# Adastra vs ML6

> Comparing AI Consulting options: Frankfurt vs Ghent. 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/adastra-vs-ml6
Generated: 2026-09-17 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold.

## Facts
| | Adastra | ML6 |
|---|---|---|
| Editorial score | 74.8/100 | 74.8/100 |
| Hourly rate | not published | not published |
| Team size | 250+ | 50-249 |
| Location | Frankfurt, Germany | Ghent, Belgium |
| Founded | 2000 | — |
| Last reviewed | 2026-09-16 | 2026-08-04 |
| Services | AI Consulting, AI Development, Generative AI | AI Consulting, AI Development, AI Agents, Generative AI |
| Industries | FinTech, Manufacturing, Public Sector | FinTech, Manufacturing, Public Sector |

## Our take on Adastra
Reviewed 2026-09-16 by Gabor Kiss against published evidence.

NLB is the study that settles the deployment question: the Slovenian bank put an agentic-AI control layer and its first use case into production in five months, with identity-based approvals through Entra ID, separated development, test and production environments, cost monitoring on Grafana dashboards and a published 80% cut in the time and cost of standing up each further use case.

Two more named systems sit behind it—GenAI enterprise search for KWS on Amazon Bedrock, OpenSearch and SageMaker, delivered inside a Microsoft Teams channel, and a print-bundling optimizer for GZ Media that went from proof of concept to a production application with errors reported down to zero.

Depth across the rest of the library is uneven: much of it is Power BI, Microsoft Fabric and Databricks reporting work rather than AI, the Magna Bohemia planning story is written in the future tense with no measured outcome, and the GZ Media headline states a six-month ROI that its own body describes as the proof of concept's projection.

The weaker fit is buyers who want a small senior team on one model end to end—the pattern here is platform and governance work staffed from a practice the site puts at more than 150 AI specialists across six countries.

### Key strengths
- Client executives go on the record by name and title—NLB's CIO and AI architect, GZ Media's print production director, Magna Bohemia's CEO—so references are traceable before the first call
- German delivery is not a sales address: four offices with street addresses in Frankfurt, Wolfsburg, Munich and Hannover, a named German CEO and a named German AI lead
- The German-language index lists further AI engagements at E.ON, KUKA, ams OSRAM and Hyundai, so the German book is not one story deep

### Good to know
- No rate is published anywhere read—ask for a blended day rate and for the split between German and Czech or Slovak delivery before comparing bids
- The 150-plus AI specialists and 20-plus years are the firm's own figures—ask how many sit in the German practice and who would staff your engagement
- Governance is the visible strength; if you need the model built and evaluated, ask for the evaluation method and accuracy numbers behind a delivered use case

## Our take on ML6
Reviewed 2026-08-04 by Gabor Kiss against published evidence.

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 how the client was left able to run the system without them.

Work spans regulated and public buyers—the national cyber security center, the EU Council newsroom, Flemish highways—alongside industrial names.

The weaker fit is a buyer wanting a fixed quote up front: no rates, headcount, or founding year appear anywhere public.

### Key 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

### Good to know
- 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 European range on our rate index and ask who staffs the work
- Delivery sits across four offices—confirm which one your team would come from

## Which to choose
Choose Adastra for:
- larger team capacity for multi-stream or enterprise-scale programs
- an overall editorial score of 74.8/100

Choose ML6 for:
- closer collaboration at a smaller team scale
- broader service offering — also covers AI Agents

## Questions buyers ask

### Which has more FinTech experience, Adastra or ML6?
Both agencies show documented FinTech work and have similar industry breadth. Compare directly on the agency profiles: Adastra and ML6.

### Which scores higher overall, Adastra or ML6?
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 Adastra and ML6?
Consider running parallel discovery briefs with Adastra and ML6 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