What RakerOne is

RakerOne is a back-office automation platform where you and a built-in AI assistant, Florent, work together to get repetitive, document-heavy office work done — intake, invoice processing, contract review, vendor onboarding, claims, and the like. You define a process once as a reusable playbook, then run it inside a project that holds your files, records, and people. Florent does the heavy lifting — reading documents, pre-filling forms, drafting records and documents — but you always review and approve before anything becomes real data.

Who it’s for

RakerOne is built for business and operations teams who run document-heavy, multi-step processes and want AI to remove the grunt work without giving up control. You do not need to be technical. If your job involves collecting files, pulling data out of them, filling forms, and producing documents — over and over — RakerOne is for you.

A typical moment: a team drops 400 PDFs into a project and types “Extract these into my Invoice table.” Florent turns that sentence into a concrete run, you review the shape and start it, the documents get read by AI, and every extracted value lands as a draft for you to check. You approve, edit, or reject each row — and only then does it become real data.

The one rule that defines RakerOne

This is the promise behind everything in the product. Florent will never:

• activate or publish a draft,
• approve or reject a task,
• submit or complete a task for you,
• start or cancel a run,
• delete anything, or
• set who can access something.

You always perform the final, consequential action yourself. Florent shapes, reads, and proposes; you decide.

How the pieces fit together

Hold this one picture in your head and the rest of the app makes sense.

Your organization is your whole workspace. Inside it you keep two things: Building Blocks (reusable definitions you set up once — project templates, playbooks, actions, record types, document templates) and projects (where the actual work happens, one project per piece of work). When you run a playbook inside a project you get a run, which is made of tasks — the individual steps a person or Florent works through. As tasks finish, they produce records (rows of data) and files. A human approves before any AI-produced data is committed.

A few relationships worth fixing in your mind:

• A playbook is a blueprint. A run is one execution of that blueprint inside a project. You can run one playbook many times.
• A record type defines the shape (the fields). A record is one row of that shape. Approved drafts become records.
• A task is one step in a run. People do Form and File upload tasks; Florent and automation handle Document, Action, and AI task steps.
• Project templates are snapshot-copied — creating a project from a template copies its contents, and later edits to the template do not change projects you already created.

A tour of the app

Every screen sits inside the same frame: a left sidebar for navigation, a top breadcrumb trail showing where you are, and the main content area on the right.

The sidebar, top to bottom

The breadcrumb

The top bar shows a breadcrumb trail of where you are — for example, Projects · Smith family · Files. It always shows human-readable names (project names, playbook names, run numbers), never internal IDs. The breadcrumb is hidden on the Home page, which is its own starting point.

Where to go next