Medical contract management system hero image

AI-native engineering operations

How a medical contract management system shipped features 40% faster with a 42% leaner engineering org.

The client is a healthcare contract management and reimbursement platform. As delivery scaled, slow PR reviews, manual QA, inconsistent documentation, and release coordination created drag. Agoura rebuilt the engineering operating model around AI-native workflows.

~40%Faster feature delivery

9.5 -> 5.5FTE operational footprint

~50%QA automation expansion

The Problem

Distributed delivery, growing friction.

As the platform scaled, engineering workflows got harder to coordinate across distributed teams, slowing the business down at exactly the wrong moment.

Pull request reviews, QA, documentation, and release coordination became persistent bottlenecks. The mandate was to increase velocity, control cost, and protect quality at once.

The Approach

AI embedded across the SDLC.

Agoura implemented an AI-native engineering operating model with AI-assisted development, automated QA and regression testing, AI-powered pull request reviews, and orchestration agents handling operational coordination.

These systems were embedded directly into architecture planning, development, QA, documentation, release coordination, and code review.

Results & ROI

What changed for the client

~40% faster feature delivery across distributed engineering teams.
~50% expansion in QA automation coverage.
9.5 to 5.5 FTE operational footprint - ~42% leaner.
Equivalent delivery capacity preserved with the smaller team.
AI-assisted standards validation and security review in place.
Scalable AI-native workflows built for long-term efficiency.

Agoura rebuilt our engineering operations for an AI-native era. We ship faster, run leaner, and execute with less friction across the entire org.

Project manager, medical contract management system