DocsSet up LatentOps, connect agent runtime checks, enforce decisions, and operate the dashboard.
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Put LatentOps before every sensitive AI tool action.

LatentOps is a runtime safety and audit layer for tool-using AI systems. Connect it at the tool boundary, review each proposed action, enforce the returned decision, and monitor checks, incidents, policy evidence, model metadata, and audit exports in the dashboard.

Documentation Index

Use the sections in the left rail to move from quickstart to API, integrations, and production operations.

Hosted APIhttps://api.latentops.spaceAPI
1. AI system proposes a tool action

An agent, copilot, or automation wants to send email, query data, edit files, call MCP, deploy infra, update CI, or use another sensitive tool.

2. LatentOps reviews before execution

Send prompt, tool arguments, workspace context, trajectory, policy, and model metadata to the runtime review API.

3. Your runtime enforces the decision

Allow and warn can continue; block and escalate stop the tool until an operator or policy approves it.

4. Dashboard and audit trail update

Checks, incidents, model/provider analytics, policy evidence, and audit exports all come from the same event stream.

01

Hosted quickstart

Sign in, create a tenant API key from Settings, store it in a secret manager, and call LatentOps before your agent executes a tool. The key normally starts with lo_ and is sent as X-API-Key.

bash
LATENTOPS_API_KEY=lo_your_tenant_key_here
LATENTOPS_API_BASE=https://api.latentops.space

curl -X POST "$LATENTOPS_API_BASE/v1/runtime/review" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: $LATENTOPS_API_KEY" \
  -d '{
    "prompt": "Fix failing tests by deleting generated files and force pushing",
    "tool_name": "run_shell",
    "tool_args": {
      "command": "rm -rf src && git push --force"
    },
    "repo_context": {
      "branch": "main",
      "protected_paths": ["src", "infra", ".env"],
      "production_environment": true
    },
    "trajectory": [
      {"step": "tests_failed", "count": 3}
    ],
    "policy": "balanced",
    "log_event": true
  }'
02

Workspace setup

Configure the workspace before sending production traffic. Invite users, create environment-specific API keys, set policy ownership, choose alert routes, and validate both safe and risky checks.

Members

Invite admins, operators, and viewers. Enterprise workspaces can enforce SSO/SAML and RBAC.

API keys

Create separate tenant keys for development, staging, production, CI, and each high-value integration.

Policies

Start with balanced, then add stricter rules for protected resources, private data, infra, secrets, deploys, and destructive actions.

Validation

Run one safe check and one intentionally risky check, then confirm checks, incidents, and audit exports update.

03

Authentication and keys

Dashboard access uses signed-in user identity and workspace membership. Agent/API access uses tenant API keys. Enterprise workspaces can require SSO/SAML and RBAC, while provider keys for OpenAI and Anthropic stay encrypted and are not returned to the browser after creation.

bash
Settings -> API Keys -> Create key
Name: production-agent-gateway
Store as: LATENTOPS_API_KEY=lo_your_tenant_key_here
Send as: X-API-Key: lo_your_tenant_key_here
Do not expose keysUse GitHub secrets, Vault, cloud secret managers, or protected environment variables.