised more than $48 million from investors including Social Capital and Valor Capital Group.
Services and capabilities: STX Next vs Revelo
| Capability | STX Next | Revelo |
|---|---|---|
| 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: STX Next vs Revelo
| Framework / platform | STX Next | Revelo |
|---|---|---|
| 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 | N/A |
Pricing comparison: STX Next vs Revelo
| Criterion | STX Next | Revelo |
|---|---|---|
| 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: STX Next vs Revelo
| Dimension | STX Next | Revelo |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Real estate tech, Healthcare, Fintech | SaaS, Fintech, E-commerce |
| Best use cases | Adding a recommendation-systems engineer to a marketplace product, Extending a Python team with a computer-vision specialist | Hiring a full-time LatAm developer with payroll handled, Staffing LLM post-training projects |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
STX Next vs Revelo: pros and cons
| STX Next | |
|---|---|
| + | Python depth means ML and backend roles come from one bench |
| + | Documented multi-year team extensions |
| + | Mexico center adds U.S. time-zone coverage |
| - | AI is a practice within a broader Python services company |
| - | Largest-in-Europe positioning is the company's own claim |
| - | No public rates |
| Revelo | |
|---|---|
| + | Removes the legal and payroll work of hiring in Latin America |
| + | Large candidate pool |
| + | Experience supplying engineers for LLM training work |
| - | Platform model means vetting is lighter than at engineering agencies |
| - | AI focus leans toward LLM training data over product engineering |
| - | Pricing requires a call |
Who should choose STX Next?
A typical fit: adding a recommendation-systems engineer to a marketplace product.
Large Python bench with documented ML staff-augmentation work. Minimum engagement is not publicly disclosed. Works best with clients in Real estate tech, Healthcare, Fintech, SaaS.
Who should choose Revelo?
A typical fit: hiring a full-time LatAm developer with payroll handled.
Payroll and compliance handled for LatAm hires. Minimum engagement is not publicly disclosed. Works best with clients in SaaS, Fintech, E-commerce, AI labs.
Decision matrix: STX Next vs Revelo
| 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 | STX Next |
| Your budget is at the lower end | Compare: STX Next (Not disclosed) vs Revelo (Not disclosed) |
| You need specialist depth in a specific vertical | STX Next |
| 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: STX Next vs Revelo
| Use case | STX Next fit | Revelo fit | Winner |
|---|---|---|---|
| Adding a recommendation-systems engineer to a marketplace product | Strong | Limited | STX Next |
| Extending a Python team with a computer-vision specialist | Strong | Limited | STX Next |
| Hiring a full-time LatAm developer with payroll handled | Strong | Strong | Both equally |
| Staffing LLM post-training projects | Limited | Strong | Revelo |
Verdict: STX Next vs Revelo
STX Next (4.2/5) is the stronger overall choice for most AI Staffing projects. Large Python bench with documented ML staff-augmentation work.
Revelo (3.9/5) is worth a look if you need staffing LLM post-training projects. If your situation matches that, Revelo is a competitive option.
Related comparisons
STX Next vs Revelo FAQ
Is STX Next better than Revelo?
STX Next (4.2/5) scores higher overall, but "better" depends on your use case. STX Next's strongest advantage: python depth means ML and backend roles come from one bench. Revelo's strongest advantage: removes the legal and payroll work of hiring in Latin America.
How do STX Next and Revelo differ in pricing?
STX Next uses time and materials; team extension; rates on request pricing. Revelo uses monthly per developer including payroll and compliance; 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: STX Next or Revelo?
Revelo 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 STX Next and Revelo?
STX Next's primary differentiator is: large Python bench with documented ML staff-augmentation work. Revelo's primary differentiator is: payroll and compliance handled for LatAm hires. They also differ in team size (250–999 vs 251–500), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Real estate tech, Healthcare vs SaaS, Fintech).
Verify all details directly with each agency before making a decision.