How Axonius Built Secure Multi-tenant AI Agents on Bedrock AgentCore
AI Executive Summary
Axonius, a cybersecurity SaaS provider, deployed fully isolated, multi-tenant AI agent on Amazon Bedrock AgentCore by using a silo architecture where each customer runs in its own VPC with a dedicated agent, Application Load Balancer and Network Load Balancer.
The design leverages Bedrock AgentCore’s runtime to allocate a unique session ID per tenant while preserving Axonius’s existing tenant‑management methodology.
Why It Matters
Strategic TakeawayThe implementation proves that large‑scale SaaS firms can achieve per‑tenant AI isolation without sacrificing scalability, demonstrating that Bedrock AgentCore can enforce strict resource boundaries at the VPC level.
Multi-Vector Implications
- TECHNICALPer‑tenant isolation via dedicated VPCs and individual AgentCore agents eliminates cross‑tenant data leakage and simplifies compliance auditing.
- MARKETSaaS vendors can now offer AI‑enhanced feature with confidence, opening new revenue streams while differentiating on security guarantees.
- GOVERNANCERegulators may view VPC‑level segregation as meeting data residency and privacy mandates, prompting tighter standards for multi‑tenant AI services.
Strategic Outlook
12-18M HorizonOver the next 12‑18 months, expect a rise in SaaS providers adopting Bedrock AgentCore’s silo pattern, with AWS adding native tooling for automated VPC‑agent provisioning and cost‑tracking dashboards.
Referenced Coverage & Sources
Read the full coverage below for original reporting, technical benchmarks, and complete primary source details.
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AI Agent
An AI Agent is an autonomous entity that perceives its environment through sensors (or inputs) and acts upon that environment using actuators (or tools) to achieve specific goals. An agent relies on a reasoning brain (typically an LLM) to plan and execute multi-step processes.
Agentic AI
Agentic AI refers to artificial intelligence systems designed to act autonomously, make decisions, plan workflows, and execute tasks without constant human intervention. Unlike traditional models that only respond to queries, agentic systems use an agentic loop to perceive environments, reason over goals, use tools, and iterate to achieve outcomes.
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