tools

Monte Carlo Data Observability Platform

Monte Carlo monitors data, ML models, and AI agents to detect quality issues, trace causes, and improve reliability.

In inglese

Monte Carlo is a web platform for monitoring data quality across warehouses, lakes, databases, BI systems, pipelines, ML models, and AI agents. It detects freshness, volume, schema, and other issues, then provides alerting, lineage, impact analysis, root-cause analysis, and performance insights.

Data engineers, analysts, ML teams, governance teams, and data leaders use it to monitor tables, data products, model metrics, and agent workflows. Pricing is usage-based through credits or monitors, and the public pricing page does not display credit or plan prices.

Features

Automated monitoring for freshness, volume, schema, and data quality issues
Field-level lineage with upstream and downstream impact analysis
Root-cause analysis correlating data, system, and code changes
Automatic data profiling for field types, null rates, and cardinality
Codeless, SQL, YAML, programmatic, and AI-assisted monitor creation
Monitoring for structured and unstructured data
ML metric monitors for RMSE, MAE, MAPE, R-squared, mean error, and accuracy
API access with plan-specific daily call limits

Use cases

Detect broken pipelines before they affect dashboards or AI systems
Trace data incidents from source tables to downstream products
Monitor ML model prediction quality and performance degradation
Profile tables and deploy monitoring coverage without writing SQL
Route alerts and coordinate incident investigation across data teams
Monitor the data used by enterprise AI agents and applications

Pros

Cons

Capabilities

Ask in plain language — “It deploys hundreds of subagents to investigate anomalies using natural language, then returns clear, validated explanations and actionable next steps.” source
Connects to your data — “Monte Carlo integrates with 50+ systems across 8 categories, spanning warehouses, lakehouses, agent frameworks, telemetry platforms, and BI tools.” source
Real-time data — “Monitors topic-level throughput and schema for streaming pipelines” source
API — “Ingests agent traces via the montecarlo-opentelemetry Python SDK, the standard instrumentation path” source

Security

SOC 2 Type II — “Monte Carlo SOC 2 Type 2 Report 2026.pdf” source
SOC 2 — “Monte Carlo SOC 2 Type 2 Report 2026.pdf” source
ISO 27001 — “Monte Carlo Data ISO 27001 27017 27018 Certificate - 2026.pdf” source

Pricing

Prices checked: 2026-09-25

Official website