Feature
Detect Objections, Opportunities, and Hesitation as They Happen
Tonvo flags critical conversation signals the moment they surface — objections, buying intent, hesitation, and topic shifts — so you always know what matters most.
Try Tonvo FreeHow It Works
Pattern-Matched Intelligence from Every Utterance
Tonvo runs each transcript segment through a signal classification model trained on thousands of annotated sales, support, and meeting conversations. The model recognizes linguistic patterns associated with objections ('we're not sure about the timing'), buying intent ('what would implementation look like?'), hesitation (long pauses, hedge words), and more. Detected signals are categorized, timestamped, and displayed as color-coded badges alongside the live transcript.
Key Benefits
Act on Signals Before They Fade
Real-time signal badges ensure you address objections and capitalize on buying intent the moment they appear, not minutes later when the window has closed.
Surface Hidden Opportunities
Many buying signals are subtle — a question about implementation timelines or a mention of budget approval. Tonvo catches what human ears often miss.
Track Signal Trends Across Calls
Aggregate signal data over time reveals patterns — which objections recur, which competitors appear most, and where deals stall in the pipeline.
Who Uses This Feature
- Sales teams identifying buying signals during pipeline calls
- Revenue leaders tracking common objection patterns across the team
- Negotiators detecting hesitation and concession openings
- Product managers capturing feature requests mentioned in customer calls
- Partnership managers spotting competitive intelligence in conversations
Under the Hood
Multi-Class Signal Classifier
The signal detection engine uses a fine-tuned transformer classifier that assigns one or more signal labels to each transcript segment. Training data includes over 50,000 annotated conversation excerpts spanning sales, support, and internal meetings. The model outputs a probability distribution across signal classes, and only signals exceeding a configurable confidence threshold are surfaced. A post-processing layer deduplicates overlapping signals and merges related detections into unified signal events.
Frequently Asked Questions
What types of signals does Tonvo detect?
How does signal detection differ from tone detection?
Can I set alerts for specific signal types?
Are detected signals included in the post-call summary?
Related Resources
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