Voice AI Lead Qualifier
An AI calling agent that answers inbound enquiries, qualifies them against real criteria and books the meeting.
- Industry
- Professional Services
- Year
- 2025
- Discipline
- AI, Software
Sample case study. The structure, depth and technical detail match a real InnovativeVibe write-up, but this is not a published client project and no results are claimed.
Challenge
The problem
Enquiries arrived faster than a two-person sales team could return calls. Leads that waited longer than an hour rarely answered, and the CRM filled with rows nobody had spoken to.
Solution
What we built
- Defined the qualification criteria with the sales team first, as a written rubric the agent could be evaluated against.
- Built a voice agent that answers within seconds, asks the qualifying questions and handles interruptions naturally.
- Wired the agent into the CRM so every call writes a transcript, a score and a next action.
- Set escalation rules: anything high-value or ambiguous transfers to a human mid-call.
Design
Interface and experience
The operator console shows a live call feed, the extracted answers as they are captured, and a single button to take over. Confidence is shown honestly rather than hidden.
Development
Technology and architecture
Python services orchestrate speech-to-text, the language model and telephony, with a strict tool interface for CRM and calendar writes. Every run is replayable against a regression set of recorded calls.
- Python
- OpenAI API
- Next.js
- PostgreSQL
- Twilio
- Docker
Features
What it does
Inbound voice answering with sub-second pickup
Rubric-based lead scoring
Live human takeover mid-call
Automatic CRM record creation and transcript
Calendar booking with conflict checks
Follow-up sequence for unreachable leads
Gallery
Screens
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