AI automation
Automate the Routine, Keep People in Charge of Decisions
The most dependable automations separate the repeatable steps from the judgement calls and put a person at the right checkpoint.
Two kinds of work
Every business process mixes repeatable steps with judgement. Reading a form and filling a table is repeatable. Deciding whether to extend credit to a customer, or how to answer an unhappy client, is judgement. Automation is strongest on the first kind and should assist, not replace, a person on the second.
Design the checkpoint
A human-in-the-loop design places a person where a mistake would be costly or hard to undo. Typical checkpoints are approving a payment run, sending a message to a customer, or changing a price. Everything before the checkpoint can be automated: collecting data, preparing a draft, checking it against rules. The person sees a clear summary and approves, edits or rejects.
Make changes traceable
Good automation leaves a record: what was proposed, who approved it, what changed. This makes errors easy to find and fix, and it builds trust in the system. The NIST AI Risk Management Framework describes the same idea in general terms, treating AI as a risk that organizations should map, measure and manage.
Our approach
MayTech Labs designs automations with a review step and an audit trail as defaults, not extras. The goal is to remove repetitive work while leaving decisions where they belong.
