Comparison updated August 2026
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 | ML6 | Unit8 |
|---|---|---|
| Editorial score | 73.3/100 | Higher score: 74.8/100 |
| Hourly rate | Contact for rates | Contact for rates |
| Team size | Larger team: 50-249 | |
| Location | Ghent, Belgium | Lausanne, Switzerland |
| Founded | — | 2017 |
| Last reviewed | Aug 4, 2026 | More recent review: Aug 7, 2026 |
What we said about each
Our take on ML6
The published case library runs to 34 studies, and the ones read in full carry before-and-after numbers rather than adjectives—Scout24's HeyImmo assistant moved user satisfaction from 68% to 75% and first-token latency from 8 seconds to under 5, and Syngenta's lab-inspection vision model doubled analysis speed across half a million wells a year. Studies name the stack down to the component (OpenAI direct API, Pydantic agents, DataDog on Scout24's own AWS; Vertex AI for Syngenta) and describe…
Reviewed Aug 4, 2026
Read the full assessment →Our take on Unit8
The practice is built around Palantir Foundry, and the published work shows what that buys: a supply-chain control tower that cut a global retailer's out-of-stock levels by half, early-warning indicators for risk and fraud at a major Swiss bank, a Foundry center of excellence at a financial institution, and a blending-optimization algorithm at a Swiss chemical company reported at roughly CHF 400,000 saved per year. Client names appear on the roster (Daimler, Merck, Swiss Re, Firmenich, WWF)…
Reviewed Aug 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 ML6 if you need
- closer collaboration at a smaller team scale
- disclosed specialization in Public Sector
- broader service offering — also covers AI Agents
Choose Unit8 if you need
- larger team capacity for multi-stream or enterprise-scale programs
- disclosed specialization in Healthcare
Strengths and watch-outs
Both upsides and risks, straight from our editorial assessments.
ML6
Strengths
- Case studies publish client-side quotes from named engineering managers, not marketing testimonials
- Published outcomes at the national cyber security center include 3x faster vulnerability handling and 70% faster NIS2 response
- Both major clouds are in evidence—AWS and Google Vertex AI appear in separately documented builds
Watch-outs
- Two energy studies run anonymized as "Energy Company"—ask for a speakable reference if you need one in that sector
- No published rates, team size, or founding year; anchor with the EU €100-200/h band and ask who staffs the work
- Delivery sits across four offices—confirm which one your team would come from
Unit8
Strengths
- Over 250 delivered data and AI projects and 150+ staff with prior experience at Apple, Amazon, Google and Palantir
- Certified partner across Palantir, OpenAI, NVIDIA, AWS, Snowflake, Databricks and Dataiku—platform choice is unlikely to be constrained by one vendor relationship
- Named fastest-growing Swiss company by the Financial Times in 2022, with Sagard NewGen backing the current phase
Watch-outs
- Ask which engagements ran outside Foundry if you do not intend to adopt it
- Most case studies describe the client by sector rather than by name—request a speakable reference in yours
- The Zurich presence is an office; the head office and registered entity are in Lausanne
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 FinTech experience, ML6 or Unit8?
- Both agencies show documented FinTech work and have similar industry breadth. Compare directly on the agency profiles: ML6 and Unit8.
- Which scores higher overall, ML6 or Unit8?
- Unit8 scores 74.8/100, 1.5 points higher than ML6 at 73.3/100. See our methodology for how scores are calculated.
- When should I consider both ML6 and Unit8?
- Consider running parallel discovery briefs with ML6 and Unit8 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.