Enterprise AI that does the work: one named job, governed from the first run.Map your first AI teammate
Solutions · Management

You asked three people.
You got three numbers.

Monday pack, what ran on each team, the number behind one question. An AI employee assembles them. You walk in with one version.

3
Answers to the same question
1wk
To assemble the Monday pack
5
Approvals sitting on the wrong desk
0
Shared picture of what ran today
The real cost

Sound familiar every Monday?

Today
  • You ask sales, finance, and ops the same question. Three spreadsheets come back. None match
  • Monday pack is still four exports and a night in PowerPoint
  • A quote, a refund, a PO follow-up — sitting on a desk that is not yours, and you find out in the meeting
  • The person who knows the real number is in another meeting. The slide goes out anyway
->
With PromptRails
  • One pack lands Sunday night. Sales, cash, open POs, the queue — same definitions
  • You ask once. The number comes from the systems, not from three inboxes
  • What is waiting on whom is on the board before the standup
  • Nothing that touches a customer or money leaves without the person you named
On your desk

One pack. One number. The right desk.

An AI employee assembles what sales, finance, and ops already ran. You get one pack, one answer, and the approvals that were waiting on the wrong person.

What ran today

Each team, one live board

See what sales, finance, operations, and service actually ran. What is waiting. What failed. Before someone walks it into the Monday meeting.

  • Active jobs per team at a glance
  • Approvals that will block the day, surfaced now
  • Open any job: the data, the draft, who has it
What ran today
Sales 14 active
Finance 9 active
Operations 6 active
Marketing 8 active
Pending approvals 5 waiting
Monday pack

The number you asked for, once

An AI employee pulls the same definitions your teams already use and drafts the pack. Hours on the job, what closed, what is still open. You edit the note. You do not rebuild the table.

  • One version of cash, pipeline, and open work
  • What waited on a person, not a slide
  • You send the pack. You do not assemble it
Monday pack
Cash vs last Monday ready
Open quotes 14 review
Overdue invoices 9 flagged
Pack waiting on you review
The right desk

Approvals wait on the person you named

A quote, a payment, a customer reply — nothing leaves until the desk you set has signed. You see who is holding the line. The trail stays.

  • You name who signs quotes, cash, and replies
  • Customer data is masked before the model sees it
  • Who approved, when, what changed — on the job
The right desk
Data masking pass
Sales manager approved
Finance waiting
Trail 12 entries
How it lands

One named job. Then it runs.

1
Sit
We walk the job as it actually runs on your team.
2
Connect
We connect the systems your people already use.
3
Draft
An AI employee does the work. You review every output.
4
Measure
Time back, queue length, what waited on you.
5
Add
If the first job holds, add the next one.

Walk in with one number. Not three.

Pick the Monday pack or the question that always comes back three ways. We sit with how it actually runs.