Trilateral Research vs ML6: full comparison for 2026
Quick verdict
Trilateral Research (4.3/5) edges ahead of ML6 (4.0/5) overall. Trilateral Research is the better choice for public bodies needing rights and ethics assessments. ML6 is the stronger option for benelux firms wanting advice from builders. The right choice depends on how independent you need the advice to be, your regulatory exposure, and your budget.
Trilateral Research vs ML6: head-to-head summary
| Criterion | Trilateral Research | ML6 |
|---|---|---|
| Founded | 2004 | 2013 |
| HQ | London, UK | Ghent, Belgium |
| Team size | 55–200 | 140+ |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Primary differentiator | Fundamental rights and ethics impact assessments from a research-led firm | Use-case discovery from engineers who also handle EU AI Act requirements |
| Pricing model | Project fees; rates on request | Project fees; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | EU AI Act, GDPR, ISO/IEC 42001 | EU AI Act, GDPR, Google Cloud |
| Industries served | Public sector, Law enforcement, Healthcare, Financial services | Manufacturing, Media, Retail, Public sector, Financial services |
Trilateral Research vs ML6: overview
Trilateral Research
Trilateral Research was established in 2004 and is headquartered in London, with an Irish operations center in Waterford. It began in research and data protection and now advises on responsible AI, including fundamental rights impact assessments of the kind the EU AI Act requires for some high-risk deployments. Directory estimates of its size range from about 55 to 200 people. It also builds its own ethical AI software, mostly for public-sector and law-enforcement users.
ML6
ML6 has been building AI in Ghent since 2013 and employs 140+ people in Belgium, Germany, and the Netherlands. Its strategy work covers ambition-setting workshops, use-case discovery, and EU AI Act questions, and OpenAI named it a services partner in June 2025. Most clients go on to build with ML6, so the advice is grounded in engineering reality but not neutral about who builds.
Services and capabilities: Trilateral Research vs ML6
| Capability | Trilateral Research | ML6 |
|---|---|---|
| Readiness assessment | ✓ | ✗ |
| Use-case prioritization | ✗ | ✓ |
| TCO / ROI modeling | ✗ | ✗ |
| AI governance & EU AI Act | ✓ | ✓ |
| Build vs. buy advice | ✗ | ✗ |
| Independent audit or assurance | ✗ | ✗ |
| Roadmap any vendor can implement | ✗ | ✗ |
| Delivery capability after advice | ✗ | ✓ |
Frameworks and platforms: Trilateral Research vs ML6
| Framework / platform | Trilateral Research | ML6 |
|---|---|---|
| EU AI Act | ✓ | ✓ |
| GDPR | ✓ | ✓ |
| DORA | N/A | N/A |
| NIST AI RMF | N/A | N/A |
| ISO/IEC 42001 | ✓ | N/A |
| Azure | N/A | N/A |
| AWS | N/A | N/A |
| Google Cloud | N/A | ✓ |
Pricing comparison: Trilateral Research vs ML6
| Criterion | Trilateral Research | ML6 |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed-scope assessment, Ongoing advisory | Fixed-scope assessment, Delivery team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Trilateral Research vs ML6
| Dimension | Trilateral Research | ML6 |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Public sector, Law enforcement, Healthcare | Manufacturing, Media, Retail |
| Best use cases | Fundamental rights impact assessments for high-risk AI., Ethics reviews of public-sector AI systems. | Use-case workshops for a Belgian or Dutch company., Checking feasibility before committing to a build. |
| Typical project type | Fixed-scope assessment | Fixed-scope assessment |
Trilateral Research vs ML6: pros and cons
| Trilateral Research | |
|---|---|
| + | Two decades of research on ethics and data protection |
| + | Fundamental rights impact assessments are a core skill |
| + | Independent of the big cloud and software vendors |
| - | Small team for large multi-country programs |
| - | Builds its own software, which can shape recommendations |
| - | Less focus on cost modeling or business cases |
| ML6 | |
|---|---|
| + | Feasibility advice comes from people who build |
| + | EU regulation is routine in its projects |
| + | Strong Belgian and German client base |
| - | Advice usually leads into its own engineering work |
| - | OpenAI partnership may color model recommendations |
| - | Limited footprint outside the Benelux and Germany |
Who should choose Trilateral Research?
A typical fit: fundamental rights impact assessments for high-risk AI.
Fundamental rights and ethics impact assessments from a research-led firm. Minimum engagement is not publicly disclosed. Works best with clients in Public sector, Law enforcement, Healthcare, Financial services.
Who should choose ML6?
A typical fit: use-case workshops for a Belgian or Dutch company.
Use-case discovery from engineers who also handle EU AI Act requirements. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Media, Retail, Public sector, Financial services.
Decision matrix: Trilateral Research vs ML6
| Your situation | Recommended choice |
|---|---|
| You want advice with no build contract attached | Trilateral Research |
| Finance needs run costs before approving anything | Neither lists cost modeling; ask for a sample |
| Some of your use cases may be high-risk under the EU AI Act | Both cover AI Act classification |
| You need an outside check on a system already built | Neither; use a dedicated auditor |
| You want the same firm to build what it recommends | ML6 |
| Your budget is at the lower end | Compare: Trilateral Research (Not disclosed) vs ML6 (Not disclosed) |
| You need advisers in many countries at once | ML6 |
Use case fit: Trilateral Research vs ML6
| Use case | Trilateral Research fit | ML6 fit | Winner |
|---|---|---|---|
| Fundamental rights impact assessments for high-risk AI. | Strong | Limited | Trilateral Research |
| Ethics reviews of public-sector AI systems. | Strong | Limited | Trilateral Research |
| Use-case workshops for a Belgian or Dutch company. | Limited | Strong | ML6 |
| Checking feasibility before committing to a build. | Limited | Strong | ML6 |
Verdict: Trilateral Research vs ML6
Trilateral Research (4.3/5) is the stronger overall choice for most AI Advisory projects. Fundamental rights and ethics impact assessments from a research-led firm.
ML6 (4.0/5) is worth a look if you need checking feasibility before committing to a build. If your situation matches that, ML6 is a competitive option.
Related comparisons
Trilateral Research vs ML6 FAQ
Is Trilateral Research better than ML6?
Trilateral Research (4.3/5) scores higher overall, but "better" depends on your use case. Trilateral Research's strongest advantage: two decades of research on ethics and data protection. ML6's strongest advantage: feasibility advice comes from people who build.
How do Trilateral Research and ML6 differ in pricing?
Trilateral Research's pricing: project fees; rates on request. ML6's pricing: project fees; rates on request. Any hourly bands shown come from Clutch, not a published rate card, so a scoping call is still needed for a project quote.
Which is better for enterprise: Trilateral Research or ML6?
ML6 is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each firm before shortlisting.
What are the main differences between Trilateral Research and ML6?
Trilateral Research's primary differentiator is: fundamental rights and ethics impact assessments from a research-led firm. ML6's primary differentiator is: use-case discovery from engineers who also handle EU AI Act requirements. They also differ in team size (55–200 vs 140+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Public sector, Law enforcement vs Manufacturing, Media).
Verify all details directly with each firm before making a decision.