Stop rekeying the same data into five different places.
Someone on your team reads a form, an email or a PDF and types it into your CRM, your accounting system and a spreadsheet — the same record, three times, drifting apart as they go. YesAI Automation reads the input once and writes it into every system it belongs in, accurately, with checks. The re-keying just stops.
- Reads forms, emails, PDFs and spreadsheets — writes to your systems
- Validation on every record; anything odd goes to a review queue
- Done-for-you and maintained — first workflow live in 2–3 weeks
Where the data comes from
Part of YesAI — Australia's AI automation consultancy
Manual data entry is slow, dull — and quietly wrong.
It is the task nobody puts on their CV. Copy the customer's details off the enquiry form into the CRM. Type the invoice numbers off the PDF into the accounting system. Paste the weekly figures from four dashboards into the master spreadsheet. Re-enter the order that came in by email so it exists in the system that actually ships it.
It eats hours, it is the first thing to fall behind when the team is busy, and it is where the expensive mistakes hide — a transposed number, a wrong customer, a record that made it into one system but not the other. And because a human did it, everyone assumes it is right.
Three copies of the truth is the same as none.
The real damage isn't just the time. When the same record has to live in three systems and a person keys it three times, the three copies drift. The address gets updated in the CRM but not the accounting system. The order quantity gets fixed in the spreadsheet but not the portal. Now nobody knows which number to trust.
Read once. Check. Write everywhere.
Every data-entry automation we build runs through the same four steps.
Read the input
The automation picks up the record wherever it lands — a submitted form, an inbox, an uploaded PDF, a dropped CSV, a new order — and pulls out the fields that matter.
Understand it
The AI step handles the messy reality: an abbreviated supplier name, a missing field, a date in the wrong format, the same customer spelled three ways. It maps the input to your fields.
Check it
Validation runs on every record — totals add up, formats are right, required fields are present, duplicates are caught. Anything that fails goes to a review queue, not into your live data.
Write it
The clean record is written into every system it belongs in — CRM, accounting, spreadsheet, database — mapped correctly each time. One entry, one source of truth, no re-keying.
The re-keying jobs that pay off first.
If your team types the same thing into more than one screen, it's a candidate.
Form → CRM
Enquiry and intake forms captured straight into your CRM — enriched, de-duplicated and assigned — instead of copied across by hand.
PDF → system
Invoices, dockets, applications and contracts read automatically, the key fields extracted and validated, and the data filed where it needs to go.
Email → record
Orders and requests that arrive by email turned into structured records in the system that actually processes them — no copy-paste.
Spreadsheet cleanup
Numbers pulled from every source into one clean sheet, formats normalised and duplicates removed, without anyone touching a cell.
System-to-system sync
A record keyed once and pushed to every system it belongs in, kept in step so the copies never drift apart.
Order & portal entry
Orders re-entered from portals or supplier emails into your own systems automatically, with the odd ones flagged for a quick check.
Do the sums on one task first.
Pick the one record your team keys into more than one place. Multiply the minutes by how often it happens. That number is usually the surprise. Tell us the task and we'll put a real figure on what automating it would save.
An automation with an owner is one that keeps working.
You could build a form-to-CRM connection yourself in an afternoon. The problem is what happens next month: the form adds a field, the CRM changes an API, a supplier tweaks their invoice layout — and the connection silently stops mapping things correctly. Nobody notices until the data is already wrong.
Because we run your data-entry automations as a managed service, YesAI Automation is the owner. We monitor them, we catch the failures early, and we fix them when something upstream changes — which is why the accuracy and the time savings actually last, rather than lasting until the first thing changes.
Book a consultation to talk it through.
What you provide
- Access to the systems the record moves between (we set up secure, scoped credentials)
- One person who knows the current process, for the scoping call
- Sign-off on the field mapping before it goes live
What we provide
- The full build — reading, AI mapping, validation and writing
- An exceptions queue so nothing wrong flows through
- Monitoring, maintenance and support when systems change
- A monthly summary of records processed and hours saved
Data-entry automation, answered.
What is data-entry automation, exactly?
It is software that reads information from wherever it arrives — a form, an email, a PDF, a spreadsheet, an order — and writes it into the systems where it belongs, correctly, without a person retyping it. YesAI Automation builds and runs it for you as a managed service. The AI step is what makes it work on real, messy input: it can read a slightly different product name, clean up an address, or flag a record it is not sure about instead of guessing.
How is this different from a macro or a simple Zap?
A macro or a basic Zap moves clean, predictable data between two apps. Real data entry is rarely clean — the supplier name is abbreviated, a field is blank, the date format changes, the same customer is spelled three ways. We add an AI step that handles those judgement calls, plus validation and an exceptions queue so nothing wrong flows through silently. And because it is managed, when a form adds a field or an app changes, we fix it — the Zap does not just quietly break.
How accurate is it compared with a person keying data?
For structured fields it is typically more accurate than manual entry, because it does not get tired, distracted or bored on the 200th record. We build validation into every workflow — checking totals, formats and required fields — and anything that fails a check is routed to a human review queue rather than written blind. You get the speed of automation with a safety net, not a black box.
Will it work with our existing systems?
Almost always. We connect to spreadsheets, CRMs, accounting tools, databases, help desks and hundreds of SaaS apps through their APIs. Where a system has no API — an old line-of-business app, a supplier portal — we can often drive it through the browser the same way a person would. See our integrations page for the common ones.
How long before a data-entry workflow is live?
Most first workflows are live within two to three weeks of the scoping call. We start with the single re-keying task costing you the most hours, prove the time saved, then expand to the next one. You are not signing up for a six-month build before anything works.
What happens when the automation is not sure about a record?
It never guesses into your live systems. Anything that fails validation or looks ambiguous goes to an exceptions queue for a person to check in seconds — approve, correct or reject. Over time we tune the rules so the queue shrinks and the routine records just flow through. You stay in control of the edge cases; the boring 90% stops touching a keyboard.
Reclaim the hours your team spends retyping.
Tell us the one record that gets keyed into more than one system. We'll tell you whether we can automate it, what it would take, and what it would save — free, no obligation.
Related automations
Data entry is rarely the only re-keying job. Here's where else AI takes the manual work off your team.