Dataforest

“Working on the WhoCPA AI Voice Agent project was a strong example of how applied Generative AI can deliver measurable business impact when deeply integrated into real workflows. From the very first intro call, it was clear that the client wasn’t looking for an experimental AI demo. Their goal was to replace and scale a critical revenue-driving process — cold calling — without losing sales quality. That set a high bar for latency, speech realism, data accuracy, and CRM/ATS integration. One of the most technically demanding aspects was achieving true real-time voice-to-voice interaction. We had to optimize the entire pipeline — from voice activity detection and speech recognition to LLM reasoning and speech synthesis — to stay below human reaction time. Reaching <450 ms latency consistently required architectural decisions at every layer, not just model selection. Another key challenge was sales intelligence. This was not a generic chatbot. We trained the agent on hundreds of hours of real sales calls, objection-handling patterns, and product-specific nuances using a RAG-based architecture. As a result, the AI behaves like a trained sales rep, not a scripted bot. What I personally value most in this project is that the results were not theoretical. The AI agent matched and in some cases exceeded human sales performance, achieving a 1:1–1.5 sales quality ratio, while operating at a fraction of the cost and with perfect consistency. This project shows how AI can move from “assistive tooling” to a core operational asset. For the client, it unlocked scalable outreach, reduced dependency on human operators, and created a sustainable competitive advantage. For us as a team, it reinforced the importance of combining strong engineering, applied AI, and deep business understanding into one solution.“