Risk Intelligence Platform: ML-Augmented Decision Support for Agricultural Risk
0→1 intelligence system | Industrial agriculture | Navigating non-regenerative systems
Project Details
Overview
In 2022, I joined an insurtech being incubated by Hyperion Insurance Group. They had a working pilot - a mobile app for safety inspections on industrial farms. One customer, one use case, but it was working. The challenge was to design the platform architecture that could scale beyond fire safety to become a generalized risk intelligence system for industrial operations. This was a true 0→1 problem - not 'design a feature' but 'design the system that enables many features.'
Problem
Insurance risk assessment for industrial operations requires ingesting documentation from multiple sources:
- Inspection reports from on-site surveys
- Survey data from risk engineers
- Loss prevention findings
- Compliance records
- Photos from site visits
Operational Chaos
Every source has different formats. Different standards. Different levels of completeness.
This isn't clean academic data.
The question was: How do you build a system that can learn from this heterogeneity and generate trustworthy risk scores that insurance stakeholders will actually use to make decisions?