Smarteeva Risk Management

Risk assessments trigger automatically when a complaint is created — no separate system, no manual handoff
AI-driven risk scoring detects emerging patterns from factual evidence using decision trees and adaptive thresholds
Full FMEA/pFMEA/dFMEA scoring with real-time dashboards that update as complaint data changes

Summary

Evermind™ — a fast-growing European SaaS company — was preparing a full platform redesign: new UI, new navigation, new onboarding, and a rebuilt permissions system. But the engineering team was stuck.Their codebase had accumulated years of async drift — un-awaited promises, deeply nested chains, race-condition hazards, and logic that worked “most of the time… except when it didn’t.”

What you will learn

Smarteeva started with a full async map of the codebase — parsing every function, promise chain, and cross-module dependency.The Editor flagged unstable flows, Debug surfaced non-awaited calls and silent failures, and Review mapped where side effects were leaking across boundaries.Patterns emerged quickly:

  • 47% of async handlers returned before their internal operations finished
  • Several “harmless” utility functions introduced hidden parallel execution
  • Error propagation was inconsistent across 6 core services
  • One legacy module triggered three parallel writes without guaranteeing order