This is a guest post co-written with Roei Zavida from Eon.

Independent software vendors (ISVs) building AI-powered products need to connect agents and humans to dozens of operational tools across clouds, each with different authentication models, network boundaries, and access policies. When those tools span AWS, GCP, and Azure simultaneously, the integration surface multiplies.

This post describes how Eon used Amazon Bedrock AgentCore, a platform to build, connect, and optimize agents at scale, with any framework or model. Eon used it to replace per-tool credentials and local Model Context Protocol (MCP) processes with a single authenticated gateway. The result gives developers and autonomous agents unified access to investigation tooling across three clouds. New engineers now reach all their investigation tools in about two minutes instead of the two days it previously took to configure credentials and local MCP servers.

About Eon

Eon provides the Autonomous Data Foundation for the AI era. The platform discovers and classifies cloud resources across AWS, Azure, and GCP. It provides continuous deduplicated backup that reduces storage costs by up to 50 percent in Eon’s internal measurements. It also detects ransomware and rogue-agent damage and delivers live grounded context for AI agents. All of this runs from a single read-only AWS Identity and Access Management (IAM) role, storing data in Apache Parquet and Apache Iceberg formats. Founded by former AWS engineers, Eon runs its software as a service (SaaS) infrastructure on AWS.