NILG.AI vs STX Next: full comparison for 2026
Last updated: July 2026
Quick verdict
NILG.AI (4.5/5) edges ahead of STX Next (4.0/5) overall. NILG.AI is the better choice for companies earlier in their AI adoption curve that want a structured discover-pilot-scale engagement model rather than a from-scratch build.. STX Next is the stronger option for enterprises wanting Python-native ML and AI engineering from a vendor with two decades of Python specialization and certified partnerships across all three major clouds.. The right choice depends on your project size, budget, and required tech stack.
NILG.AI vs STX Next: head-to-head summary
| Criterion | NILG.AI | STX Next |
|---|---|---|
| Founded | 2018 | 2005 |
| HQ | Porto, Portugal | Poznań, Poland |
| Team size | 10–49 | 330 |
| Rating | 4.5 / 5 | 4.0 / 5 |
| Best for | Companies earlier in their AI adoption curve that want a structured discover-pilot-scale engagement model rather than a from-scratch build. | Enterprises wanting Python-native ML and AI engineering from a vendor with two decades of Python specialization and certified partnerships across all three major clouds. |
| Pricing model | Consulting engagement, pilot-to-scale retainer | Fixed project, dedicated team, staff augmentation |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, scikit-learn, Data pipelines | Python, AWS, Snowflake |
| Industries served | Public Sector, Cross-industry AI adoption | Financial Services, Manufacturing, Energy & Utilities, Healthcare, Retail/E-commerce |
NILG.AI vs STX Next: overview
NILG.AI
NILG.AI is a Porto, Portugal AI consultancy founded in 2018 by Kelwin Fernandes (PhD, Computer Science, University of Porto) and Nohelia González. It runs a structured discover-pilot-scale methodology to help businesses identify high-impact AI opportunities, validate them, and scale what works, and has assisted over 100 companies across sectors. The company was incubated at UPTEC and was awarded Data Changemaker of the Year at DSPA Insights 2024 for an AI-driven urban waste-management project in the Algarve. Its YouTube education channel has over 100,000 subscribers and NILG.AI was selected for Microsoft's 'Learn with Creators' program.
STX Next
STX Next is a Poznań, Poland software company founded in 2005, describing itself as the largest Python-focused software development company in Europe with 330 employees operating a fully remote model across the US, UK, DACH region, and Poland. It holds simultaneous AWS Advanced Tier, Snowflake, Databricks, Microsoft Azure, and Amazon Bedrock partnerships, and built and open-sourced DeepNext, an autonomous AI developer agent, serving financial services, private equity, manufacturing, oil & gas, and healthcare clients.
Services and capabilities: NILG.AI vs STX Next
| Capability | NILG.AI | STX Next |
|---|---|---|
| ML Development | ✓ | ✓ |
| AI Consulting | ✓ | ✗ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI | ✗ | ✓ |
| MLOps | ✗ | ✗ |
| Data Engineering | ✓ | ✓ |
| Staff Augmentation | ✗ | ✓ |
Tech stack comparison: NILG.AI vs STX Next
| Framework / platform | NILG.AI | STX Next |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | N/A | ✓ |
| Microsoft Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| PyTorch | N/A | N/A |
| LangChain | N/A | N/A |
| Databricks | N/A | ✓ |
Pricing comparison: NILG.AI vs STX Next
| Criterion | NILG.AI | STX Next |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Consulting retainer, Fixed-scope pilot | Fixed project, Dedicated team, Staff augmentation |
| Rate transparency | Not public | Not public |
| Price tier | Enterprise / mid-market | Enterprise / mid-market |
Target audience comparison: NILG.AI vs STX Next
| Dimension | NILG.AI | STX Next |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | Public Sector, Cross-industry AI adoption | Financial Services, Manufacturing, Energy & Utilities |
| Best use cases | AI opportunity discovery workshops, Municipal and public-sector optimization pilots | Python-native ML pipeline development, Multi-cloud MLOps using Databricks, Snowflake, and Bedrock |
| Typical project type | Consulting retainer | Fixed project |
NILG.AI vs STX Next: pros and cons
| NILG.AI | |
|---|---|
| + | Founder-level technical credibility (PhD-led, Microsoft education partner) uncommon at this company size |
| + | Structured discovery-pilot-scale methodology reduces risk for first-time AI buyers |
| + | Public recognition (Data Changemaker of the Year 2024) for a real municipal deployment |
| + | Incubated at UPTEC, giving it ties into Porto's applied-research ecosystem |
| - | 10–49 employee band limits capacity for running several large programs concurrently |
| - | Heavier emphasis on strategy and pilot work than large-scale production ML engineering compared to bigger players |
| - | Public case studies skew toward public-sector and education rather than regulated enterprise sectors |
| STX Next | |
|---|---|
| + | Largest Python-focused software company in Europe (per company website), giving deep bench strength for Python-native ML engineering |
| + | Certified across AWS Advanced Tier, Snowflake, Databricks, Azure, and Amazon Bedrock simultaneously — an unusually broad multi-cloud partner portfolio |
| + | Open-sourced its own autonomous AI dev agent (DeepNext), demonstrating in-house AI R&D beyond client work |
| + | 330 employees and a fully remote model across the US, UK, DACH, and Poland gives wide delivery flexibility |
| - | AI and ML is one part of a much broader Python software-development practice, not the company's sole specialization |
| - | 330-person scale means less boutique-style founder involvement than smaller specialists on this list |
| - | Broad industry spread from banking to oil & gas trades vertical depth for breadth |
Who should choose NILG.AI?
