A real-time BD agent that listens, suggests, and writes the follow-up.
An AI-powered Business Development Agent built on AWS with LiveKit and Twilio — coaching every representative through deep prospect research, in-call suggestions, structured notes, and objective performance evaluation.
The client is a rapidly growing technology services company whose Business Development team regularly engages with prospects to present capabilities, qualify opportunities, and schedule follow-up meetings. Their outreach depends heavily on deep research, tailored messaging, and consistent communication aligned with the company's strengths.
BD teams spent significant time researching prospects — websites, social activity, recent news, industry context — before every meeting. This manual approach led to inconsistent messaging, missed insights, and varying levels of preparedness across representatives. As outreach volume grew, teams struggled to align prospect needs with offerings, support live conversations effectively, and measure performance consistently.
A fully automated AI Business Development Agent was built to conduct deep prospect research, prepare tailored meeting briefs, support representatives during conversations, and monitor BD performance — all deployed securely on AWS and powered by LiveKit and Twilio for real-time interaction.
The platform uses coordinated AI agents that analyse publicly available information, interpret company positioning, align findings with the client's service portfolio, and prepare customised talking points. During calls or meetings, the AI listens in through LiveKit / Twilio, provides real-time suggestions, and evaluates performance. All processing, storage, and orchestration run entirely on AWS for reliability and security.
- ▸Manual research across websites, social media, and news portals before every meeting.
- ▸Identifying business challenges and mapping them to the client's offerings by hand.
- ▸Preparing talking points with no standardised structure across representatives.
- ▸Taking notes during calls while trying to lead the discussion.
- ▸Evaluating own performance without objective feedback signals.
What was built and how it fits together.
Deep prospect research automation
The AI agent scans websites, social media, press releases, articles, and market activity to build a comprehensive profile for each prospect.
Tailored BD briefs and talking points
Aligns the prospect's needs with the client's capabilities, generating structured meeting briefs reps can use immediately.
Real-time meeting monitoring (LiveKit + Twilio)
During calls, the AI listens passively, surfaces relevant insights, checks whether key points are covered, and supports the rep with timely suggestions.
AI-generated notes and follow-ups
Clean, structured notes, action points, and follow-up recommendations produced automatically after each conversation.
Performance evaluation
Evaluates communication quality, depth of engagement, clarity of pitch, and coverage of required talking points.
AWS-native deployment
Agents, orchestrations, analysis pipelines, and storage run securely in the client's AWS environment.
The operational result, measured against the starting state.
- ▸Dramatically reduced preparation time through automated high-quality research.
- ▸Consistent messaging aligned with the company's service offerings.
- ▸Improved BD effectiveness with real-time meeting support.
- ▸Structured notes and follow-ups generated instantly.
- ▸Objective performance insights for representative coaching.
- ▸Higher meeting success rates through better preparation and delivery.