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Theorem Labs
All workExhibit E of 9

Compliance assessments across 15+ frameworks, grounded in the customer's own policies.

Hassan works on the platform's backend and AI workflows as a contract engineer, through Xeltec, since 2025.

Client
Arion Networks
Sector
Compliance AI
Scope
Python · Multi-LLM RAG · Supabase
iso.arionetworks.com
The ArionComply website: Compliance without the complexity
fig. 1 · the platform's front door

ProofArionComply

Given.

ArionComply replaces spreadsheets, consultants, and disconnected tools with one platform for US and EU compliance frameworks, built for small businesses, MSPs, and the under-resourced organisations that incumbents overlook.

To show.

That a gap assessment can be a conversation that remembers what it was told, grounded in the documents a company already has.

Construction.

Compliance answers have to be traceable, so every step keeps its record: prior answers loaded before the model speaks, validated facts extracted after, and the AI workflows themselves versioned and observed.

  1. 01

    Retrieval over policies

    retrieve(policies, question)

    Multi-LLM retrieval over customer policy documents, with embeddings and vector search, so answers come from the company's own words.

  2. 02

    Stateful assessments

    assess(answer) → facts

    Each conversation loads the prior answers before inference, extracts validated facts after every response, and saves its progress.

  3. 03

    Self-hosted inference

    llama.cpp · serve()

    Inference on self-hosted models, with an AIOps dashboard for versioning and observing the AI workflows.

  4. 04

    The compliance core

    log · register · notify

    Contributions across event logging, the incident register, breach notification, and MFA, on Supabase with Postgres row-level security.

Figures

fig. 2, a sketch

Assessments hold each customer's own policies, so they stay private. On the board instead: the shape of one.
In build.

Approaching its demo and MVP.

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