NILG.AI is the right choice for companies earlier in their AI adoption curve that want a structured discover-pilot-scale engagement model rather than a from-scratch build..
Founder-led by a University of Porto PhD with a public AI-education arm (100K+ YouTube subscribers, Microsoft education partner) that doubles as a technical credibility signal.. Minimum engagement starts at Not published. Works best with clients in Public Sector, Cross-industry AI adoption.
Who should choose STX Next?
STX Next is the right choice for enterprises wanting Python-native ML and AI engineering from a vendor with two decades of Python specialization and certified partnerships across all three major clouds..
Built and open-sourced DeepNext, an autonomous AI developer agent, and holds AWS Advanced Tier, Snowflake, Databricks, Azure, and Amazon Bedrock partnerships simultaneously.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Manufacturing, Energy & Utilities, Healthcare, Retail/E-commerce.
Decision matrix: NILG.AI vs STX Next
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | NILG.AI |
| You need a large dedicated team for an ongoing programme | STX Next |
| Your budget is at the lower end | Compare: NILG.AI (Not published) vs STX Next (Not published) |
| You need specialist depth in a specific vertical | STX Next |
| You need staff augmentation or team extension | STX Next |
| You need consulting before committing to a build | NILG.AI |
Use case fit: NILG.AI vs STX Next
| Use case | NILG.AI fit | STX Next fit | Winner |
|---|---|---|---|
| AI opportunity discovery workshops | Strong | Strong | Both equally |
| Municipal and public-sector optimization pilots | Strong | Limited | NILG.AI |
| Python-native ML pipeline development | Limited | Strong | STX Next |
| Multi-cloud MLOps using Databricks, Snowflake, and Bedrock | Limited | Strong | STX Next |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: NILG.AI vs STX Next
NILG.AI (4.5/5) is the stronger overall choice for most Machine Learning Development projects. Founder-led by a University of Porto PhD with a public AI-education arm (100K+ YouTube subscribers, Microsoft education partner) that doubles as a technical credibility signal.. It is best for companies earlier in their AI adoption curve that want a structured discover-pilot-scale engagement model rather than a from-scratch build..
STX Next (4.0/5) is the better choice when enterprises wanting Python-native ML and AI engineering from a vendor with two decades of Python specialization and certified partnerships across all three major clouds.. If your situation matches those criteria, STX Next is a competitive option.
Related comparisons
NILG.AI vs STX Next FAQ
Is NILG.AI better than STX Next?
NILG.AI (4.5/5) scores higher overall, but "better" depends on your use case. NILG.AI is better for companies earlier in their AI adoption curve that want a structured discover-pilot-scale engagement model rather than a from-scratch build.. STX Next is better for enterprises wanting Python-native ML and AI engineering from a vendor with two decades of Python specialization and certified partnerships across all three major clouds..
How do NILG.AI and STX Next differ in pricing?
NILG.AI uses consulting engagement, pilot-to-scale retainer pricing with a minimum engagement of Not published. STX Next uses fixed project, dedicated team, staff augmentation pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: NILG.AI or STX Next?
NILG.AI 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 NILG.AI and STX Next?
NILG.AI's primary differentiator is: founder-led by a university of porto phd with a public ai-education arm (100k+ youtube subscribers, microsoft education partner) that doubles as a technical credibility signal.. STX Next's primary differentiator is: built and open-sourced deepnext, an autonomous ai developer agent, and holds aws advanced tier, snowflake, databricks, azure, and amazon bedrock partnerships simultaneously.. They also differ in team size (10–49 vs 330), minimum engagement (Not published vs Not published), and primary industries served (Public Sector, Cross-industry AI adoption vs Financial Services, Manufacturing).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.