AI-Powered Industrial Incident Analysis and Root Cause Automation
The Challenge
Industrial incident investigations relied on manual and inconsistent data collection. Witness statements often remained unstructured, slowing root cause analysis and corrective action planning. The customer, a U.S.-based occupational safety copilot backed by private equity, aimed to modernize this process with an AI-guided digital system that reduced human bias, accelerated investigations, and prevented repeat incidents.
Hypothesis
A unified AI-driven investigation system could standardize data collection, guide investigators through consistent workflows, and convert unstructured witness inputs into actionable insights. Automating incident intake, validation, and corrective recommendations would shorten analysis cycles, improve accuracy, and maintain compliance with safety and regulatory standards.
Execution
Tatras designed and built an enterprise-grade platform that included:
- Reactive mobile interfaces for on-site data collection
- Data ingestion modules for structured and unstructured inputs
- AI-assisted Root Cause Analysis (RCA) with automated recommendations
- Compliance-ready report generation with traceable timelines
Outcomes
The platform transformed investigation data into early warning intelligence, significantly reducing manual work and improving accuracy in identifying root causes. It enabled proactive mitigation of recurring safety risks and faster generation of compliance reports. The solution is now deployed by large industrial enterprises across the U.S., supporting safer operations and stronger compliance culture.
Project Highlights
From manual investigations into structured AI workflows