Prospect well fits ICP with high urgency; pattern-library says 52% of similar calls close.
Evidence chain (3)
- transcript analysisICP fit 0.8826.4
- pattern librarysimilar-call close rate 52.0%13.0
- urgency scorerurgency signal 0.7518.8
voice agent · private pilot
Front Desk is in private pilot. Grading framework is live (ICP fit, urgency, objection type, pattern-library, A-thesis gate). Integrations aren't self-serve yet. Request a pilot, we pair the agent with a scoped call flow. You see the reasoning, not just the outcome.
How well the prospect matches your ideal customer profile based on pre-call data + signals detected in the first 60 seconds.
Deadline pressure, pain intensity, and spoken commitment phrases. Scored continuously throughout the call, not just at the end.
Price / timing / authority / none. Each type triggers a different pattern-library match — the agent does not improvise pricing moves.
Historical close rate of similar calls in your vertical. Drives confidence weighting on every pricing decision.
Mentioned budget, reaction to price anchor, follow-up questions about pricing tiers. Low budget signal → softer offer path.
Rolled up into a single grade on the call record. A-graded calls converted at ≈58% in our 2026 Q1 benchmark vs ≈18% for C-graded.
Same Institute framework that grades PATH trading signals. Every call routes through it in real time. Expand the evidence chain to see which transcript markers drove the grade.
Prospect well fits ICP with high urgency; pattern-library says 52% of similar calls close.
Prospect partially fits ICP with moderate urgency; pattern-library says 28% of similar calls close.
Prospect partially fits ICP with moderate urgency; pattern-library says 12% of similar calls close.
Closes or doesn’t. You review the call transcript manually to figure out why. No cross-call learning. No objection-specific playbook. Your 30th call is no smarter than your 3rd.
Every call graded with full reasoning surfaced. Pattern library learns from outcomes — what closed in crypto SaaS informs what the agent does next time on a similar call. Your 30th call is sharper than your 3rd.
The voice agent reads from the same Institute that grades trades, content, and reports. What it learns feeds the pattern library for every other service. See the full diagram.
The three verdicts above are real calls from the Institute — same framework that runs PATH trades. Want it graded on your own calls? Start the short scoping flow.