Agents ask first.
Wrap consequential tools once. The runtime receives sanitized arguments, trace IDs, and risk context.
Runtime security for AI agents
Stop dangerous agent actions before tools run.
TAME sits between agents and sensitive tools, enforcing deterministic policy before execution and preserving evidence when something needs review.
AI agents now touch code, customer data, and production workflows. TAME gives teams a real-time control plane before one bad tool call becomes an incident.
How it works
Policies stay deterministic.
Match agent, tool, destination, limits, risk scores, and workflow evidence before execution.
Incidents become evidence.
Blocked actions, approvals, remediation, memory writes, and containment all land in one operator queue.
What the dashboard includes
Runtime decisionsAllow, block, or require approval before tool execution.Policy
Incident queueEvidence, timeline, remediation, and reviewer outcome.Review
Security memoryLearns from completed remediation and false positives.Context
Red-team simulatorRuns fixed risky scenarios against active policy.Test
Containment playbooksPre-approved reversible actions with dry-run history.Control
Customer-owned AI keysLets teams connect their own model account for high-volume analysis.Ops
AI usage options
Use the product immediately with included analysis capacity for demos, setup, and low-volume review.
Connect customer-owned model credentials so high-volume remediation and summaries bill directly to their provider account.
TAME charges for runtime security, policy control, evidence, and workflow seats; managed AI usage can be metered as an add-on.
Private walkthrough
Schedule a demo
Schedule a focused demo to see TAME block a risky agent tool call, capture the evidence, and hand the incident to a reviewer.
TAME / Runtime security for AI agents