Nearsure vs STX Next: full comparison for 2026
Quick verdict
Nearsure (3.9/5) edges ahead of STX Next (3.9/5) overall. Nearsure is the better choice for U.S. teams adding Latin American GenAI developers. STX Next is the stronger option for python codebases adding LLM and data engineers. The right choice depends on your project size, budget, and required tech stack.
Nearsure vs STX Next: head-to-head summary
| Criterion | Nearsure | STX Next |
|---|---|---|
| Founded | 2018 | 2005 |
| HQ | Montevideo, Uruguay (U.S.-incorporated) | Poznań, Poland |
| Team size | 500–850 (sources vary) | 250–500 |
| Rating | 3.9 / 5 | 3.9 / 5 |
| Primary differentiator | Augmentation-first business model with a growing AI studio | Python specialization applied to data and AI delivery |
| Pricing model | Monthly staff augmentation rates; project development; rates on request | Time and materials; dedicated teams; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, OpenAI, AWS | Python, Django, FastAPI |
| Industries served | Software & SaaS, Healthcare & life sciences, Financial services | Financial services, Software & SaaS, Media, Healthcare & life sciences |
Nearsure vs STX Next: overview
Nearsure
Nearsure started operations in 2018 under co-founder and CEO Giuliana Corbo and is described by Bloomberg as a Uruguayan IT services company, though it is incorporated in the United States. Bloomberg reported a 2024 plan to grow to about 850 staff. Remote staff augmentation for U.S. clients is its core business, and the service list has widened to generative AI, cloud migration and Salesforce work through a Data & AI studio.
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.
Services and capabilities: Nearsure vs STX Next
| Capability | Nearsure | STX Next |
|---|---|---|
| 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: Nearsure vs STX Next
| Framework / platform | Nearsure | STX Next |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| LangChain | N/A | ✓ |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Nearsure vs STX Next
| Criterion | Nearsure | STX Next |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team | Full-time dedicated engineers, Dedicated team, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Nearsure vs STX Next
| Dimension | Nearsure | STX Next |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Software & SaaS, Healthcare & life sciences, Financial services | Financial services, Software & SaaS, Media |
| Best use cases | Adding a GenAI developer to a U.S. SaaS team, Staffing data engineers for a cloud migration | Adding LLM features to a Django product, Building data jobs in Python for analytics |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
Nearsure vs STX Next: pros and cons
| Nearsure | |
|---|---|
| + | Staff augmentation is the main business, so processes are built around it |
| + | Latin American engineers on U.S. hours |
| + | Has been profitable since early in its history, per AméricaEconomía |
| - | AI is a newer studio inside a general staffing company |
| - | Headcount reports vary between 525 and 850 |
| - | HQ location differs between sources |
| 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 |
Who should choose Nearsure?
A typical fit: adding a GenAI developer to a U.S. SaaS team.
Augmentation-first business model with a growing AI studio. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Healthcare & life sciences, Financial services.
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.
Decision matrix: Nearsure vs STX Next
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; Nearsure rates higher overall |
| 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: Nearsure (Not published) vs STX Next (Not published) |
| You need overlap with U.S. working hours | Nearsure |
| You need specialist depth in a specific vertical | STX Next |
Use case fit: Nearsure vs STX Next
| Use case | Nearsure fit | STX Next fit | Winner |
|---|---|---|---|
| Adding a GenAI developer to a U.S. SaaS team | Strong | Strong | Both equally |
| Staffing data engineers for a cloud migration | Strong | Limited | Nearsure |
| Adding LLM features to a Django product | Strong | Strong | Both equally |
| Building data jobs in Python for analytics | Limited | Strong | STX Next |
Verdict: Nearsure vs STX Next
Nearsure (3.9/5) is the stronger overall choice for most AI Staff Augmentation projects. Augmentation-first business model with a growing AI studio.
STX Next (3.9/5) is worth a look if you need building data jobs in Python for analytics. If your situation matches that, STX Next is a competitive option.
Related comparisons
Nearsure vs STX Next FAQ
Is Nearsure better than STX Next?
Nearsure (3.9/5) scores higher overall, but "better" depends on your use case. Nearsure's strongest advantage: staff augmentation is the main business, so processes are built around it. STX Next's strongest advantage: python depth fits most AI codebases.
How do Nearsure and STX Next differ in pricing?
Nearsure uses monthly staff augmentation rates; project development; rates on request pricing. STX Next uses time and materials; dedicated teams; 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: Nearsure or STX Next?
Nearsure 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 Nearsure and STX Next?
Nearsure's primary differentiator is: augmentation-first business model with a growing AI studio. STX Next's primary differentiator is: python specialization applied to data and AI delivery. They also differ in team size (500–850 (sources vary) vs 250–500), minimum engagement (Not published vs Not published), and primary industries served (Software & SaaS, Healthcare & life sciences vs Financial services, Software & SaaS).
Verify all details directly with each company before making a decision.