STX Next vs Revelo: full comparison for 2026
Quick verdict
STX Next (3.9/5) edges ahead of Revelo (3.8/5) overall. STX Next is the better choice for python codebases adding LLM and data engineers. Revelo is the stronger option for hiring Latin American developers through a marketplace. 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 | São Paulo, Brazil |
| Team size | 250–500 | 400,000+ developer network (per company) |
| Rating | 3.9 / 5 | 3.8 / 5 |
| Primary differentiator | Python specialization applied to data and AI delivery | A very large Latin American pool with payroll and compliance included |
| Pricing model | Time and materials; dedicated teams; rates on request | Marketplace placement with monthly billing; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Django, FastAPI | Python, OpenAI, Hugging Face |
| Industries served | Financial services, Software & SaaS, Media, Healthcare & life sciences | Software & SaaS, AI research labs, Financial services |
STX Next vs Revelo: overview
STX Next
STX Next was founded in Poznań in March 2005 and built its reputation as one of Europe's largest Python software houses. Its 2025 anniversary release cites about 500 staff and more than 1,000 delivered projects, with delivery centers in Poland and Mexico. The firm now presents itself as a data and AI consultancy, and Python's dominance in ML makes its bench a natural fit for model and data work.
Revelo
Revelo was founded in late 2014 in Brazil (some sources say 2015) and began as a domestic hiring platform called Contratado. It now runs a network of more than 400,000 Latin American developers and handles hiring and payment for U.S. customers. TechCrunch reported that work on foundation models made up 22% of Revelo's revenue in 2024. Revelo is a marketplace, so engineers are matched through its platform rather than employed in a delivery center.
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 | N/A |
| TensorFlow | N/A | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | ✓ |
| OpenAI | N/A | ✓ |
| AWS | ✓ | ✓ |
| Azure | 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 published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers |
| 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 | Financial services, Software & SaaS, Media | Software & SaaS, AI research labs, Financial services |
| Best use cases | Adding LLM features to a Django product, Building data jobs in Python for analytics | Hiring LLM data specialists for a model-training effort, Adding a Brazilian developer to a U.S. SaaS team |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
STX Next vs Revelo: pros and cons
| STX Next | |
|---|---|
| + | Python depth fits most AI codebases |
| + | Delivery from both Poland and Mexico |
| + | Long history of extending client teams |
| - | AI positioning is recent compared with its Python history |
| - | Polish rates are above Ukrainian and Latin American options |
| - | Fewer specialist roles such as computer vision |
| Revelo | |
|---|---|
| + | Very large pool across Latin America |
| + | Handles hiring, payroll and compliance |
| + | Foundation-model work gives some engineers LLM training experience |
| - | Marketplace matching means quality varies by candidate |
| - | Founding year is reported as both 2014 and 2015 |
| - | Less hands-on management than employer-based firms |
Who should choose STX Next?
A typical fit: adding LLM features to a Django product.
Python specialization applied to data and AI delivery. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Software & SaaS, Media, Healthcare & life sciences.
Who should choose Revelo?
A typical fit: hiring LLM data specialists for a model-training effort.
A very large Latin American pool with payroll and compliance included. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, AI research labs, Financial services.
Decision matrix: STX Next vs Revelo
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | STX Next |
| You want the supplier to own delivery as well as staffing | STX Next |
| You need one expert part-time | Neither lists part-time experts; ask about reduced hours |
| You want to test an engineer before signing for months | Neither publishes a trial; ask for a short first term |
| Your budget is at the lower end | Compare: STX Next (Not published) vs Revelo (Not published) |
| You need overlap with U.S. working hours | Revelo |
| You need specialist depth in a specific vertical | STX Next |
Use case fit: STX Next vs Revelo
| Use case | STX Next fit | Revelo fit | Winner |
|---|---|---|---|
| Adding LLM features to a Django product | Strong | Strong | Both equally |
| Building data jobs in Python for analytics | Strong | Limited | STX Next |
| Hiring LLM data specialists for a model-training effort | Limited | Strong | Revelo |
| Adding a Brazilian developer to a U.S. SaaS team | Strong | Strong | Both equally |
Verdict: STX Next vs Revelo
STX Next (3.9/5) is the stronger overall choice for most AI Staff Augmentation projects. Python specialization applied to data and AI delivery.
Revelo (3.8/5) is worth a look if you need adding a Brazilian developer to a U.S. SaaS team. 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 (3.9/5) scores higher overall, but "better" depends on your use case. STX Next's strongest advantage: python depth fits most AI codebases. Revelo's strongest advantage: very large pool across Latin America.
How do STX Next and Revelo differ in pricing?
STX Next uses time and materials; dedicated teams; rates on request pricing. Revelo uses marketplace placement with monthly billing; 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 company before shortlisting.
What are the main differences between STX Next and Revelo?
STX Next's primary differentiator is: python specialization applied to data and AI delivery. Revelo's primary differentiator is: a very large Latin American pool with payroll and compliance included. They also differ in team size (250–500 vs 400,000+ developer network (per company)), minimum engagement (Not published vs Not published), and primary industries served (Financial services, Software & SaaS vs Software & SaaS, AI research labs).
Verify all details directly with each company before making a decision.