Voice AI Agent for Personalized Task Automation_
A next-generation voice assistant MVP that adapts its personality and knowledge base per user profile, achieving sub-800ms response latency — built to secure early-stage investor interest.
Entity_Client
Stealth-Mode AI Productivity Startup (NDA)
Primary_Role
Lead AI Architect & Backend Engineer
Duration_Log
8 weeks
Resource_Team
1 dev, 1 design
Project_Overview
A stealth AI startup needed an investor-ready MVP for a next-generation voice assistant — one that behaves like a personalized chief-of-staff rather than a generic command executor. The agent needed to understand user context, adapt its tone and suggestions to individual profiles, and respond in near-human time. Built end-to-end in 8 weeks for an investor demo.
Operational_Process
Architected a real-time voice pipeline: Whisper STT → context injection via RAG → GPT-4o LLM → ElevenLabs TTS → WebSocket streaming back to client. Built a user profiling system storing preferences, task history, and schedule context in PostgreSQL with Redis session management for low-latency retrieval.
Core_Capabilities
Performance_Metrics
Response Latency
DATA_POINT: end-to-end
Task Mapping Accuracy
DATA_POINT: voice to structured tasks
Investor Outcome
DATA_POINT: early-stage funding
User Trust Score
DATA_POINT: with visual state indicators
Session Continuity
DATA_POINT: Redis session persistence
MVP Delivery
DATA_POINT: 8 weeks
Conflict_Resolution
Optimized FastAPI with async processing, selected GPT-4o Turbo for speed, and streamed TTS output in chunks rather than waiting for full response generation — achieving consistent sub-800ms latency.
Implemented RAG pulling relevant user profile snippets (preferences, history, schedule) to prime the agent's context window before every response — delivering dynamic personalization at scale.
Built frontend VAD logic that instantly pauses the AI audio stream when the user begins speaking, enabling natural conversation interruption without dead air.
Built robust WebSocket management in React and FastAPI with automatic reconnection, audio chunk buffering, and graceful degradation — maintaining session continuity on poor connections.