Kore.ai launches platform to manage AI agents across enterprise
Kore.ai announced the Agent Management Platform (AMP) on Thursday, a control system designed to govern and monitor AI agents across an organization's infrastructure. The platform addresses what analysts call "AI sprawl"-dozens of separate AI projects running on different tools and clouds without central oversight.
Gartner predicts enterprises will operate thousands of AI agents by 2028 across various business functions. Without centralized management, organizations risk losing visibility over how AI systems operate and whether they deliver measurable business results.
What the platform does
AMP consolidates monitoring, governance enforcement, performance tracking, and value measurement into a single operational layer. It works across multiple AI frameworks and cloud providers, including LangGraph, CrewAI, AutoGen, Google ADK, AWS AgentCore, Microsoft Foundry, and Salesforce Agentforce.
Two capabilities distinguish AMP from competitors. First, an evaluation studio lets teams test agent behavior and workflows before production deployment. Second, the platform operates across heterogeneous environments-it can govern AI systems built on different frameworks and tools, not just those from a single vendor.
Organizations can track AI performance and costs, enforce policies consistently, detect anomalies, and measure how AI initiatives align with business outcomes.
Why this matters for management
As AI becomes core infrastructure for enterprises, managers need visibility and accountability over how these systems operate. Prasanna Arikala, CTO and Head of Products at Kore.ai, said the platform "introduces a new operational layer for enterprise AI, giving leaders the ability to manage AI agents with the same discipline, transparency, and accountability as any other critical business system."
Raj Koneru, CEO and Founder of Kore.ai, framed the challenge directly: "Scaling AI responsibly requires more than powerful models; it requires governance, visibility, and accountability."
For management professionals overseeing AI adoption, the platform addresses a practical problem: how to move from fragmented experiments to controlled, enterprise-scale deployment. Learn more about AI governance and control for management professionals.
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