Operations · The work between the work
AI Data Entry Agent
Does the re-keying, chasing, and compiling nobody was hired for.
Nobody you hired wants to copy the same order into a second system, chase a status across four threads, or rebuild the same report every Monday. That work still gets done — by people you hired for something else.
What it does
Three things it takes off your team.
Data moved between systems without a person re-typing it, and without the errors that follow
Status chased and approvals routed automatically, so things stop stalling in someone's inbox
Recurring reports compiled and delivered on schedule, every action audit-logged
How it works
Three steps, then it runs.
Point it at the systems
Connect the tools the work lives in — CRM, spreadsheets, email, internal APIs. The agent reads and writes them like a teammate would.
Describe the outcome
You state the goal, not a brittle step-by-step script. The agent plans the steps and adapts when something changes.
It runs, you watch
It executes on a schedule or a trigger, escalates the edge cases with full context, and logs every action it took.
Point it at
- Cross-system data entry
- Status chasing and reminders
- Report compilation
- Approval routing
- Back-office reconciliation
Who this is wrong for
If the task changes shape every single time and has no repeatable pattern, an agent has nothing to learn — a person is cheaper. This pays off on the work that is dull precisely because it repeats.
Will it reach production on your workflow?
Six questions, scored out of thirty, against what actually stops automation reaching production. The result is immediate, no email required, and it will sometimes tell you not to hire us.