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Cover image for ## Case Study 1: AI
## Case Study 1: AI Phone Receptionist **Tagline:** A 24/7 voice AI that handles calls, books appointments, and takes payments — without a human. --- **The Challenge:** Service businesses lose significant revenue when calls go unanswered outside business hours or during peak times. Hiring and training front-desk staff is expensive, inconsistent, and doesn't scale. Most small and mid-size operations simply miss calls — and those missed calls are missed revenue. **The Solution:** - Built a voice AI system using Twilio/Telnyx for telephony and Claude API for real-time natural language understanding, capable of handling inbound calls end-to-end - Integrated appointment booking logic directly into the call flow — callers can schedule, reschedule, or cancel without speaking to a human - Connected Stripe for in-call payment processing and n8n for backend orchestration (CRM updates, confirmation emails, Slack alerts) - Deployed via FastAPI with webhook handlers for call events, SMS follow-ups, and fallback escalation to a human agent when needed **The Results:** *(Estimated based on system design and architecture — not from a specific client engagement)* - **100% call coverage** — system designed to handle unlimited concurrent inbound calls with no wait time or missed calls - **~70% reduction in front-desk workload** — routine calls (booking, FAQs, payments) handled without human intervention - **Estimated 4–6 hrs/day recovered** per staff member previously tied to phone duties **Tech Stack:** `Twilio / Telnyx` · `Claude API (Anthropic)` · `n8n` · `FastAPI` · `Python` · `Stripe` · `PostgreSQL` · `Redis`
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Cover image for Kazfen Lead Capture Engine —
Kazfen Lead Capture Engine — AI Intake System for Roofing Contractors Built the lead intake layer powering Kazfen’s AI pipeline. The system captures homeowner requests, structures job data, and feeds the AI engine for qualification, prioritization, routing, and follow-up automation. Captured signals include roof type, urgency, location, insurance status, inspection timing, and service request details. Features: • Roofing-specific lead intake flow • Structured AI-ready data capture • Contractor routing logic • Qualification pipeline trigger system • AI enrichment preparation • Downstream automation workflows • Lead-to-agent architecture This intake layer powers the entire Kazfen automation stack from lead submission to qualification, scoring, SMS workflows, and contractor actions. Stack: FastAPI • PostgreSQL • Claude • Twilio • Stripe
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Cover image for Kazfen Contractor Command Center —
Kazfen Contractor Command Center — AI-Prioritized Roofing Pipeline Built the operational dashboard contractors use daily to manage leads, inspections, follow-ups, and revenue opportunities. The system continuously analyzes incoming leads, prioritizes urgent opportunities, drafts actions, and surfaces what needs attention first. Features shown: • AI Morning Briefing (“do this first”) • Lead prioritization + urgency scoring • Pipeline value + expected revenue tracking • AI-generated recommendations and actions • Lead lifecycle management (new → booked → won) • Contractor review workflows • Natural-language command interface (“Ask Kazfen”) • Roofing-specific intelligence and revenue insights Kazfen acts as an AI operations layer rather than a traditional CRM. Stack: FastAPI • PostgreSQL • Claude • Twilio • Stripe • Render
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