Recommendation
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Key findings
Top 3 next actions
Step 1 · Pick a customer
You're a Staff PM at a D2C insurer looking at one policyholder's account. Click any of the three sample customers below; the platform joins the profile to a stored policy and (in step 2) to fresh life-event signals.
Step 2 · Pick a life-event bundle
What's happening in this customer's life that the carrier doesn't know? Click any of the three sample bundles below; each is a realistic scenario assembled from the brief.
Selected events (0)
Step 3 · Watch the engine work
Each event flows down the spine: ingest → coverage-gap engine → nudge orchestrator → audit ledger. Live precision, attach probability, and the immutable audit log update as the engine runs.
Idle. Press play to start.
Event spine · live
Live engine state
Events ingested
0
Coverage gap (CAD)
$0
Precision
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Attach P (top)
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Audit log streams in real time
- No events yet. Press ▶ Run the engine.
Step 4 · Recommendation, inputs, outputs
What Lifeline tells the PM. Below: the headline, the inputs that drove it, the processing variables, the drafted CS / customer artifacts, and standardized exports.
01Inputs · what you configured
02Processing · what the engine computed
Coverage: current vs. recommended
Cross-product attach probability
this profilebaseline
Nudge timing (next 90 days)
03Outputs · drafted artifacts
Drafted nudge sequence
CS console preview · what the rep sees on inbound call
04Standardized exports
Everything downloads locally. Nothing leaves the page; this is a static prototype.