Voice AI: Rebuilt
to Production.
A legacy voice AI platform rebuilt from scratch, establishing high-speed sub-second performance and enterprise-grade reliability from day one.
The Brief
The client's existing voice platform was a duct-tape stack: fragile data capture, unreliable audio pipelines, and no observability. The founding team needed a production-grade rebuild — fast — without disrupting the live product.
VMG Systems came in as a Principal AI Infrastructure Advisor. The mandate: strip it down and ship something that lasts.
The Scope
5 services. Zero ClickOps.
- React Native with native background audio persistence
- FastAPI backend — async Python, clean LLM abstraction
- Gemini AI pipeline with Langfuse observability from day one
- Next.js admin dashboard
- GCP infrastructure — Terraform-managed, zero manual config
The Method
Clean Slate Protocol
Every service started from a codified spec. IaC before any feature code. A Plan → Act → Validate loop on every task. AI eval datasets built on day one so accuracy regressions surface before users do.
Langfuse was deployed before the first feature shipped. Every Gemini call logged with inputs, outputs, and latency from day one.
What Shipped
The rebuilt platform shipped as a resilient Canary Launch. Background audio persistence — previously unreliable — runs natively. Every AI call is logged with inputs, outputs, and latency. The stack is fully reproducible: any engineer can tear it down and redeploy from Terraform.
Your infrastructure. Same standard.
Let's talk about what's broken.
Or email hello@vmg.systems