# Datamole vs Geneea

> Two top-rated AI Development agencies in Prague. Side by side: published rates, team size, service and industry coverage, and the curator's assessment of both — pairings are never sold.

Canonical page: https://www.aiagencies.eu/compare/datamole-vs-geneea
Generated: 2026-09-20 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold.

## Facts
| | Datamole | Geneea |
|---|---|---|
| Editorial score | 52.8/100 | 61.8/100 |
| Hourly rate | not published | not published |
| Team size | 50-249 | 10-49 |
| Location | Prague, Czech Republic | Prague, Czech Republic |
| Founded | 2015 | 2014 |
| Last reviewed | 2026-09-20 | 2026-09-03 |
| Services | AI Development, AI Consulting, AI Automation | AI Development, AI Automation, AI Consulting |
| Industries | Manufacturing, Healthcare, SaaS & B2B | SaaS & B2B, E-commerce, FinTech |

## Our take on Datamole
Reviewed 2026-09-20 by Gabor Kiss against published evidence.

The deepest published work is all one client: Lely's milking-routine personalization calculates an optimal treatment per cow on every robot visit, fed by Datamole's IIoT platform collecting from more than 30,000 robots worldwide across 5 million daily milking sessions, and the write-up reports up to 80 percent fewer non-optimal milkings and 0.2 kg more milk per robot-minute.

The Lely Service Support App is the second full write-up and scaled from one service center to more than 200 centers and 2,000 regular users over eight years of collaboration, though it is service analytics and an app rather than a model in the loop.

Beyond those, the case index is two-sentence summaries—Agrifac sprayer telemetry, Cup&Cino device data, Thermo Fisher Scientific microscope condition monitoring—and the third full page, Calf2Cow, is a Eurostars-2 and Horizon 2020 co-funded project run with Triodor and Lely rather than a client engagement, so ask for the list behind the "100+ successful projects" and ">80% of projects deployed" figures.

The weaker fit is a buyer shopping for generative or agentic AI—nothing published describes LLM work, and the visible depth is industrial IoT, predictive models and the applications built on top of them.

### Key strengths
- Testimonials are attributed by name and title—Marc Biermann, CTO at Cup&Cino; Ondřej Krupka, Product Owner at Thermo Fisher Scientific; Rik Steenberger, Senior Product Engineer at Lely
- Engagements run long rather than one-off: the Lely service app is documented across eight years, and the about page states most customers form a multiyear collaboration
- Registered Czech entity (company number 03742709) with a named CEO and CTO who both hold technical leads, plus a Datamole AI & IoT laboratory at CTU Prague's FIT faculty

### Good to know
- Client concentration is the first thing to probe—four of the eight case-index entries are Lely; ask for two speakable references outside agriculture before shortlisting
- No rate is published on the site—ask for a day rate and the team composition behind it early, and check them against the European range on our rate index
- No case study names a model, framework or cloud stack—ask for an architecture walkthrough and for who operates and retrains the models after handover

## Our take on Geneea
Reviewed 2026-09-03 by Gabor Kiss against published evidence.

Geneea's published case studies show NLP running in production, not pilots: a personalization engine built with Recombee lifted Economia's conversion rate 64% and later expanded to the centrum.cz portal at over 50 million recommendation requests a month, and Heureka's daily-updated review summaries score 91% helpful across more than 2.8 million reviews.

The ČTK election-night generator has covered five Czech election cycles since 2020 at up to one article a second and now also writes recurring weekly fuel-price and monthly accident reports, evidence the system stayed in use well past its first deployment.

Stack detail stops at the product layer—Geneea names its own NLP engine, aspect-based sentiment analysis and, in newer offerings, RAG and LLMs, but not specific model providers or infrastructure, so ask for that detail directly if it matters to your evaluation.

The weaker fit is buyers outside media, banking and e-commerce who need a narrow single-language project—every documented client here runs a high-volume, multi-market content or feedback operation.

### Key strengths
- Official technology-partner status with Stibo DX since 2025 puts Geneea's semantic tagging and RAG research assistant inside a live enterprise publishing platform (CUE), not a standalone tool.
- Hello bank!, a BNP Paribas digital bank serving 350,000 clients, credits the deployment with faster daily feedback triage and names its internal owner on record.
- Co-founders present original work at industry venues (WAN-IFRA AI Forum, FIBEP Tech Day) rather than marketing content alone.

### Good to know
- Ask for the specific model or provider behind the 'RAG' and 'LLM' claims in newer products—published case studies name techniques, not model vendors or infrastructure.
- Radio France's location-mapping project grew out of a four-month 'Sandbox' program—confirm it is still running before citing it as an ongoing deployment.
- No published rates are visible on site—ask Geneea to benchmark against the European range on our rate index.

## Which to choose
Choose Datamole for:
- larger team capacity for multi-stream or enterprise-scale programs
- disclosed specialization in Manufacturing / Healthcare

Choose Geneea for:
- closer collaboration at a smaller team scale
- disclosed specialization in E-commerce / FinTech
- a higher overall editorial score

## Questions buyers ask

### Which has more SaaS & B2B experience, Datamole or Geneea?
Both agencies show documented SaaS & B2B work and have similar industry breadth. Compare directly on the agency profiles: Datamole and Geneea.

### Which scores higher overall, Datamole or Geneea?
Geneea scores 61.8/100, 9 points higher than Datamole at 52.8/100. See our methodology for how scores are calculated.

### Which is faster to engage, Datamole or Geneea?
Neither publishes lead times, so this is a read on team size rather than a measured answer. Geneea runs the smaller team, which usually means fewer procurement gates and a shorter path to kickoff. Datamole runs a larger one, which tends to mean more steps but more capacity to start parallel workstreams. Current kickoff availability is the number that actually decides it — ask both.

### When should I consider both Datamole and Geneea?
Consider running parallel discovery briefs with Datamole and Geneea 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.

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Source: AIAgencies.eu — the curated register of European AI agencies. Rate provenance: "agency-confirmed" = disclosed via submission or claimed profile; "directory-listed" = Clutch or two agreeing B2B directories (lone unverified sources are never written). Full method: https://www.aiagencies.eu/methodology · Rate index: https://www.aiagencies.eu/rates