# Voice AI Product Build | Super Cat > A commercial voice product run as a long hourly engagement rather than a fixed-scope prototype — 247 hours across three months, rated 5.0. Source: https://www.super-cat.tech/portfolio/voice-ai-product Last modified: 2026-10-22 [← All case studies](https://www.super-cat.tech/portfolio)247 hours over three months · 5.0 rating # Voice AI Product Build A commercial voice product run as a long hourly engagement rather than a fixed-scope prototype — 247 hours across three months, rated 5.0. ## The problem A commercial voice product needed to work on real calls, not curated demo calls. The client had already learned that a prototype which impresses in a meeting tells you almost nothing about what happens at volume. ## What we built Voice agent development run as a long hourly engagement rather than a fixed-scope prototype: 247 hours from June to August 2025, iterating against real usage the whole way through. Before: Demo calls are not real calls; Failures only appear at volume; Accents, interruptions, edge cases. After: 247 hours over three months · 5.0 rating.Before - Demo calls are not real calls - Failures only appear at volume - Accents, interruptions, edge cases After 247 hours over three months · 5.0 rating Stack Voice AI AI Agent OpenAI API Python ## Why it holds up The length is the point. A voice product does not fail in the first demo — it fails on the hundredth call, on the accents and the interruptions and the edge cases nobody wrote a test for. Sustained hourly work over months is what lets you find those and fix them. The client left a 5.0 rating: “Cat is a talented Python and AI developer, she has a great attitude, quick learner, and overall fantastic experience!” Related service: [Rent a data scientist](https://www.super-cat.tech/rent-a-data-scientist) ## More case studies Big 4 client · fully on-premise ### Enterprise RAG Chatbot for a Big 4 Accounting Firm Multimodal retrieval over a Big 4 firm’s full compliance library, tuned for citation instead of summary — every answer arrives with its source paragraph attached. - Juniors reading thousands of pages per question - Seniors acting as search engines Read the case → 200k calls/month · 67% booking rate vs 77% human ### 24/7 AI Agent Call Center: 200k Calls a Month Across 60 US HVAC Brands Voice agents orchestrating 200,000 calls a month across 60 US HVAC brands for a 5,000-person enterprise, booking 67% of calls against 77% for human agents — within 10 points of a trained team, around the clock. Built as a product, an AI front desk that answers, books and routes, not a pilot. - Night and weekend calls unanswered - Staffing every shift hard to justify Read the case → US$1M collected in the first 3 months ### AI Payment Collection and Reminders The companion product to the AI front desk: it chases unpaid invoices with polite, timed reminders and a payment link, and stops the moment the customer pays or replies. It collected over US$1 million for the client in its first three months. - Chasing payment is awkward and late - Billable time lost to collections Read the case → Get started ## Talk to the engineer who will build it. You will speak with me directly. Bring the use case, the data and the constraints, and I will give you a straight view on feasibility, effort and the first thing to ship. [Book a call](https://calendly.com/super-chain/catyung)Hong Kong & London time zones