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 | Artefact | Datatonic |
|---|---|---|
| Editorial score | 74.8/100 | 74.8/100 |
| Hourly rate | Contact for rates | Contact for rates |
| Team size | Larger team: 1000+ | 50-249 |
| Location | Paris, France | London, United Kingdom |
| Founded | — | 2013 |
| Last reviewed | Aug 5, 2026 | More recent review: Sep 7, 2026 |
What we said about each
Our take on Artefact
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.
Reviewed Aug 5, 2026
Read the full assessment →Our take on Datatonic
The architecture detail is unusually specific for a consultancy site. The AstraZeneca engagement documents a Bedrock RAG pipeline that ingested more than 20,000 scientific documents and 1. 5 billion input tokens, with a custom batch-sync engine written to get around a 1,000-document platform ceiling.
Reviewed Sep 7, 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 Artefact if you need
- 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 Datatonic if you need
- closer collaboration at a smaller team scale
- disclosed specialization in Healthcare
- broader service offering — also covers Generative AI
Strengths and watch-outs
Both upsides and risks, straight from our editorial assessments.
Artefact
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
Watch-outs
- 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
Datatonic
Strengths
- The AstraZeneca RAG pipeline is documented at 20,000+ documents and 1.5 billion input tokens with the architecture published in full
- Vodafone AI Booster runs in more than eight markets and cut proof-of-concept-to-production by about 80%; its MLOps templates were open-sourced
- Delivery on both Google Cloud and AWS Bedrock, with named Datatonic engineers quoted alongside client-side leads
Watch-outs
- The AstraZeneca and Alpian write-ups quantify engineering, not business outcome—ask for the return figure
- Much of the work sits inside Google Cloud partnerships—ask who owns the platform relationship and what it costs after handover
- Seven offices across Europe and Toronto—ask which one staffs your engagement
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.
Frequently asked questions
- Which has more E-commerce experience, Artefact or Datatonic?
- Both agencies show documented E-commerce work and have similar industry breadth. Compare directly on the agency profiles: Artefact and Datatonic.
- Which scores higher overall, Artefact or Datatonic?
- 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 Datatonic?
- Consider running parallel discovery briefs with Artefact and Datatonic 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.