AI Automation Integrations
The tools we connect most often — and what a reliable integration actually needs.
An integration is not a checkbox. It needs authentication, field mapping, retries, duplicate protection and someone who knows what happens when the other system changes. These are the platforms we build with most often.
What makes an integration reliable
A reliable integration does five things well. It authenticates without sharing a personal password. It maps fields explicitly instead of guessing. It handles duplicates before creating a record. It retries transient failures and alerts a human when retries run out. And it logs enough detail that someone can answer "what happened to this lead?" a month later.
Most broken automations fail on one of those five points, not on the tool choice. That is why we scope the data model and failure paths before writing the workflow, and why every build includes a monitoring step and a documented owner.