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 | ML6 | Twistag |
|---|---|---|
| Editorial score | 74.8/100 | Higher score: 78/100 |
| Hourly rate | Contact for rates | €45-85/hr |
| Team size | Larger team: 50-249 | 10-49 |
| Location | Ghent, Belgium | Lisbon, Portugal |
| Founded | — | 2016 |
| Last reviewed | Aug 4, 2026 | More recent review: Sep 9, 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 Twistag
The best-documented AI portfolio on this page, and the detail is where the value is. For the manufacturer Aralab, an accounts-payable agent reads any supplier PDF with Claude while deterministic code independently recalculates every line total, unit price and tax figure against the matched purchase order: the model proposes, the validation engine verifies. It shipped in six weeks with one engineer, handles more than 2,000 invoices a month, and moved three finance people off transcription.
Reviewed Sep 9, 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
- larger team capacity for multi-stream or enterprise-scale programs
- disclosed specialization in Public Sector
- broader service offering — also covers AI Consulting and Generative AI
Choose Twistag if you need
- closer collaboration at a smaller team scale
- disclosed specialization in SaaS & B2B
- broader service offering — also covers AI Automation
- a higher overall editorial score
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 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
Twistag
Strengths
- The hybrid pattern is published, not implied: the language model interprets and deterministic code independently recalculates every figure against the purchase order
- Observability ships with the system—LangFuse traces every call with prompt versions and per-invoice cost visible in real time, so the workflow cannot get quietly expensive
- Models sit behind a provider abstraction and were swapped twice on one engagement without the product changing shape
Watch-outs
- The largest engagement, the regulatory compliance platform, is anonymized—ask for a speakable reference at one of the brands running it
- The PepTalk system publishes no measured outcome by the agency's own admission; ask what the volume and turnaround figures are now
- No headcount is published against a decade of trading—ask how many engineers would be forward-deployed on your build and for how long
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.
Pricing math
What a 12-week engagement at one full-time equivalent (~480 hours) costs at each agency’s published rate. An arithmetic projection, not a quote — real scopes move with seniority mix and team shape.
ML6
Contact for rates
Twistag
Rate: €45-85/hr
€21,600–€40,800
Only Twistag publishes a rate, so there is no gap to measure. ML6 quotes per engagement — ask for a rate card early, since a comparison that starts on scope and ends on price tends to end late.
Frequently asked questions
- Which has more FinTech experience, ML6 or Twistag?
- Both agencies show documented FinTech work and have similar industry breadth. Compare directly on the agency profiles: ML6 and Twistag.
- Which scores higher overall, ML6 or Twistag?
- Twistag scores 78/100, 3.2 points higher than ML6 at 74.8/100. See our methodology for how scores are calculated.
- Which is faster to engage, ML6 or Twistag?
- Neither publishes lead times, so this is a read on team size rather than a measured answer. Twistag runs the smaller team, which usually means fewer procurement gates and a shorter path to kickoff. ML6 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 ML6 and Twistag?
- Consider running parallel discovery briefs with ML6 and Twistag 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.