Decagon
Bring every one of your AI agent conversations into Rippit. It reads all of them, not a sample, and finds where customers get stuck and where the agent falls short.
Connecting Decagon to Rippit
Rippit reads every one of your AI agent conversations
Brings your AI agent conversations into Rippit so all of it can be read, not a sample. A Rippit admin connects it once. It’s read-only, so nothing changes in Decagon.
- 1
Label every record with AI columns
A model reads each row and applies the judgment you describe, like its topic, its sentiment, or whether it reports a bug. It runs once per record as records arrive.
- 2
Ask questions across every conversation
Ask in chat about what changed or what’s missing, and Rippit reads across the entire set, not a sample.
- 3
Query it as tables
Every conversation is stored as a table you can query and build reports from, so results come back fast and your helpdesk isn’t under analysis load.
- 4
Join it with your other data
Use lookups and rollups to bring in accounts, orders or product usage from other tables, and roll findings up by account, topic or week.
- 5
Run it on a schedule
Turn the analysis into a pipeline that runs hourly, daily, weekly or monthly, and sends the result to Slack or email.
