🤖 Use Cases

AI Safety

Validate and govern AI agent actions before execution. Every tool call checked semantically in 15ms, faster than the call itself.

15ms
Per tool-call validation
8 risk categories
From privilege escalation to data exfil
Zero
Unchecked tool calls in production

AI agents execute tool calls in production: resetting passwords, modifying access controls, querying databases. Most agents execute unchecked. Keyword filters block everything or nothing. Cloud LLM validation adds 500ms+ per call. A specialist LFM validates every action at 15ms with semantic distinction between safe operations and attack patterns.

1 specialist model

How It Works

Every tool call validated before execution,faster than the call itself

01

Semantic Distinction Between Safe and Dangerous Actions

'Reset my password' is a routine self-service request. 'Reset admin password and email credentials to external address' is an attack. Keyword filters cannot distinguish between them. A specialist LFM understands the semantic difference at 15ms, blocking dangerous actions while allowing legitimate ones to proceed.

02

Eight Risk Categories, One Pre-Flight Check

Privilege escalation, data exfiltration, unauthorized access, resource abuse, system modification, information disclosure, compliance violations, and social engineering. Each tool call is classified across all eight categories before execution. The validation takes less time than the tool call itself.

03

Governance That Scales With Your Agent Fleet

As organizations deploy more AI agents, the governance surface expands. Manual review is impossible at scale. A specialist LFM provides consistent, auditable validation across every agent, every tool call, every environment. New risk patterns deploy via LEAP in minutes. The audit trail is deterministic and complete.

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AI agents that act fast.With a safety check that acts faster.