A real-time BD agent that listens, suggests, and writes the follow-up.
Built on AWS with LiveKit and Twilio — deep prospect research, in-call suggestions, structured post-call notes, and objective performance evaluation. Every BD rep coached from average to consistent.
Outreach scaled — preparation didn’t.
Manual prospect research
BD reps burnt hours per meeting trawling websites, social activity, recent news, and industry context. The work was necessary, repetitive, and never quite consistent across the team.
Mapping needs to offerings by hand
Identifying a prospect's business challenges and aligning them to the right capabilities was a judgement call made fresh each time — slow, idiosyncratic, and easy to get wrong.
Unstructured talking points
Meeting briefs had no shared shape. Each rep walked in with their own format, their own emphasis, their own gaps — making outcomes hard to predict and hard to coach.
Notes vs. conversation
Reps took notes while trying to lead the discussion. Either the conversation suffered or the notes did — and post-call follow-up depended on whichever lost.
No objective performance signal
Self-evaluation was the only feedback loop. Without an external measurement layer, BD coaching ran on impression rather than evidence.
An AI co-pilot for every BD rep — before, during, after.
Automated prospect intelligence
The agent scans websites, social media, press releases, articles, and recent market activity to assemble a structured profile for each prospect — same depth, same shape, every time.
Tailored talking points
Aligns the prospect's needs against the client's service portfolio and generates a structured meeting brief — capabilities, pain points, opening questions, and likely objections.
In-call monitoring (LiveKit + Twilio)
During calls, the agent listens passively over LiveKit / Twilio, surfaces relevant insights to the rep, checks whether key points have been covered, and flags missed opportunities.
Structured post-call output
Clean meeting notes, action points, and follow-up recommendations are generated automatically the moment the call ends — ready to drop into CRM, no manual write-up required.
Objective performance evaluation
Evaluates communication quality, depth of engagement, clarity of pitch, and coverage of required talking points — turning every conversation into a coaching signal, not just an outcome.
AWS-native, end to end
Agents, orchestration, analysis pipelines, and storage run inside the client's AWS environment. LiveKit and Twilio handle the realtime media; AWS owns the data.
Every rep, prepared — every call, coached.
AI suggestions during live BD conversations
Structured notes generated automatically
Native deployment with Twilio for telephony
Got a similar problem? Talk to us.
Uneven BD prep, manual research, no objective coaching signal — we’ve built realtime agents that change all three. A pod can be in your stack within weeks.