Encora vs STX Next: full comparison for 2026
Quick verdict
Encora (4.0/5) edges ahead of STX Next (3.9/5) overall. Encora is the better choice for U.S. firms wanting nearshore AI teams from a large provider. 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.
Encora vs STX Next: head-to-head summary
| Criterion | Encora | STX Next |
|---|---|---|
| Founded | 2005 | 2005 |
| HQ | Scottsdale, Arizona, USA | Poznań, Poland |
| Team size | 9,500+ | 250–500 |
| Rating | 4.0 / 5 | 3.9 / 5 |
| Primary differentiator | Large Mexican and Latin American delivery base with an AI engineering practice | Python specialization applied to data and AI delivery |
| Pricing model | Dedicated teams; time and materials; 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, Travel | Financial services, Software & SaaS, Media, Healthcare & life sciences |
Encora vs STX Next: overview
Encora
Encora was founded in 2005 and is headquartered in Scottsdale, Arizona. It took its current name in 2020 after combining subsidiaries including Nearsoft, and it later absorbed Avantica. The company reports more than 9,500 engineers, designers and domain experts across the Americas, Europe, India and Southeast Asia, with AI and LLM engineering among its service lines. In December 2025 the Indian IT firm Coforge agreed to acquire Encora for about $2.35 billion, and Coforge said in April 2026 that all regulatory clearances had been received.
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: Encora vs STX Next
| Capability | Encora | 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: Encora vs STX Next
| Framework / platform | Encora | 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 | ✓ | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Encora vs STX Next
| Criterion | Encora | STX Next |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated team, Full-time dedicated engineers, 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: Encora vs STX Next
| Dimension | Encora | 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 | Building a nearshore team for a SaaS product's AI roadmap, Adding data and LLM engineers to a healthcare platform | Adding LLM features to a Django product, Building data jobs in Python for analytics |
| Typical project type | Dedicated team | Full-time dedicated engineers |
Encora vs STX Next: pros and cons
| Encora | |
|---|---|
| + | Nearshore delivery from Mexico and Latin America on U.S. hours |
| + | Scale to staff several teams at once |
| + | AI work is a named service line with its own platform |
| - | The Coforge acquisition may change account management, pricing and contract terms |
| - | Dedicated teams are the norm, so single-seat placements are less common |
| - | AI depth varies by delivery center |
| 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 Encora?
A typical fit: building a nearshore team for a SaaS product's AI roadmap.
Large Mexican and Latin American delivery base with an AI engineering practice. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Healthcare & life sciences, Financial services, Travel.
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: Encora vs STX Next
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Both; Encora rates higher overall |
| You want the supplier to own delivery as well as staffing | Both; Encora 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: Encora (Not published) vs STX Next (Not published) |
| You need overlap with U.S. working hours | Encora |
| You need specialist depth in a specific vertical | Encora |
Use case fit: Encora vs STX Next
| Use case | Encora fit | STX Next fit | Winner |
|---|---|---|---|
| Building a nearshore team for a SaaS product's AI roadmap | Strong | Strong | Both equally |
| Adding data and LLM engineers to a healthcare platform | 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: Encora vs STX Next
Encora (4.0/5) is the stronger overall choice for most AI Staff Augmentation projects. Large Mexican and Latin American delivery base with an AI engineering practice.
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
Encora vs STX Next FAQ
Is Encora better than STX Next?
Encora (4.0/5) scores higher overall, but "better" depends on your use case. Encora's strongest advantage: nearshore delivery from Mexico and Latin America on U.S. hours. STX Next's strongest advantage: python depth fits most AI codebases.
How do Encora and STX Next differ in pricing?
Encora uses dedicated teams; time and materials; 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: Encora 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 Encora and STX Next?
Encora's primary differentiator is: large Mexican and Latin American delivery base with an AI engineering practice. STX Next's primary differentiator is: python specialization applied to data and AI delivery. They also differ in team size (9,500+ 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.