Addepto vs Deviniti: full comparison for 2026
Last updated: July 2026
Quick verdict
Addepto (4.4/5) edges ahead of Deviniti (4.0/5) overall. Addepto is the better choice for mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline.. 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.
Addepto vs Deviniti: head-to-head summary
| Criterion | Addepto | Deviniti |
|---|---|---|
| Founded | 2017 | 2004 |
| HQ | Warsaw, Poland | Wrocław, Poland |
| Team size | 50–249 | 300+ |
| Rating | 4.4 / 5 | 4.0 / 5 |
| Best for | Mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline. | 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 | Fixed project, Time & Materials | Fixed project, staff augmentation |
| Min. engagement | $10,000+ | Not published |
| Primary tech stack | Python, MLOps pipelines, AWS | Python, LLM fine-tuning tooling, RAG architectures |
| Industries served | Aviation, Manufacturing, Automotive, Financial Services, Retail/E-commerce, Logistics | Financial Institutions, Regulated enterprise IT |
Addepto vs Deviniti: overview
Addepto
Addepto is a Warsaw, Poland AI consultancy founded in 2017 that explicitly positions its value around production-grade delivery — moving clients from proof-of-concept to production — rather than research exploration. It covers AI consulting, generative AI development, data engineering, MLOps, document processing, and computer vision, serving aviation, manufacturing, automotive, finance, retail, healthcare, and logistics clients. Addepto is a GoodFirms top-rated firm for Big Data and Business Intelligence services, with a 50–249 employee band per Clutch.
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: Addepto vs Deviniti
| Capability | Addepto | Deviniti |
|---|---|---|
| ML Development | ✓ | ✓ |
| AI Consulting | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI | ✗ | ✓ |
| MLOps | ✓ | ✗ |
| Data Engineering | ✓ | ✗ |
| Staff Augmentation | ✗ | ✓ |
Tech stack comparison: Addepto vs Deviniti
| Framework / platform | Addepto | Deviniti |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | N/A |
| Microsoft Azure | N/A | N/A |
| Google Cloud | ✓ | N/A |
| Kubernetes | N/A | N/A |
| PyTorch | N/A | N/A |
| LangChain | N/A | N/A |
| Databricks | N/A | N/A |
Pricing comparison: Addepto vs Deviniti
| Criterion | Addepto | Deviniti |
|---|---|---|
| Minimum engagement | $10,000+ | Not published |
| Engagement models | Fixed project, Time & Materials, Dedicated team | Fixed project, Staff augmentation, Dedicated team |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Accessible | Enterprise / mid-market |
Target audience comparison: Addepto vs Deviniti
| Dimension | Addepto | Deviniti |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | Aviation, Manufacturing, Automotive | Financial Institutions, Regulated enterprise IT |
| Best use cases | Computer vision for document processing, MLOps pipeline hardening for existing proof-of-concepts | Self-hosted LLM and RAG system development, AI chatbot and knowledge-base solutions for enterprises |
| Typical project type | Fixed project | Fixed project |
Addepto vs Deviniti: pros and cons
| Addepto | |
|---|---|
| + | Broad industry coverage from aviation to legal shows delivery flexibility beyond a single vertical |
| + | Explicit MLOps and production focus addresses the common 'stuck in proof-of-concept' failure mode |
| + | $10K entry point is accessible for a mid-market pilot engagement |
| + | GoodFirms top-rated recognition for Big Data and Business Intelligence services |
| - | Broad industry spread can mean less depth in any single regulated vertical than a specialist boutique |
| - | Exact team size within the 50–249 Clutch band is not broken out by function |
| - | Public case studies are largely testimonial-based rather than published with hard metrics |
| 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 Addepto?
Addepto is the right choice for mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline..
Explicit 'proof-of-concept to production' positioning addresses the common failure mode where enterprise ML pilots never reach deployment.. Minimum engagement starts at $10,000+. Works best with clients in Aviation, Manufacturing, Automotive, Financial Services, Retail/E-commerce, Logistics.
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: Addepto vs Deviniti
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Addepto |
| You need a large dedicated team for an ongoing programme | Addepto |
| Your budget is at the lower end | Compare: Addepto ($10,000+) vs Deviniti (Not published) |
| You need specialist depth in a specific vertical | Addepto |
| You need staff augmentation or team extension | Deviniti |
| You need consulting before committing to a build | Addepto |
Use case fit: Addepto vs Deviniti
| Use case | Addepto fit | Deviniti fit | Winner |
|---|---|---|---|
| Computer vision for document processing | Strong | Limited | Addepto |
| MLOps pipeline hardening for existing proof-of-concepts | Strong | Limited | Addepto |
| 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: Addepto vs Deviniti
Addepto (4.4/5) is the stronger overall choice for most Machine Learning Development projects. Explicit 'proof-of-concept to production' positioning addresses the common failure mode where enterprise ML pilots never reach deployment.. It is best for mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline..
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
Addepto vs Deviniti FAQ
Is Addepto better than Deviniti?
Addepto (4.4/5) scores higher overall, but "better" depends on your use case. Addepto is better for mid-market to enterprise buyers in aviation, logistics, or finance that already have a proof-of-concept and need it hardened into a production MLOps pipeline.. 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 Addepto and Deviniti differ in pricing?
Addepto uses fixed project, time & materials pricing with a minimum engagement of $10,000+. 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: Addepto or Deviniti?
Addepto 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 Addepto and Deviniti?
Addepto's primary differentiator is: explicit 'proof-of-concept to production' positioning addresses the common failure mode where enterprise ml pilots never reach deployment.. 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 (50–249 vs 300+), minimum engagement ($10,000+ vs Not published), and primary industries served (Aviation, Manufacturing vs Financial Institutions, Regulated enterprise IT).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.