Your agent improves every day.
With real data, not guesses.
Retraining is the panel where you see every phrase your agent didn't understand, which intent it should resolve, and a button to suggest the document that closes the gap. No parallel spreadsheets. No IT projects. Weekly iteration, based on what's really happening in production.
Without retraining, your bot becomes noise. With data, it becomes an ally.
Symptoms we see in conversational AI operations when this module is missing.
You don't know what failed
A customer asked something, the bot replied "I didn't understand" and closed the chat. That phrase disappears. Nobody sees it, nobody fixes it.
Flat or declining coverage
The catalog changes, products rotate, doubts evolve. If you don't retrain, coverage drops month over month.
Complaints that "the bot doesn't understand"
Human tickets increase for queries the bot should have resolved. Rising operational cost, falling NPS.
Every improvement is a project
Requesting a change means opening an IT ticket, waiting a week, and hoping. No autonomy for the business team.
KB without prioritization
Which document to upload first? Which intent to add? Without metrics, everything is opinion and nothing moves.
No traceability
In which conversation did it fail? What had the customer said before? Without context, you can't improve properly.
Data in silos
Conversations in one tool, products in another, KB in a third. Crossing everything is manual and costly.
No export
The team wants to take the data to Excel for review. If the platform doesn't export, everything ends up in screenshots.
Measure. Detect. Fix. Measure again.
Three numbers that matter, calculated automatically.
Total messages received, unrecognized phrases and coverage %. Filters for today, week, month, year, or custom range. The team benchmark is 100% coverage — and this panel tells you exactly how far you are.
- Automatic calculation in each window
- Comparison against historical benchmark
- Top N intents (5, 10, 25, 50)
- Time filter: today / week / month / year / custom
- Exportable to Excel for offline review
- API available for your own BI
The intents your bot should resolve — prioritized by volume.
The platform groups unrecognized phrases into proposed intents and orders them by frequency. So you know what to cover first to maximize the coverage jump: what most people are asking and the bot still doesn't know how to answer.
- Automatic intent clustering
- AI-suggested name (search_product_X)
- Absolute volume and % of total
- History to see improvements post-correction
- Marking of already-covered intents
From failed phrase to corrected document, in one click.
Each missing intent has a "Suggest Doc" button. The AI drafts a document with the real phrases as examples, adds it to the RAG, and leaves it ready for review. The business team approves or edits — without going through IT.
- Auto-generated document draft
- Includes real phrases as examples
- Immediate indexing on approval
- Versioning and rollback
- No IT or code required
What changes when you operate with comprehension data.
Want to see your real coverage?
In the demo we'll show you what the Retraining panel would look like with conversations similar to yours — and where the highest-impact opportunities are.