Best Machine Learning Development Companies in Europe

Neoteric vs Plain Concepts: full comparison for 2026

Last updated: July 2026

Quick verdict

Neoteric (4.3/5) edges ahead of Plain Concepts (3.9/5) overall. Neoteric is the better choice for mid-market companies wanting to move a generative AI proof-of-concept into a production-grade product. Plain Concepts is the stronger option for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery. The right choice depends on your project size, budget, and required tech stack.

Neoteric vs Plain Concepts: head-to-head summary

Criterion Neoteric Plain Concepts
Founded 2005 2006
HQ Gdansk, Poland Madrid, Spain
Team size 51–200 201–500
Rating 4.3 / 5 3.9 / 5
Best for Mid-market companies wanting to move a generative AI proof-of-concept into a production-grade product Enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery
Pricing model Fixed project, dedicated team Dedicated team, fixed project, retainer
Min. engagement $20K $35K
Primary tech stack Python, OpenAI API, LangChain Python, Azure ML, Azure OpenAI Service
Industries served SaaS, Fintech, Healthcare, Enterprise Enterprise, Retail, Healthcare, Financial Services

Neoteric vs Plain Concepts: overview

Neoteric

Neoteric was founded in 2005 and is headquartered in Gdansk, Poland, with an additional office in New York. The midsize company specializes in generative AI, AI consulting, and custom software development, helping clients move from AI proof-of-concept to production deployment.

Plain Concepts

Plain Concepts, founded in 2006 and headquartered in Madrid, Spain, is a 450-plus person technology consultancy with offices across the USA, UK, Spain, Germany, the Netherlands, and Romania. As a Microsoft Gold Partner, Microsoft AI Partner, and 2016 Microsoft Partner of the Year, Plain Concepts brings deep Azure-native AI and machine learning delivery experience alongside mixed reality and IoT engineering.

Services and capabilities: Neoteric vs Plain Concepts

Capability Neoteric Plain Concepts
ML model development
Computer vision
NLP
Generative AI / LLM integration
MLOps
AI strategy consulting
Staff augmentation

Tech stack comparison: Neoteric vs Plain Concepts

Framework / platform Neoteric Plain Concepts
Python
TensorFlow N/A N/A
PyTorch N/A N/A
AWS N/A
Azure
Kubernetes N/A

Pricing comparison: Neoteric vs Plain Concepts

Criterion Neoteric Plain Concepts
Minimum engagement $20K $35K
Engagement models Fixed project, Dedicated team Dedicated team, Fixed project, Retainer
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: Neoteric vs Plain Concepts

Dimension Neoteric Plain Concepts
Best company size Startup to mid-market Startup to mid-market
Best industries SaaS, Fintech, Healthcare Enterprise, Retail, Healthcare
Best use cases Taking a generative AI proof-of-concept to production, LLM integration into an existing SaaS product Azure-native ML model deployment for an enterprise client, Mixed reality plus AI product development
Typical project type Fixed project Dedicated team

Neoteric vs Plain Concepts: pros and cons

Neoteric
+ Two decades of operating history since founding in 2005 as a Polish software consultancy
+ Dedicated generative AI practice, not a bolted-on service line
+ New York office provides closer coverage for US-based clients
+ Track record spanning both custom software delivery and AI-specific projects
- Broader custom-software heritage means ML and AI is one of several practice areas
- Mid-size team may have longer ramp time for highly specialized ML research work
Plain Concepts
+ Two decades of operating history since founding in 2006, with Microsoft Gold and AI Partner status
+ Multi-country office footprint across Spain, the UK, Germany, the Netherlands, Romania, and the US for broad coverage
+ Deep Azure-native ML and AI delivery credentials, useful for Microsoft-standardized enterprises
+ Recognized with Microsoft Partner of the Year award in 2016
- Azure-centric specialization may be less ideal for clients standardized on AWS or GCP
- Broader technology consultancy scope, including mixed reality and IoT, means ML is one of several core practices
- Larger enterprise-oriented engagement sizes, less accessible for very small startup budgets

Who should choose Neoteric?

Neoteric is the right choice for mid-market companies wanting to move a generative AI proof-of-concept into a production-grade product.

Two-decade-old Polish software house with a dedicated generative AI practice and a US-facing New York office. Minimum engagement starts at $20K. Works best with clients in SaaS, Fintech, Healthcare, Enterprise.

Who should choose Plain Concepts?

Plain Concepts is the right choice for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery.

Deep Azure-native AI and ML delivery credentials as a Microsoft Gold and AI Partner, plus mixed reality expertise. Minimum engagement starts at $35K. Works best with clients in Enterprise, Retail, Healthcare, Financial Services.

Decision matrix: Neoteric vs Plain Concepts

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

Use case fit: Neoteric vs Plain Concepts

Use case Neoteric fit Plain Concepts fit Winner
Taking a generative AI proof-of-concept to production Strong Limited Neoteric
LLM integration into an existing SaaS product Strong Limited Neoteric
Azure-native ML model deployment for an enterprise client Limited Strong Plain Concepts
Mixed reality plus AI product development Limited Strong Plain Concepts
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: Neoteric vs Plain Concepts

Neoteric (4.3/5) is the stronger overall choice for most Machine Learning Development projects. Two-decade-old Polish software house with a dedicated generative AI practice and a US-facing New York office. It is best for mid-market companies wanting to move a generative AI proof-of-concept into a production-grade product.

Plain Concepts (3.9/5) is the better choice when enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery. If your situation matches those criteria, Plain Concepts is a competitive option.

Related comparisons

Neoteric vs Plain Concepts FAQ

Is Neoteric better than Plain Concepts?

Neoteric (4.3/5) scores higher overall, but "better" depends on your use case. Neoteric is better for mid-market companies wanting to move a generative AI proof-of-concept into a production-grade product. Plain Concepts is better for enterprises standardized on Microsoft Azure wanting a certified Microsoft AI Partner for ML delivery.

How do Neoteric and Plain Concepts differ in pricing?

Neoteric uses fixed project, dedicated team pricing with a minimum engagement of $20K. Plain Concepts uses dedicated team, fixed project, retainer pricing with a minimum engagement of $35K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Neoteric or Plain Concepts?

Plain Concepts 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 Neoteric and Plain Concepts?

Neoteric's primary differentiator is: two-decade-old polish software house with a dedicated generative ai practice and a us-facing new york office. Plain Concepts's primary differentiator is: deep azure-native ai and ml delivery credentials as a microsoft gold and ai partner, plus mixed reality expertise. They also differ in team size (51–200 vs 201–500), minimum engagement ($20K vs $35K), and primary industries served (SaaS, Fintech vs Enterprise, Retail).

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