AI that can prove it's right
Encode any rule, policy, or law as code that returns the same answer every time, with a proof of why. Language models synthesise the rules at build time. A constraint solver evaluates them at decision time.
Affordability check for unsecured consumer credit.
curl -X POST https://api.aethis.ai/api/v1/public/decide \
-H "Content-Type: application/json" \
-d '{
"ruleset_id": "aethis/consumer-credit-prequalification",
"field_values": {
"credit.has_adverse_history": false,
"credit.employment_status": "employed",
"credit.gross_annual_income": 50000,
"credit.has_joint_applicant": false,
"credit.joint_annual_income": 0,
"credit.dti_percent": 25,
"credit.credit_score_band": "excellent",
"credit.product_type": "unsecured",
"credit.ltv_percent": 0,
"credit.stress_test_passed": true,
"credit.is_existing_customer": true
},
"include_trace": true
}'Navigation, not just decisions.
Legislation isn't a checklist. It's a forest of criteria with branches, exceptions, and alternative routes. Aethis maps the traversable paths through the rules and guides a user towards the best outcome given their situation — surfacing viable routes, not just a verdict.
Soft constraints find the path. Hard constraints hold the law.
What is Aethis?
Aethis compiles legislation, policy, and contracts into formally verified rules. Language models read the source at build time and synthesise candidate rules; subject matter experts (SMEs) write tests that define correct behaviour; the engine refines rules until every test passes. At decision time, a constraint solver evaluates the compiled rules against the supplied facts. No language model in the request path. Every decision returns a proof and an audit trail traceable to the source.
- 0
- LLM calls in the request path
- 100%
- accuracy where frontier LLMs score 63-100% Simpson 2026 §3
- 1,000×
- faster than a frontier-LLM call
- ≈£0
- marginal cost vs ~$0.02 per LLM call
How does Aethis compare?
How Aethis compares to other ways of making rule-based decisions.
| Capability | Aethis | LLM only | Static rules engine | Decision tree |
|---|---|---|---|---|
| Same input → same output | ||||
| Source-cited audit trail | Manual | Partial | ||
| Authoring from source text | LLM-assisted | n/a | Manual | Manual |
| Handles legislation directly | Yes (probabilistic) | Hand-encoded | Hand-encoded | |
| Auditable for regulated workflows | When rules are explicit and validated | Not deterministic | Yes (no source traceability) | Yes (fixed branching) |