Asymptote Labs gives security teams runtime control over AI-agent activity

Asymptote Labs is a security and runtime-data layer for companies adopting AI agents across local machines, CI and cloud environments. It is for security and engineering teams that need to know which agents, tools and files are actually being used—not merely which models are approved on paper.

What it does

Asymptote’s open-source Agent Beacon captures local agent runtime telemetry and forwards a normalized record to the systems the customer already uses. The managed platform adds ingest, retention, search, detections, inventory, policy, identity mapping and approval workflows. The public product pages name Claude Code, Codex, Cursor and other harnesses, with integrations across SIEM, identity, collaboration and developer tools. Asymptote homepage Agent Beacon

That split is the main buying advantage. A team can start by owning the raw event record locally, then decide whether it needs managed fleet visibility or a private deployment. The runtime view is also more specific than a generic endpoint log: prompts, tool calls, file access and network events are the evidence needed to investigate what an agent saw and did.

Price and tradeoffs

The Community option is free forever through Agent Beacon. Enterprise and Private Deployment are custom, with managed retention, detections, fleet inventory, policy controls, SSO/RBAC and data-isolation options listed on the pricing page. Asymptote pricing The company also advertises 12-plus harnesses, eight-plus SIEMs and one-click MDM deployment; these are product claims to verify against the organization’s exact fleet.

The tradeoff is visibility versus data boundary. Capturing prompts, file edits and tool calls can expose source code, credentials or customer material if redaction and retention are poorly configured. The docs describe an open-source path and managed/private options, but a security team should still review collection scope, identity mapping, policy failures and forwarding behavior. No security test was performed for this profile.

The South Park Commons profile identifies Justin D’Souza as an ML engineer and Shukan Shah as a workflow-automation and agentic-cybersecurity builder. The current site also names security and engineering leaders supporting the company; those are not treated as independent product validation.

My editorial take

I would start with Agent Beacon when the immediate problem is inventory and evidence, not buy the managed control plane before the team knows which runtime events it needs. Enterprise or private deployment becomes credible when the fleet is large, investigations cross endpoints and identity, or data residency is a hard requirement. The first decision is what you are allowed to observe, not how many detections the dashboard promises.

Quick facts

Field	Sourced detail
Buyer	Security and engineering teams governing AI agents
Product	Open telemetry plus managed detection and policy control
Pricing	Community free; Enterprise and Private Deployment custom
Integrations	Agent harnesses, SIEMs, identity and developer systems are advertised
Main fit question	Do you need agent runtime evidence across a fleet today?

Sources checked

Asymptote’s South Park Commons profile, homepage, pricing page, docs and Agent Beacon repository were checked on 2026-09-19.