I built and shipped Lyzr AI in less than 2 days: a full-stack underwriting copilot that turns loan policy and applicant data into a structured YES/NO recommendation with explanations. The live product at lyzr.archlife.org combines a React frontend, a FastAPI backend, a Firebase-backed data layer, and a Lyzr ADK orchestrator that routes each case through credit, affordability, collateral, compliance, and escalation subagents.
This was not a mockup or a one-screen demo. It was a deployable product surface with real request handling, persistence, and live deployment.
Speed came from keeping the problem tight and the execution path explicit. The system had one job, one primary user flow, and a clean split between presentation, orchestration, and data.
The implementation was simple in the right way: each layer had a clear responsibility, and each responsibility could be shipped independently without turning the project into a tangle.
That included the deployed frontend, backend, database, and live integration path. The result is a real AI product that can be opened, reviewed, and iterated on immediately instead of being described only in slides.
