§ PLATFORM
The AI agent enforcement engine
Execlave sits between your AI agents and the systems they control — evaluating every action against your policies, generating immutable audit trails, and stopping violations before they happen.
§ 05 / CORE CAPABILITIES
Everything you need to govern AI agents at runtime
From policy definition to compliance reporting, the platform enforces and proves every decision.
Everything you need to govern AI agents at runtime
01 / Capability
Sub-20 ms enforcement
Every agent action is evaluated against your policies before it reaches the real world. Semantic classification, policy evaluation, and audit logging — all in a single synchronous call.
02 / Capability
Policy engine
Define granular governance policies with rules for tool access, cost limits, rate controls, content filtering, and time-based restrictions. Policies are enforced deterministically at runtime.
03 / Capability
Full execution trace auditing
Every agent action generates an immutable, cryptographically signed audit trail. Filter, search, and export traces for compliance reviews and incident investigations.
04 / Capability
Prompt version control
Manage prompt versions with a full lifecycle: draft, review, approve, deploy, and rollback. Every change is tracked with diffs and approval workflows.
05 / Capability
Kill switches and approvals
Pause any agent instantly. Route high-risk actions through human-in-the-loop approval workflows via dashboard, Slack, or API.
06 / Capability
Cloud or self-hosted
Deploy Execlave as a managed cloud service or run it entirely within your own infrastructure using Docker Compose. Your data never leaves your perimeter.
§ STACK
Works with your AI stack
Works with your AI stack
§ ARCHITECTURE
How the enforcement engine works
Each agent action is evaluated in sequence before it can reach your systems.
How the enforcement engine works
Agent requests an action
Your agent’s SDK call sends the action context (tool, input, agent ID) to the Execlave enforcement API.
Semantic classification
Execlave classifies the action using a local LLM — detecting prompt injection, PII, and intent categories.
Policy evaluation
All matching policies are evaluated deterministically: tool access, cost budgets, rate limits, content rules, and time windows.
Decision & audit
The action is allowed, paused for human review, or blocked. An immutable, cryptographically signed audit log entry is created regardless of the outcome.
Ready to govern your AI agents?
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