All agents

Clean RO stories without the typing

Writes the complaint, cause and correction on each RO from tech notes, voice memos and fault codes, and flags gaps before invoicing and warranty review.

How it works
The reality

Thin RO notes cost money.

Customers question vague invoices and warranty reviewers reject them. Techs would rather turn wrenches than type, so stories are short and someone else rewrites them.

At 6 pm a shop has 22 ROs closed out with notes like replaced sensor, ok now. The service manager spends the next morning rewriting them before they can invoice.
A typical day for heavy-duty repair shops
How it works

RO story writer, step by step.

The agent does the work inside your systems. Your team approves what matters.

  1. 1

    Collect the notes

    Gathers tech notes, voice memos, fault codes and parts used on the RO.

  2. 2

    Write the story

    Drafts a complaint, cause and correction in plain shop language.

  3. 3

    Send for review

    Posts the story to the RO and flags gaps like a missing fault code.

What changes

Your team keeps the judgment calls.

The agent takes the repetitive work. People approve, decide and talk to customers.

  • Fewer invoice disputes
  • Stories ready for warranty review
  • Techs talk instead of typing

Works inside the systems you already run

Shop managementVoice memosRO story writerDiagnosticsAccounting
Questions we get

Before you ask.

Writes the complaint, cause and correction on each RO from tech notes, voice memos and fault codes, and flags gaps before invoicing and warranty review. It works in three steps: collect the notes, write the story and send for review.

It works inside the tools your team already uses, including shop management, voice memos, diagnostics and accounting. Nothing to rip out and nothing new to learn.

It starts in shadow mode, drafting the work for your team to approve or correct. You decide what it handles on its own, and every action is logged.

Your data is used only to run the workflows you approve. We do not use your proprietary data to train public or unrelated AI models.

Get started

Start with one agent.

Pick the workflow that hurts most. We'll scope it on the first call.