Post weekend orders into the ERP
Every Monday the agent takes the weekend order export and enters each one into the ERP, flagging the handful that need a human decision.
Hands Free Data Entry
Your AI employee reads records from a spreadsheet, export, email, or PDF and types them into any web or desktop application, including tools with no API. Every field is checked against the source before submission, and anything incomplete or ambiguous is set aside in an exception report instead of entered wrong. Recurring entry jobs run on a schedule with the approval checkpoints you choose.
Copying data from one system into another is the most repetitive work in any business: orders into the ERP, leads into the CRM, invoices into the accounting tool. Your AI employee does the typing. It reads the source, opens the target app, and enters each record the way a careful human would.
Sources can be anything the agent can read: a spreadsheet, a CSV export, an email thread, a PDF, a web dashboard. Targets can be anything it can operate: web apps through browser automation, native desktop software through the companion app. The same run can span both.
Accuracy comes from checking, not hoping. The agent validates each field against the source before submitting, flags rows that do not fit, and pauses for your input on anything ambiguous instead of guessing. Every submission is logged with the record it came from.
Because the agent operates real interfaces, nothing about your tools needs to change. The aging ERP without an API, the vendor portal with no export, the internal tool nobody can integrate: if a person can type into it, your employee can too.
AI Agents That Do the Typing
Data entry automation turns a stack of records into completed entries in your system. The agent reads each source record, navigates to the right form, fills every field, submits, and verifies that the entry landed before moving to the next one.
It works record by record at machine pace and does not get tired on row 300. What costs a person an afternoon of mechanical work runs in the background while your team does something that needs a human.
From Spreadsheet to System of Record
The most common job is the simplest: a spreadsheet of rows that needs to end up inside a business system. Hand the agent the file and the destination and it enters every row, mapping columns to fields the way you described.
When a row is incomplete or contradicts what is already in the system, the agent does not push it through. It collects the exceptions into a report so a human decides only the cases that genuinely need judgment.
Works in Apps With No API
Most data entry pain lives in tools without integrations: legacy ERPs, government and vendor portals, internal software. Because your employee operates the actual interface through the browser or the desktop companion app, integration is not required.
A single workflow can pull from a web dashboard, enter records into a native desktop application, and confirm results back in a spreadsheet, all in one unattended run.
Checks Built Into Every Run
Each field is validated against the source before submission. Totals can be checked after a batch. Anything that does not match becomes an exception for review instead of a silent mistake in your books.
The approval gateway adds a human checkpoint exactly where you want one: approve every submission, approve once per batch, or let routine entries flow and gate only the irreversible ones.
Runs on a Schedule or a Trigger
Recurring entry jobs become standing instructions: every morning, take yesterday's orders and post them to the ERP. The agent runs the routine unattended and posts a summary with the exception list.
Backlogs work too. Point the employee at the pile, define the mapping, and let it grind through while the activity feed shows progress in real time.
How It Works
Your AI employee reads records from any source and types them into any web or desktop application, validating each field and flagging exceptions for review.
Data entry runs on the same foundation as browser and desktop automation. The agent opens the source, reads each record, navigates the target application, and fills the form field by field. After submitting, it verifies that the entry landed correctly before moving on, and it logs every record to the activity feed.
Exceptions are the heart of the design. Anything incomplete, contradictory, or ambiguous is set aside and reported instead of entered. Combined with the approval gateway, you choose exactly how much human oversight each job gets, from reviewing every submission to skimming a nightly summary.
Use Cases
Move leads from forms into the CRM
Form submissions and event lists become clean CRM records with the right owner, source, and tags, entered minutes after they arrive.
Enter supplier invoices into accounting software
The agent reads each invoice, enters it into the accounting tool with the right details, and queues anything unusual for review.
Migrate records between two systems
When switching tools, the employee enters historical records into the new system, preserving fields that the official importer drops.
Keep product listings consistent across marketplaces
Price and stock changes get entered across every marketplace dashboard, so listings never drift out of sync.
Comparison
| Before | After |
|---|---|
| Hours of copying between systems every week. | The agent types it in while your team does real work. |
| Manual entry means typos that surface weeks later. | Every field is validated against the source before submission. |
| Legacy tools without APIs stay manual forever. | The agent operates the real interface, no integration needed. |
| Backlogs sit untouched because nobody has the time. | Point the employee at the pile and review the exception report. |
FAQ
How accurate is automated data entry?
The agent validates every field against the source before submitting and verifies the entry after submission. Records that do not match or are ambiguous become exceptions for human review instead of being entered wrong.
What sources can it read?
Spreadsheets, CSV files, PDFs, emails, web pages, and exports from other tools. If the agent can open and read it, it can use it as the source for an entry run.
Does the target system need an API?
No. The agent operates the real interface, filling forms in web apps through browser automation and in native desktop software through the companion app. Tools with no integration story work fine.
What happens with ambiguous or incomplete records?
They are set aside and collected into an exception report, or the agent pauses and asks you, depending on how you set it up. The agent does not guess on data that goes into your systems.
Can it run unattended on a schedule?
Yes. Recurring entry jobs run on whatever schedule you set, and every run produces a logged summary. Approval gates still apply wherever you configured them.
How is this different from RPA data entry bots?
RPA bots replay fixed clicks and break when a form changes. Your AI employee reads the screen each time and adapts, so a moved field or a new dialog does not end the run. You also describe the job in plain language instead of building a flowchart.
How are logins and credentials handled?
The agent uses sessions you approve through the companion app. Credentials are stored securely and never appear in logs or transcripts.
Can it handle a large backlog?
Yes. The agent works through the pile record by record and keeps going until it is done, logging progress as it goes. You review the exception report at the end rather than every row.
Monday mornings used to be three hours of retyping weekend orders into our ERP. The agent now does it before I sit down, and I just read the exception list with my coffee.
Where Hands Free Data Entry fits
Hands Free Data Entry is part of How they use your computer.
Your AI agent operates your browser and desktop apps the way a human would. Navigate web apps, fill forms, click buttons, move files, and complete multi-step workflows across any application. Install the lightweight companion app and your employee gains access to your entire machine.
- How they use your computer: Control any browser or desktop app.
Read the guide
More in Desktop Control
- Browser Automation: Most automation tools can read a public web page and stop there. The moment a task needs a real login, a multi-step form, or clicking through an actual workflow, they fall over. Browser Automation gives an employee a real browser on your own machine, driven through the desktop companion app, so it can navigate, click, type, and pull data out of sites the same way you would, including the ones that live behind a sign-in.
- Computer Controller: Most AI tools stop at the browser. The moment work lives in Photoshop, Excel, Logic, Final Cut, or a native app with no API, they're stuck. Computer Controller is what lets an employee step outside the browser and operate your actual desktop, real mouse, real keyboard, real screen, through the companion app running on your machine.
- Proactive Employer Messaging: Your AI employee does not wait for you to check in. When it finishes a task, hits a blocker, or needs a decision from you, it sends the update itself, straight into the same chat thread you already use with that employee. No separate inbox, no polling a dashboard to see if something happened.
- Automatic File Organization: Your AI employee sorts, renames, and files documents on your own computer through the Sistava Desktop Companion app: reading what is in a folder, working out what each file is, and moving it where it belongs using the naming convention and folder structure you describe in plain language. File access stays inside your home folder, and every move, rename, or write is recorded in the activity feed so you can see exactly what changed.