# Artefact vs DataSentics

> Comparing AI Consulting options: Paris vs 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/artefact-vs-datasentics
Generated: 2026-10-21 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold.

## Facts
| | Artefact | DataSentics |
|---|---|---|
| Editorial score | 74.8/100 | 74.8/100 |
| Hourly rate | not published | not published |
| Team size | 1000+ | 50-249 |
| Location | Paris, France | Prague, Czech Republic |
| Founded | — | 2016 |
| Last reviewed | 2026-08-05 | 2026-09-03 |
| Services | AI Consulting, AI Development, AI Automation, AI Agents | AI Development, AI Consulting, Generative AI |
| Industries | E-commerce, FinTech, Manufacturing | FinTech, E-commerce, Healthcare |

## Our take on Artefact
Reviewed 2026-08-05 by Gabor Kiss against published evidence.

The Bpifrance engagement is the one to read first. Artefact took agentic AI from experiment to scale across 500 employees at a public investment bank, and what came out of it was not one assistant but more than 1,500 individual agents built by the business teams themselves. That is a different claim from most agentic case studies, which describe a system rather than an adoption curve.

Carrefour is the sharper commercial example: a conversational agent that produces a complete market study for a store opening in two minutes, work that previously took months, with a 15-point improvement in revenue-prediction accuracy alongside it. VINCI Airports runs across seventy sites, Nexans has a data and AI roadmap built on Databricks, and Burger King, FDJ United and Groupe Barrière each publish their own write-up.

More than a hundred further client pages sit behind those, which is the largest published body of work in this register.

The size cuts both ways. This is a 2,500-person firm across thirty-two offices, so the team you meet is not the team you get by default—ask who staffs the engagement and where they sit.

### Key strengths
- Agentic AI evidenced at adoption scale rather than pilot scale: 500 employees, then more than 1,500 agents emerging from the business itself
- Outcome figures published on the cases that carry them—two minutes for a market study, 15 points of revenue-prediction accuracy, seventy airports
- Over a hundred client pages published, so a buyer can find work in their own sector rather than accepting an analogue

### Good to know
- 2,500 people across thirty-two offices—confirm which office delivers, who is named on the team, and how much is subcontracted
- Many of the published cases carry no numbers at all; the strong ones are strong, but the portfolio is uneven on outcomes

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

DataSentics documents five named production deployments with the stack disclosed down to the model: a LightGBM fraud-detection model live on Databricks and AWS for 2.35 million Esure customers, and an XGBoost and Elasticsearch product-matching pipeline processing tens of millions of Heureka offers a day at over 98% precision.

A Databricks-based personalization system is credited with 1,000 additional advisor meetings at Česká Spořitelna (Erste Group) in three months, and the story is co-published on Databricks' own customer-reference site, independent corroboration of the numbers.

The Seznam.cz case study goes further and documents the MLOps platform itself—feature store, MLflow model registry, CI-triggered retraining—rather than a single model, which is rarer to see published.

The weaker fit is smaller companies without an internal data-science counterpart—every documented engagement pairs DataSentics engineers with the client's own data team, and the published work assumes that counterpart exists.

### Key strengths
- Every case study lists the named engineer or lead behind the work, with a direct email and phone—Petr Dvořák, David Vopelka and Ondřej Havlíček among them.
- Databricks Elite Consulting Partner status is independent, verifiable corroboration of the platform expertise behind these case studies, not a self-reported claim.
- The Nestlé shelf-monitoring model runs at over 97% detection accuracy inside a live mobile app used by field sales reps, not a lab benchmark.

### Good to know
- Confirm which legal entity signs the contract—DataSentics now operates inside the Eviden/Bull group rather than as an independent boutique.
- Ask for a reference case outside retail, insurance and banking—documented deployments cluster tightly there, plus one internal media-platform MLOps project.
- No rate is published on site—benchmark against the European range on our rate index before assuming group-vendor pricing.

## Which to choose
Choose Artefact for:
- larger team capacity for multi-stream or enterprise-scale programs
- disclosed specialization in Manufacturing
- broader service offering — also covers AI Automation and AI Agents

Choose DataSentics for:
- closer collaboration at a smaller team scale
- disclosed specialization in Healthcare
- broader service offering — also covers Generative AI

## Questions buyers ask

### Which has more E-commerce experience, Artefact or DataSentics?
Both agencies show documented E-commerce work and have similar industry breadth. Compare directly on the agency profiles: Artefact and DataSentics.

### Which scores higher overall, Artefact or DataSentics?
Both score equally well overall (74.8/100). The deciding factor is specialization — see the editorial quotes and Strengths sections above. Full methodology.

### When should I consider both Artefact and DataSentics?
Consider running parallel discovery briefs with Artefact and DataSentics 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