Agency Comparison
Plain Concepts vs QUANT AI Lab
Two top-rated AI Consulting agencies in Madrid.
Comparison updated · Newest review
Side by side
Published data on both agencies. Where one side measurably differs, the dot marks it: the higher score, the lower published rate, the larger team, the more recent review. Which of those is an advantage depends on your brief.
| Attribute | Plain Concepts | QUANT AI Lab |
|---|---|---|
| Editorial score | Higher score: 68/100 | 61.8/100 |
| Hourly rate | €85-130/hr | Contact for rates |
| Team size | Larger team: 250+ | 50-249 |
| Location | Madrid, Spain | Madrid, Spain |
| Founded | 2006 | 2019 |
| Last reviewed | More recent review: Sep 7, 2026 | Aug 5, 2026 |
What we said about each
Our take on Plain Concepts
The AI portfolio is named, dated and Azure-deep: ALEX writes cataract discharge reports for the Ribera healthcare group on Azure OpenAI and Azure AI Search with dynamic few-shot retrieval, validated at 96% of reports needing no physician correction, with the head of ophthalmology quoted by name. AENOR's standards search pairs a machine-learning search engine with an assistant over 50,000 published certifications, Thera4All's Brain runs Azure OpenAI inside Plain Concepts' own Evergine engine…
Reviewed Sep 7, 2026
Read the full assessment →Our take on QUANT AI Lab
Twenty-eight published use cases, and what makes them worth reading is that each one names its stack. Fraud detection on Databricks, Neo4j and Snowflake. A destination recommender for airline revenue built with SageMaker, Hugging Face, TensorFlow and Airflow.
Reviewed Aug 5, 2026
Read the full assessment →Best for
Where each agency measurably leads on the published data — team capacity, declared specializations, editorial scoring, and rates where both publish them. Use these to match an agency to your project priorities.
Choose Plain Concepts if you need
- larger team capacity for multi-stream or enterprise-scale programs
- disclosed specialization in Healthcare
- broader service offering — also covers Generative AI
- a higher overall editorial score
Choose QUANT AI Lab if you need
- closer collaboration at a smaller team scale
- disclosed specialization in E-commerce
- broader service offering — also covers AI Automation
Strengths and watch-outs
Both upsides and risks, straight from our editorial assessments.
Plain Concepts
Strengths
- Four named-client AI systems published with the stack named, including a healthcare deployment validated at 96% of generated reports requiring no physician correction
- Own graphics engine (Evergine) and a Microsoft relationship deep enough that Nestlé's 700-expert Global IT Hub uses them across security, MLOps and generative AI
- More than 700 employees published, so a multi-workstream program is staffable without subcontracting
Watch-outs
- Most case studies close on qualitative bullets rather than measured outcomes—ask for the metric that moved on the engagement closest to yours
- Nearly all published work is Azure-native; if you run on AWS or GCP, ask for a delivered system on your stack
- At €85–130/h they price above most of the Spanish market—scope tightly, since published projects range from multi-year programs to single features
QUANT AI Lab
Strengths
- Twenty-eight use cases each naming its technology stack, which lets an engineering buyer assess the team before the first call
- Genuine quantitative depth—Bayesian networks, hierarchical models, optimization—rather than an LLM-only practice
- A registered Spanish company with a named executive team and offices in Madrid, Paris, Bordeaux and London
Watch-outs
- Every use case is anonymized and the four bank logos attach to none of them—ask which client corresponds to which build
- No outcome figures anywhere; the catalog proves capability and says nothing about impact
Service coverage
Where the two overlap, and where each covers ground the other does not.
Industry coverage
Where the two overlap, and where each covers ground the other does not.
Pricing math
What a 12-week engagement at one full-time equivalent (~480 hours) costs at each agency’s published rate. An arithmetic projection, not a quote — real scopes move with seniority mix and team shape.
Plain Concepts
Rate: €85-130/hr
€40,800–€62,400
QUANT AI Lab
Contact for rates
Only Plain Concepts publishes a rate, so there is no gap to measure. QUANT AI Lab quotes per engagement — ask for a rate card early, since a comparison that starts on scope and ends on price tends to end late.
Frequently asked questions
- Which has more FinTech experience, Plain Concepts or QUANT AI Lab?
- Both agencies show documented FinTech work and have similar industry breadth. Compare directly on the agency profiles: Plain Concepts and QUANT AI Lab.
- Which scores higher overall, Plain Concepts or QUANT AI Lab?
- Plain Concepts scores 68/100, 6.2 points higher than QUANT AI Lab at 61.8/100. Both portfolio quality and business credibility feed into the score — see our methodology for the full breakdown.
- When should I consider both Plain Concepts and QUANT AI Lab?
- Consider running parallel discovery briefs with Plain Concepts and QUANT AI Lab if your project spans multiple workstreams, you want competitive proposals to compare scope and approach, or you're undecided between the specialization angles each brings (see the Best for cards above). Most engagements ultimately go with one — but the parallel-brief phase is a low-cost way to validate fit.
Read the full reviews
A side-by-side is a starting point. The full assessments carry the portfolio analysis, documented engagements, and the evidence behind every strength and watch-out above.