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AI automation for operations
Operations teams lose days to re-typing documents, chasing approvals and reconciling systems. We automate the routine cases end to end and send only the unclear ones to a person, with a log of every step.
Trusted by teams at






Most operations work follows a pattern. Something arrives, someone reads it, checks it against another record, decides and updates a system. The reading and matching parts are what AI does well now. The deciding stays with a person when the stakes or the ambiguity are high.
We build the flow so the model handles what is clear and a person handles what is not, with a one-click way to resolve exceptions. Over time the share handled without a person goes up, and the log shows exactly why.
Where a process is a mess, we fix the process before automating it. Automating a broken step just makes the mistake faster.
Document-heavy back offices
Delivery notes, invoices, forms and emails read, matched and filed automatically.
Teams reconciling data across systems
Records compared and updated with mismatches flagged for review.
Managers building reports by hand
Recurring reports assembled from source systems on schedule.
We measure the current process first, so the result can be compared with a real starting point.
Process observation
Week 1Watch the work, count volumes and time, and collect real documents and exceptions.
DeliverableProcess map and baseline
Design the flow
Week 1 to 2Define what the AI handles, what a person handles and what gets logged.
DeliverableFlow design with exception rules
Build and test on real documents
Week 2 to 5Run the flow on historical documents and measure the matches and misses.
DeliverableTest results
Parallel run
Week 5 to 7Run alongside the manual process until the results agree.
DeliverableParallel run report
Cut over and monitor
Switch to the automated flow with alerts and a runbook.
DeliverableLive flow and monitoring
Typical timeline
A focused operations flow, scoped after the audit call
Stack we build with
n8n · TypeScript · Python · Claude · OpenAI · PostgreSQL · Supabase · Webhooks
Describe one process. We tell you which steps AI can handle and which should stay manual.
Delivery notes and invoices
Read, matched and filed, with unclear cases flagged for a person.
Compliance paperwork
Electronic invoicing and VAT paperwork automated end to end.
Owner visibility
One operating view replacing spreadsheets that only one person understood.
A measured baseline and a flow tested on your real documents.
Week 1
Process map and baseline
Volumes, time per item and the top exception types, measured on the current process.
Week 2
Flow design
What the AI handles, what goes to a person and the rules for both.
Week 3 to 4
Test on real documents
The flow run on historical items, with matches and misses reported.
Day 30
Parallel run plan
How and when the automated flow runs beside the manual one.
Achieved results only. Clients that have not agreed to be named are described instead.
Ordrix, restaurant supply chain
Incoming delivery notes and invoices are read and matched automatically. Only the unclear cases reach a person, and the review team went from re-typing everything to spot-checking exceptions.
Pilote EMC, French construction
Electronic invoicing and subcontractor VAT compliance automated end to end, and an AI that answers far more inbound calls and leads than the team could handle manually.
Addictest, international education
A matching engine that pairs students to universities, an AI writing tool for CVs and cover letters, and an operating system that gives the CEO visibility without living in spreadsheets.
We do not sell fixed packages sight unseen. The number depends on how many systems the work touches, and the audit call tells you that number before you commit to anything.
Single workflow
Low four figures
One focused workflow live in one to two weeks, with error handling, retries and monitoring built in from day one.
Full system
Scoped after an audit call
AI steps, monitoring and integrations across several systems, typically four to eight weeks. No template price, because scope drives the cost.
Embedded engineer
From $60,000/year
A dedicated engineer building and maintaining the work inside your team, instead of a scoped project.
Book a free audit call and leave with a process map and a scoped first flow.
Book a free audit callA 30 minute call. Describe the process and volume, and we tell you what can be automated and what should stay with a person.
In this call, we'll walk through your project scope, timeline, and goals - so we can both check if we're a fit. No obligation, no slide deck, just a working session.
Don't want a call? Email walid@ayautomate.com
“The team is super fast - sometimes we had to slow them down. We managed to scale the company without investing into hiring.”

Elie Salame
COO, Adstronaut.io
We've created products featured in
Walid Boulanouar
View LinkedInThis call is for teams ready to move. If that's you, pick a time.
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FAQ
It depends on your documents, so we test on a sample of your real ones before committing. Unclear cases go to a person with a one-click way to resolve them, so accuracy problems become exceptions, not errors in your systems.
The item goes to an exception queue for a person. Every decision, automated or manual, is logged.
No. We connect to what you run through APIs, exports or database access. If a system offers none of those, we say so before building.
A single focused flow starts in the low four figures. Multi-system builds are scoped after an audit call. Use the automation payback calculator to estimate payback time.
Yes, through the automation maintenance plan, or your team can run it from our runbook.