Useful automation starts by understanding the real work, before choosing a tool. This guide helps you make that decision with data, tests and clear ownership.
Where it fits your workflow
We build specialized assistants with scoped sources, permissions and oversight. We automate drafts and repeatable actions with limits and approval where needed.
How to plan the implementation
Limit the tools, sources and actions the agent can use. Prepare adversarial examples and require human confirmation for changes involving customers, money or sensitive data.
Before implementation, map the source data, the expected outcome and the person who approves exceptions. Check which systems offer an API and which steps need manual review.
What to measure and when to step in
Set a baseline and monitor verified answers, escalated requests and corrected actions. An automatic outcome is not necessarily a correct one: keep uncertain cases visible and record staff corrections.
Log when the agent is uncertain, uses an outdated source or tries to act beyond its permissions.
AI back-office agent
The agent helps classify requests and prepare back-office actions using business data. Sensitive tasks require permissions and approval before execution.
See how we build it ↗What comes next?
Choose one workflow, document how it works today and note the time it takes and common errors. With that baseline, we can define a small test before expanding the automation.