ISE combines GenAI and traditional AI—including machine learning and text mining—to automate defect analysis, test planning and code investigation. This dual-AI approach lets us go beyond pattern recognition to deliver contextual recommendations that genuinely reflect how your product has behaved across real release cycles.

Absolutely. We designed ISE to integrate seamlessly with your existing defect resolution systems, so there is no need to overhaul workflows your teams already rely on. You get the full benefit of AI-powered sustenance engineering without the disruption of a platform migration or retraining effort.

Orphan defects are defects that have no test scenarios mapped to them, essentially blind spots in your test coverage. ISE automatically flags these gaps so your teams can address them before they become release risks. It is one of the more practical ways we help organizations close coverage holes that traditional approaches miss.

ISE delivers measurable improvements across efficiency, quality and speed—including faster go-to-market, improved CSAT scores, reduced deskilling rates and lower operational costs. By automating the repetitive, time-consuming work of sustenance engineering, we help your teams focus on higher-value activities that actually move the business forward.

While ISE is purpose-built for software product sustenance in general, our engineering capabilities extend to automotive domains, including ADAS and connected vehicle systems. If you are managing complex automotive software with high defect volumes and rigorous certification requirements, ISE's AI-driven sustenance approach is well-suited to those demands.

ISE pinpoints exactly where to start investigating a defect, surfaces similar or duplicate issues and recommends proven resolution approaches—all automatically. In practice, this means your engineers spend less time hunting for root causes and more time fixing them, significantly compressing resolution cycles.

ISE analyzes your test case suites to identify and eliminate redundant test steps, then recommends an optimized test plan based on your actual release defect history. The result is leaner, smarter test coverage, so your teams are testing what genuinely matters without sacrificing quality or confidence.

When experienced engineers leave, they take critical product knowledge with them. ISE captures and operationalizes that knowledge, embedding defect patterns, resolution history and test insights directly into the workflow. This reduces deskilling rates and helps newer team members get up to speed without compromising product quality.

Defect clustering groups related defects by the product features they affect, giving your teams a clearer picture of where problems are concentrated. This makes triage and prioritization far more effective—rather than treating each defect in isolation, your team can address root causes at the feature level and resolve issues more efficiently.

ISE automates the sustenance activities that consume the most engineering time: defect localization, duplicate defect detection, resolution recommendations, test case optimization, redundant test step elimination and orphan defect flagging. Together, these capabilities significantly reduce manual effort across the full software development and testing lifecycle.