SenseLense

WEBSITE LINK

https://senselense.netlify.app/

Inspiration

Important customer details get lost in scattered notes, forgotten conversations, and disconnected tools. Sales teams already know everything they need to close deals and keep customers happy, but that knowledge lives in the wrong places and disappears at the worst times.

We did not just want to organize that information. We wanted to capture something even deeper than notes ever could. Not just what a customer said, but how they felt when they said it. Because the moment a prospect lights up about payroll solutions, or goes quiet during a pitch, that is the most valuable signal in the entire sales journey. And right now it is gone forever.

SenseLense exists to change that.

What it does

SenseLense transforms raw sales calls into structured intelligence in near real-time:

Transcription: Converts conversations to text with ElevenLabs.
Emotion & Engagement Tracking: Monitors customer signals with Presage.
AI Insights: Generates summaries, key points, and actionable next steps using Gemini AI.
Timeline Fusion: Aligns conversation transcripts and physiological data into a clear, time-stamped view for easy analysis.

How we built it

Backend: Python + Flask
Database: SQLite stores transcripts, mood metrics, and AI outputs
AI Integration: ElevenLabs, Presage, Gemini AI
Sync Engine: Aggregates conversation and physiology into 20-second windows for actionable insights

Challenges we ran into

Synchronizing speech with physiological readings
Correctly labeling speakers (seller vs. client)
Handling inconsistent AI outputs and parsing safely
Testing without live calls using simulated audio + physiology data

Accomplishments that we're proud of

Merged conversation + physiology into a meaningful, interactive timeline
Built an AI pipeline that delivers actionable insights from sales calls
Turned raw call data into structured intelligence sales teams can use immediately

What we learned
Combining multiple AI tools requires careful normalization and error handling
Aggregating signals into fixed windows makes real-time insights actionable
Even minimal AI pipelines can produce high practical value for sales teams