NILG.AI vs Deviniti: full comparison for 2026
Last updated: July 2026
Quick verdict
NILG.AI (4.5/5) edges ahead of Deviniti (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.. Deviniti is the stronger option for enterprises in regulated or complex sectors wanting generative AI, RAG, and LLM work delivered by a vendor with deep enterprise-software (Atlassian ecosystem) roots.. The right choice depends on your project size, budget, and required tech stack.
NILG.AI vs Deviniti: head-to-head summary
| Criterion | NILG.AI | Deviniti |
|---|---|---|
| Founded | 2018 | 2004 |
| HQ | Porto, Portugal | Wrocław, Poland |
| Team size | 10–49 | 300+ |
| 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 in regulated or complex sectors wanting generative AI, RAG, and LLM work delivered by a vendor with deep enterprise-software (Atlassian ecosystem) roots. |
| Pricing model | Consulting engagement, pilot-to-scale retainer | Fixed project, staff augmentation |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, scikit-learn, Data pipelines | Python, LLM fine-tuning tooling, RAG architectures |
| Industries served | Public Sector, Cross-industry AI adoption | Financial Institutions, Regulated enterprise IT |
NILG.AI vs Deviniti: 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.
Deviniti
Deviniti is a Wrocław, Poland software house founded in 2004, with 300+ specialists serving over 15,000 clients across 38 countries (per company website). It holds 50+ Atlassian-certified professionals and was a 2024–2025 Atlassian Partner of the Year finalist for Emerging Markets, and has more recently built out generative AI, custom AI agent, self-hosted LLM, LLM fine-tuning, and RAG architecture capabilities, including contributions to the open-source Bielik.AI project.
Services and capabilities: NILG.AI vs Deviniti
| Capability | NILG.AI | Deviniti |
|---|---|---|
| ML Development | ✓ | ✓ |
| AI Consulting | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI | ✗ | ✓ |
| MLOps | ✗ | ✗ |
| Data Engineering | ✓ | ✗ |
| Staff Augmentation | ✗ | ✓ |
Tech stack comparison: NILG.AI vs Deviniti
| Framework / platform | NILG.AI | Deviniti |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | N/A | N/A |
| Microsoft Azure | N/A | 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 | N/A |
Pricing comparison: NILG.AI vs Deviniti
| Criterion | NILG.AI | Deviniti |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Consulting retainer, Fixed-scope pilot | Fixed project, Staff augmentation, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Enterprise / mid-market | Enterprise / mid-market |
Target audience comparison: NILG.AI vs Deviniti
| Dimension | NILG.AI | Deviniti |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | Public Sector, Cross-industry AI adoption | Financial Institutions, Regulated enterprise IT |
| Best use cases | AI opportunity discovery workshops, Municipal and public-sector optimization pilots | Self-hosted LLM and RAG system development, AI chatbot and knowledge-base solutions for enterprises |
| Typical project type | Consulting retainer | Fixed project |
NILG.AI vs Deviniti: 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 |
| Deviniti | |
|---|---|
| + | 300+ specialists and 15,000+ clients across 38 countries show significant delivery scale (per company website) |
| + | Contributions to the open-source Bielik.AI project demonstrate genuine LLM/NLP engineering, not just integration work |
| + | Deep Atlassian-ecosystem expertise is a strong complementary asset for enterprise clients running Jira/Confluence-based workflows |
| + | Founded 2004 — two decades of enterprise software delivery experience |
| - | Generative AI and RAG practice is newer than its core Atlassian and enterprise-software business, so ML-specific track record is shorter than the overall company history suggests |
| - | 300+ specialists are split across Atlassian consulting and AI/software delivery, so dedicated AI headcount is unclear |
| - | 15,000+ client claim is per company marketing and not independently broken down by service line |
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 Deviniti?
Deviniti is the right choice for enterprises in regulated or complex sectors wanting generative AI, RAG, and LLM work delivered by a vendor with deep enterprise-software (Atlassian ecosystem) roots..
50+ Atlassian-certified professionals and Atlassian Partner of the Year finalist status give it unusually strong enterprise-IT integration credibility alongside its generative AI practice and Bielik.AI open-source contributions.. Minimum engagement starts at Not published. Works best with clients in Financial Institutions, Regulated enterprise IT.
Decision matrix: NILG.AI vs Deviniti
| 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 | Deviniti |
| Your budget is at the lower end | Compare: NILG.AI (Not published) vs Deviniti (Not published) |
| You need specialist depth in a specific vertical | NILG.AI |
| You need staff augmentation or team extension | Deviniti |
| You need consulting before committing to a build | NILG.AI |
Use case fit: NILG.AI vs Deviniti
| Use case | NILG.AI fit | Deviniti fit | Winner |
|---|---|---|---|
| AI opportunity discovery workshops | Strong | Strong | Both equally |
| Municipal and public-sector optimization pilots | Strong | Limited | NILG.AI |
| Self-hosted LLM and RAG system development | Limited | Strong | Deviniti |
| AI chatbot and knowledge-base solutions for enterprises | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: NILG.AI vs Deviniti
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..
Deviniti (4.0/5) is the better choice when enterprises in regulated or complex sectors wanting generative AI, RAG, and LLM work delivered by a vendor with deep enterprise-software (Atlassian ecosystem) roots.. If your situation matches those criteria, Deviniti is a competitive option.
Related comparisons
NILG.AI vs Deviniti FAQ
Is NILG.AI better than Deviniti?
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.. Deviniti is better for enterprises in regulated or complex sectors wanting generative AI, RAG, and LLM work delivered by a vendor with deep enterprise-software (Atlassian ecosystem) roots..
How do NILG.AI and Deviniti differ in pricing?
NILG.AI uses consulting engagement, pilot-to-scale retainer pricing with a minimum engagement of Not published. Deviniti uses fixed project, 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 Deviniti?
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 Deviniti?
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.. Deviniti's primary differentiator is: 50+ atlassian-certified professionals and atlassian partner of the year finalist status give it unusually strong enterprise-it integration credibility alongside its generative ai practice and bielik.ai open-source contributions.. They also differ in team size (10–49 vs 300+), minimum engagement (Not published vs Not published), and primary industries served (Public Sector, Cross-industry AI adoption vs Financial Institutions, Regulated enterprise IT).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.