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Tore AI

The AI that worksthe whole queue

Not a chat widget bolted onto a help desk. The same intelligence answers the question, sees the bug, finds the cause, writes the fix, writes the article and spots the pattern, because it is the same system holding all of it.

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Included in every plan. Not an add-on, and not priced per resolution.

Last 30 days
Conversations resolvedBugs investigatedArticles writtenAvg first responseAvg time to resolutionSatisfaction
On its ownnobody opened it0008s2m4.6
Priya RamanTogetherit drafted, a person sent0004m26m4.9
Dan OkaforPriya RamanSarah OkonjoYour teamthe ones that needed a person0001h 12m5h 40m4.7
Every conversation records who closed it, so the split is measured rather than claimed.

One case, end to end

A bug arrives four ways and leaves as one change

Every door leads to the same investigation, the same evidence and the same person holding the approval. Watch it once and the rest of this page is detail.

Every way a bug arrives4 doors
  • Maya RiveraCustomer reportCheckout throws a 500 with no plan selectedreplay, console, network attached
LinearIt lands in your trackerLinear · Jira
GitHubfix/checkout-500Awaiting review

Six jobs, one system

What it actually does

Each of these has a page that goes deeper. This is the shape of the whole thing in one place.

It answers them

Replies from your own help center and cites the article it used, so the customer can check it. When it is not confident it hands to a person rather than guessing.

Changing your email signs out other sessions.citedResetting your password

It sees the bug

The report arrives with the element they clicked, the console, the network trail and a replay of the seconds before. Secrets are stripped first, and the customer is told what was removed.

replay 0:30consolenetworkthe elementAttached without them doing anything.

It finds the cause

A thousand error events become one problem. Then it reads the code around the failure and writes down what it found and why it thinks so.

api/checkout/route.ts:42TypeError: priceId undefined1,284 events, one cause.

It writes the fix

A change on a branch, applied and validated against the failure it reproduced, with the checks that ran and the files it touched shown before anyone approves.

+ if (!plan) return badRequest()  const session = await create()+1 −0 · tests green · waiting on a person

It writes the docs

The answer someone just typed becomes a help center article, so the next person who asks gets it without waiting for anybody.

Why changing your email signs you outDrafted from the reply you just sent.

It spots the pattern

The same complaint arriving in chat, email and the portal becomes one request, so what you are looking at is how many people asked, not how many messages arrived.

chatcan we export?emailCSV download?Bulk export · 41 people asked

Model routing

The right model for the job, not one model for everything

Reading a message to sort it and rewriting a payment path are not the same task, and paying reasoning prices for the first one is how AI features get expensive and slow at once.

  • Triage runs fast and cheap, because most of what arrives only needs classifying.
  • Authoring a change runs at high reasoning, because that is where being wrong costs you.
  • The reviewer is forced onto a different vendor than the author, so nothing marks its own homework.
  • You are not locked to one provider. Models are registered, and the role each one serves is configuration.
How the routing is configured
One case, three modelsRouted per job
  • gpt-5.6-codexTriagefast, cheapRead it, classify it, decide if it is worth picking up

Everywhere, not somewhere

Twelve places the AI is already working

Most of these are not surfaces anyone thinks of as AI surfaces. That is the point. It is not a feature in the sidebar, it is how the product runs.

What you control

The question is never can it, it is what stops it

Autonomy is a setting, not a personality. Every rung, limit and lock below is enforced by the product rather than asked of the model.

Four rungs, set per area

Automatic, confidence gated, approval required, or human review. Set it per domain, and a domain setting may only ever be more restrictive than the floor.

Risk classes that cannot be loosened

One shared registry the whole product agrees on. A locked class stays locked, so authentication, billing and migrations are out of automation whatever a setting says.

A budget, and a switch that stops work in flight

Spending is capped per organization per period. The kill switch is not a pause for new work, it terminates what is already running.

The reviewer is never the author

Three roles run the work, and the model reviewing a change is forced onto a different vendor than the model that wrote it. A model marking its own homework is the failure mode everyone else ships.

Every AI control, in detailRisk classes and boundaries

Judge it, do not trust it

Every resolution says who resolved it

Each conversation closes as resolved by the AI on its own, resolved by the AI with a person, resolved by a person, resolved by the customer, or closed automatically. Satisfaction is filed against that same attribution.

So the question stops being whether the AI is any good in general, and becomes whether it is any good on your queue, which is the only version of the question worth answering.

What you can measure

How a conversation can close

  • The AI, on its ownno person touched it
  • The AI, with a personit drafted, someone sent
  • A personthe AI did not resolve it
  • The customerthey solved it themselves
  • Automaticallyit went quiet and timed out
Included in every plan

Point it at one product and judge it on your own queue

No card. Fourteen days is long enough to see what it resolved without you, and what it correctly refused to touch.

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