Information architecture for AI
Don't retrieve compliance documents. Retrieve compliance decisions.
Don't retrieve compliance documents. Retrieve compliance decisions.
NovaCopilot is a regulatory infrastructure layer for AI. We do not compete with the language models, we are their regulatory fact layer: a Global Regulatory Answer, Decision & Enforcement Graph where supervisory decisions and sanctions link directly to the requirements they enforce. Instead of your pipeline reading thousands of pages of legislation, case law and supervisory decisions, it fetches a finished, deterministic decision object of 100 to 300 tokens, with source, read date and content hash.
From documents to decisions
1. Documents
Legislation, case law and supervisory decisions are fetched daily from the publisher, with official wording.
2. Objects
The text is broken down into deterministic regulatory objects: requirements, controls, evidence, sanctions and precedents, each with its own ID and hash.
3. Decisions
The AI system fetches the decision object directly. The same question always gives the same answer, and the answer can be verified against the source.
The measurable gains
- Token reduction
- A decision object of 100 to 300 tokens replaces thousands of pages of source text in the prompt.
- Lower latency
- A finished answer instead of crawl, normalisation and RAG in your own pipeline.
- Less GPU cost
- No vector database of your own, no inference over raw text.
- Fewer hallucinations
- Every claim comes from the register, never from the model. Missing evidence is marked, never guessed.
- Full provenance
- Source, read date, version and sha256 on every object, ready for audit.
We do not compete with LLMs
The language models reason. NovaCopilot gives them verified regulatory facts to reason from.
Build your own end product on top of the decision objects: an app, a dashboard, an analysis tool. The infrastructure underneath is finished.
Delivery is JSON rendered directly in your surface, on phone, desktop or tablet. No PDFs, Excel or CSV in the delivery path.
Built for apps first
Every agent answer is compact enough to render directly in an app surface, source line included. One call returns a finished decision object, with no RAG step in between.