We automate the work your team still does by hand, and build it so the system tells you which items need a person and why.
Most manual work is not hard. It is reading a document, looking something up in another system, keying it in, and sending it to someone for approval. The trouble starts when an automation gets some of those wrong and gives no sign of which ones.
So we design around the exceptions. Clean items go straight through. Anything the system cannot prove is right goes to a review queue with the source document beside it and a plain reason for the hold. Your team stops checking everything and starts checking the few items that matter.
Under the hood that is usually Power Automate for the flow, AI document reading for extraction, a lookup against your system of record to confirm what was read, and a Power Apps screen for review and approval. Where a system has no API, a desktop bot does the keying.
Read invoices, match them to the right job, purchase order or cost code, and route them for approval before posting.
Capture email and fax attachments and file them to the right client or matter folder without losing or duplicating a document.
Turn dispatch, telematics or timesheet data into hours by pay code, with anything outside the written rules flagged for review.
Roll last period forward, apply what changed, and produce drafts for a qualified person to check and sign.
Multi-step approvals with reminders, delegation when someone is away, and a record of who decided what.
Bots that key approved data into older or locked-down applications, with retries and a log of every result.
Documents and data arrive from mailboxes, folders, exports or other systems and are captured before anything else happens.
Values are extracted, then confirmed against your system of record rather than trusted because they were legible.
Only items that fail a check reach a person, with the source document and the reason shown side by side.
Approved items move on to the people and systems that need them, and every decision is recorded.
Clients are described by type. We do not publish client names.
The problem. An invoice tool was miscoding a share of invoices with no indication of which ones.
What we built. Two independent readers plus a job-cost lookup decide what a person needs to see; unresolved items go to the right project manager.
The problem. Documents arriving by email and fax were filed by hand into matter folders.
What we built. A capture step that records every incoming item exactly once, followed by filing with a review path for anything ambiguous.
The problem. Weekly driver hours were worked out by hand from inspection records and dispatch tickets.
What we built. A rules engine that calculates hours by pay code and a review app where dispatch approves and exports the results.
What we build with: Power Automate · Power Automate Desktop · AI Builder · Azure AI Document Intelligence · Power Apps · Dataverse · SharePoint
It depends on the documents, which is why we test on a sample of yours before committing. More important than the rate is that the system flags the items it is unsure about, so errors are caught before they are posted.
It goes to a review queue with the reason, and the right person is notified. Nothing is silently dropped, and failures raise an alert rather than waiting to be noticed.
No. We work with the systems you already have, through their APIs where they exist and through desktop automation where they do not.
You do. It runs in your Microsoft tenant under your licenses, and we hand over documentation so your team or another partner can maintain it.
A focused workflow is typically delivered in a few short sprints, each ending with a working demonstration on your own documents.
Free 30-minute call. No sales pitch. We'll tell you honestly what we would do and whether we are the right fit.
