Revenue Discovery
Release a swarm of agents to find the money left on the floor in your CRM, sales calls, and support history, then hand each owner the decision that protects it.
What you can do
Revenue rarely disappears in one dramatic moment. A renewal date drifts past the contract end. A proposal quietly undercuts the current price. A customer mentions the same bug on three calls and nobody connects it to the renewal. The signals are already in your systems, spread across thousands of records nobody has time to read.
It is one of the fastest-ROI uses of AI in a large organization. SPIRITT can put a swarm of agents on it:
- read your CRM accounts, deals, contracts, and orders alongside recorded sales calls and support tickets
- find renewals at risk, mismatched terms, stalled pipeline, and expansion the team has not acted on
- cite every finding with the exact records and customer quotes behind it
- size what is at stake, with the formula shown, so nobody has to trust a black box
- turn the findings into one decision per account, with a proposed owner and a clear definition of done
- publish the result as a live, shareable brief for your managers
Connect Salesforce or HubSpot, add calls from Gong, and support history from Zendesk or Intercom, plus 1,500+ more integrations. The agents work across all of it at once.
Proof: $711k a year in at-risk renewals
Here is an example report for Tenovia Analytics, a simulated B2B fintech with about 200 employees and 200 customers. The company was created in partnership with Era, Eon.io's data infrastructure, so its data behaves like a real, messy enterprise. A swarm of SPIRITT agents went through 5,795 sales calls and support histories and found:
- 3 at-risk renewals worth $711k a year
- $2.56m in pipeline to qualify
- 41 findings, each traced to its source
Each finding comes with a proposed owner, one clear ask, and the records and quotes behind it. All figures come from the simulated dataset. Explore the sample report.
The extra
Discovery is the start, not the end. Schedule the analysis to run every week so new risks surface before the renewal window closes, post each owner's next step to Slack, and write the decisions back to your CRM.
Want the same rigor on your messy SaaS data first? See Turn SaaS Data into an AI-Ready Database.