# Mochi — Voice AI Screening Agent

> Draft case study. Content to be expanded.

## Summary

Mochi is an intelligent voice screening agent built at Maki People that autonomously conducts phone interviews with candidates in real time.

## Context and problem

Screening large candidate pools by phone does not scale with human recruiters.

## My role and ownership

Currently leading Mochi. Personally responsible for:
- Real-time audio orchestration framework (LiveKit)
- Multi-agent decision system (finite state machine)
- Turn-management framework (interruptions, end-of-turn detection, flow)
- Self-hosted LLM cluster powering in-call reasoning

## Technical implementation

### Architecture

- Real-time audio streaming and processing on LiveKit
- Multi-agent decisioning coordinated by a finite state machine
- Turn management for multi-party conversation, interruption handling, and end-of-turn detection
- Self-hosted LLM cluster for low-latency reasoning and dialogue

### Stack

- Language: Python
- Real-time: custom frameworks on top of LiveKit
- AI / ML: self-hosted LLM cluster

## Key decisions and trade-offs

_To be added._

## Outcome and evidence

In production at Maki People. Detailed metrics to be added.

## Links

- Related: https://www.maki.tech