Cybersecurity
Building an AI
agent for deal
risk and priority
A cybersecurity sales team needed a better way to identify deal risk before it showed up in missed forecasts.
Blind Spot
The forecast missed the nuance sellers were seeing too late.
The company had deal data, call notes, activity signals, and stage history, but no consistent way to combine them into an early risk view.
Managers were finding problems after commit calls, not before them.
Agent
Ombrik built an AI scoring layer around fit, movement, activity, and risk.
We built a custom scoring layer that pulled together CRM data, activity patterns, qualification signals, and deal movement.
The agent flagged risk, surfaced missing context, and gave managers a clearer basis for intervention.
Decisioning
Sales leaders saw risk earlier and coached with better context.
Forecast reviews became more precise, deal inspection improved, and coaching focused on the opportunities where action could still matter.
The system did not replace judgment; it made judgment faster and better informed.
AI scoring layer
Risk Signals
Combined stage movement, activity, fit, and missing context.
AI Agent
Generated deal summaries, flags, and recommended inspection points.
CRM Integration
Pushed scores and context into the team workflow.
Manager View
Created a cleaner surface for coaching and forecast review.
Next Step
Ready to build your revenue operating layer?
Every engagement starts with a strategy call. We map your systems, identify what's broken, and outline the path forward.
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