𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭𝐬:

• After-hours emergency calls resulted in missed, delayed, or inconsistent responses.
• High-stress situations (fires, accidents, security breaches) required instant, accurate incident capture.
• Human-operated call centers were expensive, hard to scale, and error-prone under pressure.
• Critical information was often lost, incomplete, or delayed, slowing emergency response times.
• Needed a 24/7, reliable, and fully automated incident intake system with seamless human escalation.

𝐎𝐮𝐫 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡:

• Designed and built a fully automated, real-time AI voice agent for emergency incident handling.

𝐚) 𝐂𝐨𝐫𝐞 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝

• Natural voice interaction to calmly guide callers during high-stress situations.
• Structured incident data extraction (location, urgency, incident type, severity, contact info).
• Real-time classification & prioritization using AI-driven decision logic.
• Instant escalation pipelines to emergency teams, on-call engineers, or security personnel.
• Fail-safe human handoff when complexity or urgency exceeded automation thresholds.

𝐛) 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞

• Voice AI: ElevenLabs + Vapi.ai + Retell.ai for human-like conversational flow
• Workflow Orchestration: Make.com & n8n for backend automation and system integrations
• Telephony & Messaging: Twilio for call routing, recording, fallback logic, and SMS alerts
• Event Processing: Real-time pipelines for dispatch, escalation, logging, and audit trails

𝐎𝐮𝐭𝐜𝐨𝐦𝐞𝐬:

• Reduced incident response time by 70–80%.
• Enabled 24/7 autonomous incident intake without human staffing overhead.
• Improved first-response accuracy by 90%+ through structured data capture.
• Eliminated missed after-hours calls (~100% capture rate).
• Cut operational support costs significantly.
• Significantly improved emergency handling quality and stakeholder confidence.