Every broken call, classified — with the exact fix.
Gap Analysis reads every production transcript, classifies what went wrong into one of five gap types, and tells you the root cause. Zero setup, zero manual review — turn a failed call into a better agent in minutes.
Zero setupRoot cause + evidenceSeverity ranked
Every failure has a name.
Classification turns a vague “the AI didn't work” into a specific, fixable root cause.
Expectation Gap
The AI did something different than the caller expected — redirected to FAQ instead of booking, kept handling instead of transferring. Usually a prompt fix.
Knowledge Gap
The AI didn't know an answer it should have — hours, pricing, location specifics. Usually fixed by adding to the knowledge base.
Policy Gap
The AI gave information that violated business policy — quoted a discount you don't honor, promised a service you don't offer. Fix is a clearer policy statement.
Communication Gap
The AI failed to confirm understanding, repeated itself, or contradicted itself. The caller restated the same request four times. Fix is a confirmation loop.
Execution Gap
The AI knew the answer but failed to act — said "I'll book that" but never called the tool, said "let me transfer" but never handed off. Fix is on the action layer.
Severity-ranked
Every gap is scored Critical → Low, so the fix list is ordered by what's actually costing you money.
From failed call to fix, automatically.
Reads every transcript
Every production call and chat syncs from HighLevel and is analyzed within minutes — no uploads, no tagging, no per-account setup.
Classifies the gap
Each failure is sorted into one of the five gap types with a severity and a root-cause label, so you see exactly what went wrong.
Points to the fix
Root cause plus the exact transcript excerpt as evidence — paired with a prescriptive fix, severity-ranked so you fix what costs bookings first.
What it looks like in production.
Real data. One client. 30 days. A national automotive service chain running Voice AI across 50+ locations.
Frequently asked about Gap Analysis.
Expectation Gap (the AI did something different than the caller expected), Knowledge Gap (the AI didn't know an answer it should have), Policy Gap (the AI gave information that violated business policy), Communication Gap (the AI failed to confirm understanding or repeated/contradicted itself), and Execution Gap (the AI knew the answer but failed to take the right action — book, transfer, capture).
As soon as the call syncs from HighLevel — typically within minutes of the call ending. Gap Analysis runs continuously on every call, so you don't have to remember to check anything. Critical and high-severity gaps surface immediately in the dashboard.
For each gap, SuperLedger recommends a specific action — Update prompt, Add to knowledge base, Clarify policy, or Improve prompting — paired with the transcript excerpt as evidence. You see exactly what the AI said and exactly what to change. Most fixes take less than 5 minutes.
Yes. Gap Analysis classifies failures across both Voice AI calls and Conversation AI chats — same five gap types, same root-cause + fix structure, same dashboard.
The rest of the platform.
Turn broken calls into better agents.
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