Client Overview

A high-growth startup specializing in AI agents designed to drive autonomous decision-making across dynamic operational environments.

Requirement

The client was experiencing rapid growth but lacked the infrastructure to support reliable experimentation and insight generation:

No dedicated pre-deployment testing environment for safely validating agent behavior and configuration changes
Limited system observability, making it difficult to proactively detect anomalies
Absence of a centralized intelligence layer to unify metrics across business and engineering teams

We delivered a modular, cloud-native platform optimized for speed, resilience, and scalability:

Built a realistic simulation environment using .NET 8, Azure Functions, Blob Storage, and Azure DevOps, allowing safe validation of autonomous workflows
Adopted an agentic architecture to support self-directed testing and feedback loops
Developed a custom intelligence layer with real-time monitoring, role-specific dashboards, and automated alerting
Employed Terraform for infrastructure-as-code to ensure reproducibility and consistent provisioning across environments

Over 40% faster testing cycles, accelerating innovation and iteration
30% fewer post-deployment issues, leading to improved reliability
Real-time insights and anomaly alerts, enabling faster, data-driven decision-making
52% improvement in incident response times due to automated signal detection
Improved cross-functional alignment through shared visibility and reporting
Scalable, future-proof architecture ready for seamless integration and growth