Add Deterministic Enforcement in 2 Minutes
Exogram is pure Python middleware between your agent and your execution layer.
Zero AI in the loop. 0.07ms evaluation. Works with every framework.
The Execution Boundary
There is no native enforcement layer in current LLM frameworks. Exogram is deployed at the boundary between your agent logic and your internal tools.
- ✓ No infrastructure changes
- ✓ No model changes required
- ✓ No prompt retraining
Production Readiness Analyzer
Paste your current agent execution logic to check for unhandled vulnerability paths.
- → database operations
- → financial actions
- → API integrations
- → filesystem access
The Integration Diff
Time to integrate: ~2 minsStop trusting the LLM payload blindly. Add the deterministic execution boundary.
from exogram import ExogramClient client = ExogramClient(api_key="exo_live_...") def run_agent_action(prompt): tool_call = llm.generate_response(prompt)+ verdict = client.evaluate(tool_call)+ if not verdict.is_safe:+ return handle_rejection(verdict.error)- execute(tool_call.arguments) # blind trust+ execute(tool_call.arguments) # governed
Three Lines of Code
Exogram does not replace your stack. It sits between your agent and execution.
pip install exogramLightweight Python SDK. No system dependencies. No GPU. No model downloads.
client = ExogramClient(api_key="exo_...")One line. Connects to the Exogram evaluation edge. Sub-millisecond latency.
verdict = client.evaluate(action, payload)Intercept every tool call. Get PERMIT or DENY with a precise error trace.
Works With Your Stack
REST API or MCP. Any framework. Same deterministic engine.
Exogram enforces what AI is allowed to do at the execution boundary.