We’ve been working with auditors and compliance teams in regulated sectors (finance, healthcare) and hit a wall: LLM risk assessments are subjective, non-reproducible, and don't satisfy growing regulatory demands for evidence, not just opinions.

So we built EB3F (Evidence-Based Framework for Foundational Models). It's a packaged methodology that transforms an audit from a consultant's report into a standardized process for producing reproducible, legally-admissible exhibits.

The twist: We're not selling consulting services. We're structuring it as a transferable asset (like a franchise model). We sell the complete framework – methodology, tools, templates – so that consultancies, RegTech firms, or in-house teams can run their own certified audits.

We're looking for:

1. Feedback from experts in AI governance, compliance, and ML security. Is this approach useful? What's missing? 2. First partners (especially in consulting or RegTech) who want to implement this as their own service line. We're ready to discuss details under NDA.

Why would you buy this? Our estimate (based on building similar frameworks in corps): it saves 18-24 months and $750K-$1M+ in R&D, legal reviews, and piloting that you'd spend to build this in-house.

What does the community think? Can a "framework as an asset" model work in the AI governance space?