Monte Carlo at a Glance

What is Monte Carlo?

Enterprises are putting agents into production faster than they can keep them trusted. Agents fail in ways traditional monitoring misses: bad retrieval context, wrong or hallucinated answers, silent drift, and runaway costs. Many of those failures start in the data an agent depends on, so Monte Carlo covers agents and their data in one place.

• Agent trust is the category. Monte Carlo watches every layer an agent depends on, from the data feeding it to the answers it gives.
• Bayes does the work. Bayes, Monte Carlo's AI teammate, triages and troubleshoots alerts, builds and tunes monitoring coverage, and finds what's breaking your agents. You choose how much of that work it takes on.
• Your agents improve over time. Each fix you accept and Monte Carlo verifies makes your agents better instead of letting them drift.

The four layers of agent trust

Monte Carlo monitors and evaluates each layer, and traces failures across them so teams fix the root cause the first time.

• Context: the data that powers your agents. Monte Carlo connects to your data warehouses, data lakes, ETL, orchestration, and business intelligence tools. It learns your data's historical patterns with machine learning and alerts when pipelines break or anomalies emerge, with no thresholds to configure. Field-level lineage shows where your data comes from and what depends on it, so failures can be traced to their source, and the catalog shows the location, health, and ownership of every data asset, which also helps teams meet data governance requirements.
• Performance. Agent metric monitors catch latency spikes, token usage over budget, and rising error rates.
• Behavior. Agent trajectory monitors check how an agent reasons and uses its tools.
• Output. Agent evaluation monitors and agent validation monitors check the quality of the answers your agents give.

See Agent Trust overview to instrument your first agent.

How teams work with Monte Carlo

• Where engineers already work. Use Monte Carlo in its UI, in Slack and Microsoft Teams, and from AI coding assistants and CI/CD through the MCP Server. The Agent Toolkit provides pre-built skills that teach coding agents to check data health, monitor datasets, triage alerts, and safely make code changes.
• Security-first architecture that scales with your stack. Designed by security industry veterans, the platform maps your company's data assets at rest, without requiring the extraction of data from your environment, and scales to any data size.
• No-code onboarding for your data stack. Code-free implementation gives you out-of-the-box coverage of your existing data stack and seamless collaboration with your teammates.