Monte Carlo
Unified observability platform for production data pipelines and AI agent systems
| What is it | Unified observability platform for production data pipelines and AI agent systems |
|---|---|
| Pricing | Contact for Pricing |
| Free tier | No |
| Platform | Web Application |
| API | Yes |
| Works with | Claude AI |
| Best for | monitoring production AI systems for reliability, troubleshooting data pipeline issues in real time |
| Domain registered | 2023 |
Data updated Aug. 1, 2026
What does Monte Carlo do?
Monte Carlo is an observability platform built for enterprises that run data pipelines and AI agents in production. It monitors the health of your data, the behavior of your AI models, and the performance of your agents — all from one place. Instead of waiting for stakeholders to report broken dashboards or strange agent outputs, you get automated alerts the moment something goes wrong. The platform helps you track data freshness, volume, and schema changes, and it keeps an eye on agent performance so you can catch drift, errors, or unexpected behavior early.
The tool connects to over 200 integrations across data warehouses, code repositories, and agent frameworks. You set up monitors for your specific data assets and agent workflows, and Monte Carlo automatically learns normal patterns and flags anomalies. When an issue is detected, it surfaces the root cause — showing you exactly where the pipeline broke or which agent action triggered a failure. The platform also provides a unified view of your entire data and AI estate, so you can see dependencies and troubleshoot across systems.
Monte Carlo is a good fit for data engineering and AI/ML teams at companies that cannot afford data downtime or unreliable AI outputs. It is used by enterprises like Disney, Salesforce, and Nasdaq to reduce data incidents, cut troubleshooting time, and build trust in their data and AI products. If your team ships data pipelines or AI agents that need to stay reliable at scale, this platform gives you early warning and clear diagnostics.
Key features
What makes it stand outWho is Monte Carlo for?
Who benefits most from this toolPricing
Start
- Observability for Agents, ML, Data, and Performance
- Fleet of agents to automate work
- Incident triaging, root cause analysis & lineage
- Self-guided onboarding, 24-hour support SLA
- Integrations: Agents developed on Langchain, Snowflake Intelligence, Databricks Genie and many others
- Integrations: Data Warehouse, BI, ETL
- Up to 10 users
- Pay per monitor, up to 1,000
- 10,000 API calls / day
Scale
Everything in Start, plus:
- Everything in Start
- Advanced Security: SSO, SCIM, Self-Hosted Storage, PII Filtering, Audit Logging
- Automation: Data exports, Webhooks
- Data Mesh support: Unlimited Data products, Domains
- FDE services available, 8+ hour support SLA
- Additional Integrations: Lakes: Databricks, Hive, Glue, Azure Data Lake
- Additional Integrations: Databases: MySQL, Postgres, SQL Server
- Unlimited users
- Pay per monitor
- 50,000 API calls / day
Enterprise
Everything in Scale, plus:
- Everything in Scale
- Multi-workspace support for testing and development
- Advanced enterprise cost attribution ("chargebacks")
- FDE services available, 4+ hour support SLA
- Additional Integrations: EDW: Oracle, SAP Hana, Teradata, Microsoft Fabric
- Additional Integrations: Enterprise productivity + governance: ServiceNow, Data Catalogs
- Additional Integrations: Fully customizable bring-your-own-integration
- Unlimited users
- Pay per monitor
- 100,000 API calls / day
Business Critical
Everything in Enterprise, plus:
- Everything in Enterprise
- Dedicated Instance
- Disaster recovery: rollover to a different region
- Unlimited users
- Pay per monitor
- 100,000 API calls / day
Trust & presence
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