How the AI works
The models are the product, so here is exactly what they do
Live routing
- Map evidence to controlsgpt-4.1-mini
- Write the gap in plain languagegpt-4.1-mini
- Draft the missing policygpt-4.1-mini
- Triage an incoming documentgpt-4.1-nano
The pipeline
Five steps, and two of them have no model in them at all
Ingest
fast model
Whatever you paste is split into passages and each one is triaged: is this a policy, a ticket, a settings export, a chat log? Triage runs on the cheapest model that can read, because this step is volume work and does not need judgement.
Nothing is discarded. A passage Trellis cannot classify still goes to the mapping step.
Map
balanced model
Every control in scope is put to the model together with its criterion, its plain-language meaning and the evidence an auditor asks for. The model returns a status, the gap, the evidence it saw, the evidence still needed and a supporting quote.
The prompt is explicit that silence means missing, intent does not count, and no numeric score may be produced.
Verify
no model
This step has no model in it. Quotes are matched against your submitted material verbatim after normalising whitespace and quote characters. Fragments under eighteen characters are rejected outright. Anything unfound is dropped and the finding is labelled unsupported.
A control returned as met with no evidence named is downgraded to weak here, in code, with the reason shown to you.
Score
no model
Readiness is arithmetic on the statuses. Met counts one, weak counts a half, missing counts nothing, divided by the controls in scope.
We never ask a model for the number, because a number a model invented is a number you cannot defend to an auditor.
Draft
balanced model
The largest open gap is drafted into a real document: purpose, scope, the policy itself, the evidence retained, and the three fields reviewers always check, which are owner, effective date and review cadence.
Drafts must not claim you already do something. Unknown specifics come back as bracketed placeholders so it is obvious what to fill in.
Model-agnostic
The candidate set, and why it exists
| Model | Provider | Tier | Routed for | USD / 1M tokens |
|---|---|---|---|---|
| gpt-4.1live | openai | frontier | long policy sets, contested control judgements, multi-framework overlap | $8.00 |
| gpt-4.1-minilive | openai | balanced | control mapping, gap wording, policy drafting | $1.60 |
| gpt-4.1-nanolive | openai | fast | document type triage, deduplicating evidence | $0.40 |
| claude-sonnetdeclared | anthropic | frontier | careful reading of long policy text, draft tone | $9.00 |
| gemini-flashdeclared | fast | bulk ticket triage, screenshot and settings extraction | $0.50 | |
| llama-opendeclared | meta | open | self-hosted deployments, customers who cannot send data out | $0.30 |
Live means a key for that provider is configured in this deployment and the adapter is wired. Declared means the model is in the routing table behind the same interface and switches on when a key is present. If every provider is unreachable, a run falls back to a deterministic offline analyser and the result says so on its face, rather than failing or quietly pretending.
Limits
What this cannot do
It can be wrong about a control
Trellis assesses 22 controls from text. A policy can say the right words and describe something nobody does. Our answer is to default to missing and to make you name the evidence, which makes the product feel harsher and makes it more useful.
It cannot see what you did not give it
If your best evidence is a screenshot in someone's downloads folder, Trellis will call that control missing. It is right to. An auditor would too.
It does not watch your infrastructure
Trellis reads what you bring at the moment you bring it. Continuous drift checks are on the roadmap and are not here yet.
It is not an auditor
No output of this product is an audit, a certification or an opinion. A licensed CPA firm does that, independently of you and of us.
Read how we handle your material
Retention, subprocessors, deletion and the training question.