Case Study
Hexaware’s agentic AI platform helped a leading global alternative asset management firm break free from operational bottlenecks, delivering measurable gains in speed, productivity, and resilience—while continuously learning and improving.
The client is a major multinational organization operating at the intersection of private equity, alternative asset management, and financial services. With a complex, high-stakes environment and global operations, their IT landscape is vast and mission-critical. The firm’s ability to respond rapidly to incidents and maintain operational continuity is essential for both business performance and client trust.
Despite significant investment in automation, coverage plateaued at just 35%. This left a growing volume of complex, cross-tower incidents to be handled manually by senior engineers. As a result, operational costs continued to rise, and the return on investment in automation stalled.
L2 analysts were forced to spend hours correlating telemetry data across five different dashboards. Critical operational knowledge was locked away in static, tribal documentation—making it inaccessible and not ready for AI-driven insights. This lack of institutional memory at the point of action led to slow, error-prone resolutions.
Instead of focusing on high-value, root cause analysis, L3 subject matter experts (SMEs) were routinely pulled into escalations that should have been resolved earlier. This not only led to engineer fatigue and burnout but also turned the escalation path into a bottleneck, threatening both operational resilience and team retention.
Hexaware designed and deployed an agentic AI-powered operations platform tailored to the client’s unique environment. This solution replaced static, runbook-driven workflows with intelligent, continuously learning agents that operate at every tier of the incident management chain.
Two months after go-live, the client’s L3 escalation queue has shrunk by nearly a third. Senior engineers can now focus on genuine root-cause challenges, while L2 analysts resolve incidents faster with AI-guided recommendations. The DEVAL Engine continues to learn from every incident, steadily improving agent precision and expanding the platform’s ability to handle increasingly complex scenarios. The engagement remains active, with the platform’s intelligence and value compounding with every incident resolved.
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