Top Machine Learning Development Services in Europe

Deviniti vs STX Next: full comparison for 2026

Last updated: July 2026

Quick verdict

Deviniti (4.0/5) edges ahead of STX Next (4.0/5) overall. Deviniti is the better 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.. 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.

Deviniti vs STX Next: head-to-head summary

Criterion Deviniti STX Next
Founded 2004 2005
HQ Wrocław, Poland Poznań, Poland
Team size 300+ 330
Rating 4.0 / 5 4.0 / 5
Best 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. 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 Fixed project, staff augmentation Fixed project, dedicated team, staff augmentation
Min. engagement Not published Not published
Primary tech stack Python, LLM fine-tuning tooling, RAG architectures Python, AWS, Snowflake
Industries served Financial Institutions, Regulated enterprise IT Financial Services, Manufacturing, Energy & Utilities, Healthcare, Retail/E-commerce

Deviniti vs STX Next: overview

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.

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: Deviniti vs STX Next

Capability Deviniti STX Next
ML Development
AI Consulting
Computer Vision
NLP
Generative AI
MLOps
Data Engineering
Staff Augmentation

Tech stack comparison: Deviniti vs STX Next

Framework / platform Deviniti 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: Deviniti vs STX Next

Criterion Deviniti STX Next
Minimum engagement Not published Not published
Engagement models Fixed project, Staff augmentation, Dedicated team Fixed project, Dedicated team, Staff augmentation
Rate transparency Not public Not public
Price tier Enterprise / mid-market Enterprise / mid-market

Target audience comparison: Deviniti vs STX Next

Dimension Deviniti STX Next
Best company size Mid-market to enterprise Mid-market to enterprise
Best industries Financial Institutions, Regulated enterprise IT Financial Services, Manufacturing, Energy & Utilities
Best use cases Self-hosted LLM and RAG system development, AI chatbot and knowledge-base solutions for enterprises Python-native ML pipeline development, Multi-cloud MLOps using Databricks, Snowflake, and Bedrock
Typical project type Fixed project Fixed project

Deviniti vs STX Next: pros and cons

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
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 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.

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: Deviniti vs STX Next

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Deviniti
You need a large dedicated team for an ongoing programme Deviniti
Your budget is at the lower end Compare: Deviniti (Not published) vs STX Next (Not published)
You need specialist depth in a specific vertical STX Next
You need staff augmentation or team extension Deviniti
You need consulting before committing to a build Deviniti

Use case fit: Deviniti vs STX Next

Use case Deviniti fit STX Next fit Winner
Self-hosted LLM and RAG system development Strong Limited Deviniti
AI chatbot and knowledge-base solutions for enterprises Strong Strong Both equally
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: Deviniti vs STX Next

Deviniti (4.0/5) is the stronger overall choice for most Machine Learning Development projects. 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.. It is best 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..

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

Deviniti vs STX Next FAQ

Is Deviniti better than STX Next?

Deviniti (4.0/5) scores higher overall, but "better" depends on your use case. 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.. 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 Deviniti and STX Next differ in pricing?

Deviniti uses fixed project, staff augmentation 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: Deviniti 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 Deviniti and STX Next?

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.. 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 (300+ vs 330), minimum engagement (Not published vs Not published), and primary industries served (Financial Institutions, Regulated enterprise IT vs Financial Services, Manufacturing).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.