Best Machine Learning Development Companies in Europe

DATAFOREST vs Gemmo: full comparison for 2026

Last updated: July 2026

Quick verdict

DATAFOREST (4.1/5) edges ahead of Gemmo (4.0/5) overall. DATAFOREST is the better choice for small and mid-market businesses needing data engineering plus ML analytics as a combined offering. Gemmo is the stronger option for companies wanting a structured, staged AI engagement, from opportunity discovery through implementation and optimization. The right choice depends on your project size, budget, and required tech stack.

DATAFOREST vs Gemmo: head-to-head summary

Criterion DATAFOREST Gemmo
Founded 2018 2014
HQ Kyiv, Ukraine Dublin, Ireland (AI Lab in Milan, Italy)
Team size 51–200 11–50
Rating 4.1 / 5 4.0 / 5
Best for Small and mid-market businesses needing data engineering plus ML analytics as a combined offering Companies wanting a structured, staged AI engagement, from opportunity discovery through implementation and optimization
Pricing model Fixed project, dedicated team Fixed-price discovery engagement, dedicated team
Min. engagement $15K $15K
Primary tech stack Python, Airflow, AWS Python, Scikit-learn, AWS
Industries served E-commerce, SaaS, Fintech, Healthcare Sustainability, Manufacturing, Enterprise, Public Sector

DATAFOREST vs Gemmo: overview

DATAFOREST

DATAFOREST is a data science and software development agency founded in 2018, headquartered in Kyiv, Ukraine, with an additional office in New York. The company, with an estimated 50 to 249 employees, provides ETL pipelines, data analytics, and custom machine learning solutions, and has been recognized by The Manifest as a top-reviewed IT agency in Ukraine, per company website; independently unverifiable.

Gemmo

Gemmo AI, founded in 2014 by Dr Luca Marchesotti and headquartered in Dublin, Ireland, is a boutique AI firm with an additional AI Lab in Milan, Italy. Gemmo blends strategic AI consulting with hands-on technical implementation through a structured engagement model: AI Pathfinder for opportunity discovery, followed by AI Implementation and AI Optimization phases. The firm won Best Application of AI in Sustainability at the 2023 AI Awards for a noise-source-identification API, per company website; independently unverifiable.

Services and capabilities: DATAFOREST vs Gemmo

Capability DATAFOREST Gemmo
ML model development
Computer vision
NLP
Generative AI / LLM integration
MLOps
AI strategy consulting
Staff augmentation

Tech stack comparison: DATAFOREST vs Gemmo

Framework / platform DATAFOREST Gemmo
Python
TensorFlow N/A N/A
PyTorch N/A N/A
AWS
Azure N/A
Kubernetes N/A N/A

Pricing comparison: DATAFOREST vs Gemmo

Criterion DATAFOREST Gemmo
Minimum engagement $15K $15K
Engagement models Fixed project, Dedicated team Fixed project, Dedicated team
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: DATAFOREST vs Gemmo

Dimension DATAFOREST Gemmo
Best company size Startup to mid-market Startup to mid-market
Best industries E-commerce, SaaS, Fintech Sustainability, Manufacturing, Enterprise
Best use cases Building ETL pipelines feeding a downstream ML model, Predictive analytics for e-commerce customer behavior Structured AI opportunity discovery for a company new to AI adoption, Sustainability-focused AI applications such as noise or environmental monitoring
Typical project type Fixed project Fixed project

DATAFOREST vs Gemmo: pros and cons

DATAFOREST
+ Combines core data engineering (ETL and pipelines) with ML analytics under one team
+ Growing review base and recognition from The Manifest as a top-reviewed Ukraine IT agency
+ Competitive pricing relative to Western European ML firms
+ New York office adds coverage for US-based clients
- Kyiv, Ukraine-based delivery carries the same operational-continuity considerations as other Ukraine-linked firms
- Founded in 2018, a shorter track record than more established European ML consultancies
- Data engineering heritage means the ML practice is comparatively newer within the firm
Gemmo
+ Structured, staged engagement model reduces risk of open-ended AI consulting scope creep
+ Dual Dublin and Milan presence gives coverage across two distinct European markets
+ Award recognition for a real-world sustainability application at the 2023 AI Awards, per company website
+ Founder-led boutique structure keeps senior AI expertise close to client engagements
- Small team size of 11 to 50 limits capacity for large, multi-workstream enterprise programmes
- Founded in 2014 with a public track record still smaller than more established European AI consultancies
- Award and case-study claims are self-reported and not independently verifiable

Who should choose DATAFOREST?

DATAFOREST is the right choice for small and mid-market businesses needing data engineering plus ML analytics as a combined offering.

Combined data engineering (ETL) and ML analytics practice with a growing review base. Minimum engagement starts at $15K. Works best with clients in E-commerce, SaaS, Fintech, Healthcare.

Who should choose Gemmo?

Gemmo is the right choice for companies wanting a structured, staged AI engagement, from opportunity discovery through implementation and optimization.

Structured three-phase engagement model of Pathfinder, Implementation, and Optimization, rather than an open-ended consulting retainer. Minimum engagement starts at $15K. Works best with clients in Sustainability, Manufacturing, Enterprise, Public Sector.

Decision matrix: DATAFOREST vs Gemmo

Your situation Recommended choice
You need full-ownership delivery on a defined project scope DATAFOREST
You need a large dedicated team for an ongoing programme DATAFOREST
Your budget is at the lower end DATAFOREST
You need specialist depth in a specific vertical DATAFOREST
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build DATAFOREST

Use case fit: DATAFOREST vs Gemmo

Use case DATAFOREST fit Gemmo fit Winner
Building ETL pipelines feeding a downstream ML model Strong Limited DATAFOREST
Predictive analytics for e-commerce customer behavior Strong Limited DATAFOREST
Structured AI opportunity discovery for a company new to AI adoption Limited Strong Gemmo
Sustainability-focused AI applications such as noise or environmental monitoring Limited Strong Gemmo
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: DATAFOREST vs Gemmo

DATAFOREST (4.1/5) is the stronger overall choice for most Machine Learning Development projects. Combined data engineering (ETL) and ML analytics practice with a growing review base. It is best for small and mid-market businesses needing data engineering plus ML analytics as a combined offering.

Gemmo (4.0/5) is the better choice when companies wanting a structured, staged AI engagement, from opportunity discovery through implementation and optimization. If your situation matches those criteria, Gemmo is a competitive option.

Related comparisons

DATAFOREST vs Gemmo FAQ

Is DATAFOREST better than Gemmo?

DATAFOREST (4.1/5) scores higher overall, but "better" depends on your use case. DATAFOREST is better for small and mid-market businesses needing data engineering plus ML analytics as a combined offering. Gemmo is better for companies wanting a structured, staged AI engagement, from opportunity discovery through implementation and optimization.

How do DATAFOREST and Gemmo differ in pricing?

DATAFOREST uses fixed project, dedicated team pricing with a minimum engagement of $15K. Gemmo uses fixed-price discovery engagement, dedicated team pricing with a minimum engagement of $15K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: DATAFOREST or Gemmo?

DATAFOREST 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 DATAFOREST and Gemmo?

DATAFOREST's primary differentiator is: combined data engineering (etl) and ml analytics practice with a growing review base. Gemmo's primary differentiator is: structured three-phase engagement model of pathfinder, implementation, and optimization, rather than an open-ended consulting retainer. They also differ in team size (51–200 vs 11–50), minimum engagement ($15K vs $15K), and primary industries served (E-commerce, SaaS vs Sustainability, Manufacturing).

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