Business Automation
AI workflows live in production in 2–4 weeks
Not a six-month transformation program. We find the manual process burning the most hours, automate it with AI, and have it running in production — with an audit trail — inside a month. Then we do the next one.
What automation has done for our clients
What we automate
The four workflows that eat SMB back offices
If your team is copying data from one place to another, a machine should be doing it. These are the patterns we’ve automated most — but the honest answer is: bring us the process, and we’ll tell you if it’s automatable and what it will save.
Dispatch Automation
Incoming jobs parsed, prioritized, and assigned to the right person or crew automatically — by skills, location, and load — instead of waiting on one coordinator’s inbox. Our field-services client assigns work 75% faster, and nothing falls through the cracks because every job is tracked from intake to completion.
Order Intake
Orders arrive as EDI files, emailed PDFs, spreadsheets, and portal downloads — and someone re-keys them all. We automate intake end-to-end: AI reads the document, validates SKUs and pricing against your ERP, flags exceptions for a human, and books the clean ones straight in.
Invoice & Document Processing
Supplier invoices, pro forma invoices, packing slips, POs — AI extracts the line items, matches them to your records, and routes exceptions for approval. We run this in production today: Claude-powered document parsing that turns a PDF into structured ERP data in seconds.
Reporting Automation
The Friday-afternoon spreadsheet ritual, retired. Scheduled jobs pull from your systems, build the workbook — formatted, formula-driven, ready for finance — and email it to the right people automatically. One client’s monthly storage-billing workbook now builds itself from 40,000+ rows of data.
Why 2–4 weeks is realistic
We automate one workflow at a time, on proven plumbing
Most automation projects fail by trying to boil the ocean. We don’t. Each engagement targets one workflow with a measurable baseline — hours per week, error rate, turnaround time — and ships on our production-tested pipeline (the same engine behind Automate): intake, transform, deliver, log.
AI does what AI is good at — reading messy documents, classifying, extracting, drafting. Deterministic code does the rest. And every run is logged, so when someone asks “what did the system do with order 4471?”, there’s an answer.
- Week 1 — map the workflow, gather real sample data, define the exception rules
- Weeks 2–3 — build and test against real historical documents and orders
- Week 3–4 — run in parallel with the manual process, then cut over
- Ongoing — monitored under your managed plan; refinements included
What’s the most repetitive job in your back office?
Tell us in the free assessment. We’ll tell you what it costs you per year, whether it’s automatable, and exactly what we’d build.
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