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The AI operating system for justice

Your morning is already done.

Every person on your staff supervises an agent and works from their own dashboard. Overnight it prepares the day. You arrive, you review, you approve once.

Accessible to everyone (WCAG 2.2 AA) · 100+ languages · Every action on the record

A sample view of a deputy clerk's own dashboard on eCourt AI, as it looks at the start of a Tuesday. Nothing here is a performance figure; the counts are illustrative. Her agent is Scribe, the documents and notices agent, which reports to her and is set to draft for approval. Overnight it prepared the cascade from yesterday's continuance: notices in three languages, a calendar change, and the portal answer, all waiting on one approval, each carrying the record it came from. Relay, the voice agent, answered the routine calls that came in after hours and left a short call-back list with the reason attached to each. Ledger, the payments agent, reconciled the day's transactions and flagged one payment plan going off track early enough to fix. Below that, her own record of everything done in her name, attributed and timestamped. Nothing has been sent. She reviews, approves once, and the day begins.

Due processImpartialityOpen courtsAccess to justiceOn the record

Between the systems, there is only a person.

Case management here, payments there, scheduling somewhere else, and a portal that knows none of it. Each one does its job. Not one of them tells the next what just happened.

So a clerk types the same date into four screens. An officer reads last night’s activity one file at a time. A judge asks why Thursday is jammed and waits a quarter for the answer. The counter stays busy because the phone never stops, and the person actually standing at it waits.

None of that is anyone’s fault. It is simply what happens when the work crosses seven systems and only a person can carry it across.

And when a handoff drops, someone finds out the hard way. A notice goes to an address they left two years ago, and the warrant that follows is out of all proportion to forgetting an appointment.

The stitching is the job nobody was hired to do, and it is most of the day.

The building was dark. The work carried on.

Your agent does not stop when the counter closes. It directs the follow-ups, the checks, the recomputes, and the drafts through the night, so the morning arrives prepared instead of arriving as a backlog.

Every one of those is preparation. Nothing reaches a person, a calendar, or the record until someone on your staff approves it.

A sample of what happens between the close of one day and the start of the next on eCourt AI. This shows the kinds of work and the order they happen in; it contains no performance figures. At 18:00 the counter closes and nobody is at the desk. At 19:40 a call arrives anyway and is answered in the caller's language, with what they need written down for the morning. At 23:15 an order lands in the record and every date it touches is recomputed against the rule that governs it, sources kept. At 02:30 the notices are drafted in the languages each recipient reads and checked against local rules; drafted, not sent. At 04:05 a scheduling conflict is found and flagged with options prepared. At 06:50 the payment plans are reconciled and one going off track is flagged early enough to act on. At 08:02 a member of staff arrives and it is all waiting in one queue, each item carrying its record. They review and approve once. Every item above is preparation. Nothing left the building without a person approving it.

One agent to supervise. Never a fleet to manage.

Nobody on your staff is handed a control panel of robots. Each person supervises a single agent, the way they would a single colleague. That agent directs its own work underneath, and every action anywhere below resolves back to the person at the top.

Which is why the org chart does not change shape. Nobody is replaced. Everyone gains a staff.

Meet the agents
Staffed byRelayGuideScribeLedgeravailable now · Docket, Compass, Vantage in development
The accountability chain on eCourt AI, drawn from the top down. At the top, one person: a member of your staff, who supervises and decides. Below them, one primary agent, which reports to that person, carries published guardrails, and works at the autonomy level the agency set. Below the agent, the work it directs: follow-ups, checks, recomputes, and drafts, running continuously so a morning arrives prepared, and never exceeding the permissions of the agent above. At the base, the engine: the deterministic layer holding the record and your jurisdiction rules, from which every fact is drawn. Every action anywhere in the chain resolves to the person at the top.

The model never holds the facts.

A hearing date is never written by a model here. It is computed from the rule that governs it, or read from the record, and it arrives with its source attached. Underneath every agent is the engine: the deterministic layer holding the record and your jurisdiction’s rules, from codes and charges to deadlines, fees, notice requirements, and who may see what.

The model reads the question and writes the answer in plain words. The engine decides what the answer is. Every reply carries the rule or the record it came from.

How the engine works
How an answer is produced on eCourt AI. A question arrives from a person, in their own words. The model reads it and works out what is being asked. That is the only thing the model is asked to do on the way in. The question then goes to the engine, the deterministic layer holding the record and your jurisdiction rules, which computes or retrieves the answer along with the rule or record it came from. The model then puts that answer into plain words in the reader language. The model never sources a fact and is never asked to remember one, so a fabricated date has nowhere in this path to originate. The answer leaves carrying its source.

Nothing happens at a level you did not set.

Every capability is opt-in, and autonomy is one control your agency turns, per agent and per workflow. Work prepared overnight sits at the level you chose for it, and what an agent may finish without review is never more than you allowed.

Governance
Your policies, not ours. Customise what ships, or write your own.
Observability
Watch the work as it happens. Every agent has a manager view, and the manager is you.
Traceability
Everything on the record: attributable, timestamped, reviewable, exportable.
Governance and controls
Autonomy on eCourt AI is a single control with four positions, set by the agency per agent and per workflow, and changeable at any time. The positions in order: 1, Suggest, the agent recommends, your staff act. 2, Draft for approval, the agent prepares, a human signs, which is the default at deployment. 3, Act with review, the agent acts, your staff audit. 4, Act on its own, earned, scoped, always on the record. Agents earn autonomy the way staff do, by doing the work well, visibly, over time.

The first step is smaller than you think.

Most agencies begin where nothing is spent: a readiness plan they own, or a solution that costs the agency nothing at all. Your first agent goes live on one workflow, instrumented from day one, and at 90 days you review your own numbers with us.

The path an agency takes with eCourt AI, in four steps, each one further than the last but none of them large. Step 1, A readiness plan: Policies and priorities you own. No cost. Step 2, Self-funded solutions: Turn on what costs your agency nothing. Step 3, Your first agent: One role, one workflow, measured from day one. Step 4, The roster: An agent for every role, sharing context. Most agencies begin at the first or the second step, where nothing is spent, and the results decide whether there is a third.

Your staff stop carrying the work between the systems and go back to the work only they can do. The person who would have missed a hearing gets told, in their language, in time. And the difference shows up on your own dashboard, in numbers you can take to a budget hearing.

The future of courts and justice, working today

Start with one agent, connect what you have, and keep your staff in control from the first day. Add the next role when the results make the case.

Not sure where to start?Get an AI readiness plan