Zudu - Enterprise Voice AI Platform

The Problem

Zudu needed backend engineering for a voice AI platform connecting live audio, speech services and business workflows. The work needed to support session handling, language-aware provider selection and call analytics while keeping consent and data-handling controls consistent across call handlers.

Our Approach

The contribution covered a FastAPI voice-processing pipeline, WebSocket audio sessions, Deepgram speech-to-text integration and ElevenLabs speech output. Language and locale settings inform provider selection; supported languages depend on the configured provider and model and need testing with representative callers. Shared middleware handles controls such as recording encryption, consent flags and retention rules. A Next.js dashboard surfaces call analytics and session health. This describes the engineering contribution, not independent certification of the platform's regulatory compliance. Provider agreements, deployment settings and operating procedures need their own review. End-to-end response latency also depends on the network, speech detection, model, tools and speech output; no independently documented latency benchmark is asserted here.

Pipeline Breakdown