Building an agile brokerage platform and elevating customer experience with agentic AI-driven DataOps

Business need

A Fortune 200 risk and insurance company wanted to drive digital transformation to deliver personalized insurance programs, enhance customer experience, and unlock new revenue streams through advanced analytics.

However, their complex data ecosystem was fragmented across multiple business entities, hindering a unified, real-time view of customers and operations. Moreover, legacy systems struggled to scale for real-time analytics and AI use cases, impacting decision-making and business agility. The organization needed to transition from reactive DataOps to an intelligent, autonomous model that could scale with its global data ambitions, while ensuring reliability, efficiency, and cost control.

Key business requirements:

• Unify 1500+ fragmented data feeds into a single source of truth
• Create a modern, self-service, governed data platform with advanced analytics capabilities
• Power intelligent, data-driven insurance recommendations for customers
• Ensure SLA adherence and reliability for business-critical data workloads
• Support large-scale, multi-region data workloads with seamless orchestration
• Reduce manual effort in monitoring, triage, and remediation workflows
• Build a future-proof, AI-ready data foundation for multiple business use cases
• Lower spiraling cloud and infrastructure costs

Solution

Partnering with the client, Impetus built a secure, scalable unified data platform on AWS, supporting 1,500+ data sources and 1,300+ client integrations across 18+ countries, with real-time ingestion and processing of 100+TB data. This created a governed, AI-ready mesh, empowering teams with 360-degree visibility, smart governance, and advanced analytics at scale. Simultaneously, the platform helped customers identify the most suitable insurance programs for their unique needs.

To enhance operational efficiencies, specialized AI agents were deployed across the client’s AWS ecosystem for continuously monitoring signals, detecting anomalies, performing root-cause analysis, and triggering automated remediation. This reduced manual effort significantly and enabled a massive shift from reactive DataOps to predictive, autonomous, self-healing operations.

Key highlights 

Application modernization with zero downtime: Seamlessly migrated 200+ applications from legacy container systems to Kubernetes, managing 60+ clusters

Unified observability & cost intelligence layer: Provided a single pane of glass across performance, resource usage, SLAs, and costs.

Faster releases with DevSecOps: Established native GitOps pipelines integrated with security and quality tools, and enabled single-click CI/CD

AI-powered productivity gains: Integrated GenAI copilots for CI/CD, debugging, PR automation, and more—enhancing developer efficiency and time-to-market

Agentic AI-driven optimization: Leveraged custom AI agents to generate cloud provisioning templates, streamline infra setup, automate right-sizing, and eliminate idle resources.  

Intelligent, autonomous operations: Deployed AI agents for anomaly detection, root-cause analysis, incident triage, and self-healing remediation workflows

Self-service provisioning: Delivered a customized portal enabling automated infrastructure provisioning, reducing dependency on niche expertise

Impact

By building a single source of truth and embedding agenticAI-driven DataOpsinto the client’s AWS-based data platform, Impetus transformed the way the company monitors, manages, and optimizes data-driven workflows. They have been able to meet growing customer expectations and unlock new business opportunities, while consistently improving performance, reliability, and cost efficiency.

Business benefits

• Massive cost savings: Reduced overall cloud costs by 40% through continuous AI-driven optimization 
• Faster innovation cycles: Reduced release time by 75%, accelerating delivery of new features and data-driven capabilities 
• Operational efficiencies: Enabled 90% reduction in resource provisioning time through self-service automation and orchestration
• Improved performance: Achieved 99% SLA adherence and 99.8% success rate for data processing jobs, ensuring business continuity
• Revenue growth: Enabled 800+ new customer wins and 25,000+ annual client contract registrations with greater personalization
• Reduction in MTTR: AI-driven triage and remediation dramatically improved incident resolution speed