Northbeams

Most AI governance projects stall because they require a network appliance, a six-month procurement cycle, or an agent that IT won’t approve before the audit date arrives. Northbeams addresses this by deploying a browser-side agent that observes AI tool usage across the workforce, classifies each tool, intercepts outbound data in real time to block credential or PII leakage, and writes the resulting activity log into audit-ready compliance evidence — all without touching network infrastructure. The core workflow is: install agent, surface the shadow AI inventory, set allow/block/sandbox policies per tool, and export the evidence package when the auditor calls.

The differentiating feature is the MCP layer. As engineering teams adopt coding agents — Cursor, Claude Desktop, Aider — and connect them to MCP servers, Northbeams claims to govern which agents can reach which tools and enforce per-tool access policies. The vendor also describes linking coding agent sessions directly to git commits, giving security teams a traceable record of what an agent touched and what it shipped. This positions Northbeams specifically for organizations where the AI risk is not just browser-based chat tools but autonomous coding sessions running against internal repositories.

For SMBs inheriting a shadow AI problem without a dedicated security team, the ungated Discovery tier removes the barrier to starting. For companies preparing EU AI Act, SOC 2, or HIPAA evidence, the automated audit trail solves the most time-consuming manual step. Where it breaks: teams with more than a few hundred seats, or with AI deployments spread across multiple physical sites, report that managing per-tool policies at scale becomes a hands-on administrative task. Organizations that need API-level enforcement rather than browser-side interception — or that run AI workloads entirely outside the browser — will find the coverage model insufficient and will need a network-layer or endpoint solution instead.