The Cost of a Bad Number: Bringing trusted data to your AI agents
The Cost of a Bad Number: Bringing trusted data to your AI agents
Fixing a wrong number takes a day. Winning back trust takes months.
Your team’s data is synced, in one place, and the dashboard looks great, yet everyone still double-checks it in their own spreadsheet. That’s because a bad number doesn’t have to be wrong. It can be misread or just quietly doubted, and either way you pay for it in hours of re-verifying, teams arguing over whose figure is right, and decisions built on assumptions nobody traced back. Add AI agents and it gets harder: they fill gaps confidently with guesses nobody sees, and they’re moving from answering questions to taking action.
In this session, SyncHub and Dashlytix walk through:
Where numbers actually break between the data arriving and someone trusting it
Why the problem usually isn’t the model, it’s what the model doesn’t know
How to model your data so agents get the right answer without guessing
A live demo: ask a plain business question, get the answer, and see exactly where it came from
One practical thing you can do this week to make your numbers checkable
Speakers
Mikayla Hall (host) | SyncHub | Head of Growth
Ben Liebert | SyncHub | Founder
Daniel Taft | Dashlytix | Co-Founder
Ashley Rodan | Dashlytix | Chief AI Officer
Who it’s for
Data practitioners, analysts, and finance or ops leads who build reporting, or rely on it, and are starting to put AI agents on top.
Bring your questions. We’ll leave time for Q&A at the end.