Coforge Limited announced continued momentum for its AgenticOps capabilities, helping enterprises build the operational foundation required to scale AI-driven autonomy securely, resiliently, and cost-effectively. The announcement reflects growing client demand for AI infrastructure and operations models designed specifically for AI agents and autonomous systems.
As organizations move from AI pilots to production deployments, agent fleets expose resiliency, security and control gaps that conventional operating models were never designed to handle. They include insufficient governance and controls, agent drift, a widening set of attack vectors, unreliable tool integration and orchestration, data security and sovereignty exposure, limited agent accuracy and observability, and escalating token consumption costs.
AgenticOps within the Coforge Nuuron enablement suite
Coforge's AgenticOps approach is purpose-built to close these gaps, giving enterprises the governance, security, and trusted AI Infrastructure needed to run agentic AI safely at scale. It provides centralized controls and continuous monitoring to detect and correct agent drift, embeds zero-trust security to guard against emerging attack vectors, and flexibility to integrate with existing tools for reliable, scalable orchestration.
With built-in data security and sovereignty controls, real-time observability, and intelligent token optimization, AgenticOps gives enterprises the confidence and control to move agentic AI from pilot to production. Coforge is working with more than 160 clients to enable their AgenticOps journey. 37 clients are already experiencing 98.2% accuracy with AgenticOps across 392 secure environments spanning AI workloads, cloud, and AI infrastructure.
At the center of the offering is EvolveOps.AI, the AgenticOps layer within the Coforge Nuuron AI autonomy enablement suite. EvolveOps.AI brings governance, control, and a single enterprise-grade harness for operationalizing agents, including continuous evaluations and automated drift detection, token consumption monitoring, and a governed registry of approved tools and model control protocols (MCPs). One harness replaces the fragmented tooling that leaves most agent programs stranded in pilot.
"The intelligence layer and the data capabilities beneath it are now well understood. What decides how far an enterprise can actually take autonomy is the strength of its AgenticOps foundation," said Ashish Kumar, Global Head, Cloud & AI Infrastructure, Coforge. "Autonomy at scale demands an operational foundation that holds under load, where security, governance, performance and cost are managed continuously rather than reviewed after the fact. AgenticOps is what allows enterprises to make that transition with confidence."
Early client deployments have delivered measurable outcomes, including significantly faster threat remediation, improved operational resilience, and tighter control of token spend. By pairing autonomy with governance and accountability, Coforge is helping clients move AI from experimentation into business-critical operations.
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