Monte Carlo

Monte Carlo is an enterprise observability platform for data, machine-learning systems, and AI agents. It monitors pipelines and production systems, detects reliability or behavior problems, links incidents to lineage and root causes, and provides shared workflows for data engineers, AI engineers, and governance teams.

The current product has expanded beyond its earlier data-observability focus into agent trust and AI observability. All commercial tiers include agent, ML, data, and performance observability plus a fleet of agents for automating operational work; plans scale through usage credits, integrations, security, user counts, and API limits.

Supported use cases

Detect a broken data pipeline

Alert on unexpected changes and use lineage to identify the affected upstream or downstream assets.

Monitor agents in production

Observe agent behavior and performance across supported frameworks and enterprise systems.

Coordinate reliability response

Triage an incident, find root cause, route it to the right owner, and record operational context.

Limitations

Usage and integration limits vary by tier

The Start tier caps users, monitors, and daily API calls; higher tiers add security, integrations, support, and enterprise controls.

Sales-assisted pricing

The official page describes credit-based commercial tiers but requires a pricing request for actual rates.