workflow: data entry

You're paying skilled people to be a copy-paste bridge between systems

The order arrives by email. Someone retypes it into the ERP. Then into the tracking spreadsheet. Then into the customer's portal. Three systems, one record, zero new information created — and one typo away from shipping the wrong thing. We install a system that reads what arrives, extracts the fields, writes them everywhere they need to go, and sends your team only the records that genuinely need a human call.

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the manual version

Where the time actually goes

Watch one record cross your desk. An order, an intake form, a shipment confirmation, a policy update — it lands as an email, a PDF, or a row in someone else's portal. A person reads it, alt-tabs to system one, and starts typing. Vendor names get looked up. Dates get reformatted. Codes get remembered or guessed. Then the same person opens system two and does it again, slightly differently, because the fields don't match.

Run the math on your own volume. If a record takes four minutes to key into two systems and your team handles sixty a day, that's four hours of typing daily — a half-time hire whose entire output is moving data that already existed. And the typing is the cheap part. The expensive part is the drift: the shipment that went to the old address because only one system got the update, the two databases that disagree about the same customer, the afternoon someone loses each month reconciling them.

None of this work requires judgment. It's reading, transcribing, and cross-checking, and all three are things software now does with a full audit trail.

The retype itself: fields a machine already produced, typed back in by hand, once per destination system
The fix-ups: date formats, name casing, SKU lookups, and codes translated between systems from memory
The double entry drift: systems that slowly stop agreeing because updates only land in one of them
The cleanup: reconciliation sessions and 'which system is right?' debates that exist only because humans key inconsistently

agentclaw · workflow run

$ claw run invoice-intake

→ 47 documents queued

→ extracted · matched · posted

✓ done in 3m 12s · 0 exceptions escalated

the automated version

Extraction, sync, and a human only at the exceptions

Three stages, running continuously, inside the tools you already own. Nothing changes for the people sending you data.

01
Capture and extraction
An agent watches every intake point: the shared inbox, the web form, the portal, the folder where scans land. Each document gets read on arrival — emails, PDFs, spreadsheets, photos of paper forms. The agent pulls out the fields you care about, normalizes them into your formats (your date style, your SKU codes, your naming conventions), and validates each one against your reference data before anything moves.
02
Sync and write-back
The structured record gets written to every system that needs it: CRM, ERP, accounting, the tracking sheet, the client portal. Before writing, the agent checks whether the record already exists, so updates land as updates instead of duplicates. Systems with APIs get direct writes; systems without them get clean import files or entry through the same screens your team uses. One source event, every destination in agreement.
03
Exception review
Anything the agent isn't sure about stops before it's written: a field below the confidence threshold, a customer that matches two existing records, a value that fails a business rule, a document in a layout it hasn't seen. Each exception goes to the right person with the original document attached, the problem spelled out, and a one-click fix. Your team's decisions feed back into the rules, so the queue shrinks over time instead of growing.

Signs it's time to automate this

You don't need all six. Two or three is usually enough to make the math work.

The same information gets typed into two or more systems by hand, every day
Your 'integration' between two systems is a person exporting a spreadsheet and re-importing it
Entry backlogs pile up whenever one specific person is out sick or on vacation
Two systems regularly disagree about the same customer, order, or shipment, and someone has to reconcile them
You've hired, or are about to hire, someone whose job is mostly keeping up with keying
A copy-paste error has already reached a customer: wrong address, wrong quantity, wrong price

Straight answers

Our software is old and half of it has no API. Will this still work?+

Usually, yes. Where an API exists, the agent writes directly. Where it doesn't, it produces clean import files in the exact format your system expects, or works through the same screens your team uses today. The honest caveat: screen-level automation is more fragile than an API, so we scope it carefully during the audit and tell you plainly if one of your systems makes the economics bad.

What happens when the AI misreads a document?+

It will, sometimes — smudged scans and creative supplier formats exist. That's why nothing uncertain gets written. Every extracted field carries a confidence score, and anything below your threshold, or anything that fails a validation rule, stops in the exception queue with the original document alongside for a human to confirm. You set the threshold. Cautious teams start by reviewing everything and loosen it as the error log stays clean.

Can I do this myself?+

A simple version, yes. If your data arrives in consistent formats and you're mapping fields between two modern tools, a Zapier-style connector plus our free data cleanup prompt pack will get you moving, and the rest of the free skills library shows you how. DIY breaks down where the real cost lives: messy documents, duplicate detection across systems, conflict resolution when two records disagree, and maintenance when a sender changes their layout. A DIY pipeline that fails silently doesn't stop entering data — it starts entering wrong data.

What does it cost?+

Engagements start at $5,000/month, which covers building the workflow and running it: monitoring the queues, tuning the extraction and matching rules, and fixing things when a source format changes. Do your own math first. Count the hours per week your team spends retyping and reconciling, price them at loaded cost, and add what the last data error that reached a customer cost you. If that total is well under the fee, you don't need us yet — start with the free resources and come back when the volume does.

Keep going

AI agents for logistics

BOLs, rate confirmations, and carrier portals: the industry where rekeying between systems runs deepest.

AI agents for insurance brokers

Policy data lives in the AMS, the carrier portal, and the quote sheet — and someone keys all three.

Workflow automation services

How we scope, build, and run automations like this one.

Data cleanup prompt pack

The free DIY starting point if you want to test extraction and normalization yourself first.

Find out what the retyping actually costs you

The free AI opportunity audit traces every record through your systems, counts the touches, and tells you which ones are worth automating first — and which aren't.

Book your free audit

We take on companies ready to invest $5,000+/month. Not there yet? Our free resources are genuinely free.