Azumo vs STX Next: full comparison for 2026
Quick verdict
Azumo (4.1/5) edges ahead of STX Next (3.9/5) overall. Azumo is the better choice for nearshore LLM and NLP builds for U.S. mid-market. 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.
Azumo vs STX Next: head-to-head summary
| Criterion | Azumo | STX Next |
|---|---|---|
| Founded | 2016 | 2005 |
| HQ | San Francisco, California, USA | Poznań, Poland |
| Team size | 100–500 (sources vary) | 250–500 |
| Rating | 4.1 / 5 | 3.9 / 5 |
| Primary differentiator | A nearshore team that also builds its own NLP products | Python specialization applied to data and AI delivery |
| Pricing model | Monthly rates for augmented engineers; dedicated teams; project pricing; rates on request | Time and materials; dedicated teams; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, LangChain, OpenAI | Python, Django, FastAPI |
| Industries served | Healthcare & life sciences, Media, Software & SaaS, Financial services | Financial services, Software & SaaS, Media, Healthcare & life sciences |
Azumo vs STX Next: overview
Azumo
Azumo is headquartered in San Francisco and has built AI-driven applications since 2016, with most of its engineers in Latin America. Directory headcounts range from under 100 to several hundred people. It offers staff augmentation, dedicated teams and full product outsourcing, and it also maintains its own AI products, including an NLU toolkit. Named clients include Meta and UnitedHealth (per company website; independently unverifiable).
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: Azumo vs STX Next
| Capability | Azumo | 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: Azumo vs STX Next
| Framework / platform | Azumo | STX Next |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| LangChain | ✓ | ✓ |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Azumo vs STX Next
| Criterion | Azumo | STX Next |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers, Dedicated team, Managed delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Azumo vs STX Next
| Dimension | Azumo | STX Next |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare & life sciences, Media, Software & SaaS | Financial services, Software & SaaS, Media |
| Best use cases | Adding a conversational-AI engineer to a healthcare app team, Building a document-search assistant on internal knowledge | 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 |
Azumo vs STX Next: pros and cons
| Azumo | |
|---|---|
| + | Its own AI products show applied NLP experience |
| + | Latin American engineers share U.S. working hours |
| + | Flexible mix of augmentation and project delivery |
| - | Headcount reports vary widely, so ask how many AI engineers are actually on staff |
| - | Smaller bench than the large nearshore firms on this list |
| - | Founding year differs across sources (2013 or 2016) |
| 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 Azumo?
A typical fit: adding a conversational-AI engineer to a healthcare app team.
A nearshore team that also builds its own NLP products. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare & life sciences, Media, Software & SaaS, 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: Azumo vs STX Next
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; Azumo rates higher overall |
| You want the supplier to own delivery as well as staffing | Both; Azumo rates higher overall |
| 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: Azumo (Not published) vs STX Next (Not published) |
| You need overlap with U.S. working hours | Azumo |
| You need specialist depth in a specific vertical | Azumo |
Use case fit: Azumo vs STX Next
| Use case | Azumo fit | STX Next fit | Winner |
|---|---|---|---|
| Adding a conversational-AI engineer to a healthcare app team | Strong | Strong | Both equally |
| Building a document-search assistant on internal knowledge | Strong | Strong | Both equally |
| Adding LLM features to a Django product | Strong | Strong | Both equally |
| Building data jobs in Python for analytics | Strong | Strong | Both equally |
Verdict: Azumo vs STX Next
Azumo (4.1/5) is the stronger overall choice for most AI Staff Augmentation projects. A nearshore team that also builds its own NLP products.
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
Azumo vs STX Next FAQ
Is Azumo better than STX Next?
Azumo (4.1/5) scores higher overall, but "better" depends on your use case. Azumo's strongest advantage: its own AI products show applied NLP experience. STX Next's strongest advantage: python depth fits most AI codebases.
How do Azumo and STX Next differ in pricing?
Azumo uses monthly rates for augmented engineers; dedicated teams; project pricing; 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: Azumo or STX Next?
STX Next 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 Azumo and STX Next?
Azumo's primary differentiator is: a nearshore team that also builds its own NLP products. STX Next's primary differentiator is: python specialization applied to data and AI delivery. They also differ in team size (100–500 (sources vary) vs 250–500), minimum engagement (Not published vs Not published), and primary industries served (Healthcare & life sciences, Media vs Financial services, Software & SaaS).
Verify all details directly with each company before making a decision.