Monte Carlo
UnclaimedClose the loop between data inputs and agent outputs with an end-to-end Data and AI Observability Platform.
Visit WebsiteTL;DR - Monte Carlo
- End-to-end data and AI observability for enterprise teams.
- Monitors data quality and AI outputs to prevent issues like hallucination and bias.
- Provides automated lineage, alerting, and root cause analysis for faster resolution.
Pricing: Paid only
Best for: Enterprises & pros
Pricing Plans
Start
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- Monitoring for Data Warehouse, Business Intelligence, ETL
- Incident triaging, troubleshooting and root cause analysis
- Lineage
- Performance observability
- Self-guided onboarding
- 24+ hour support SLA
- Up to 10 users
- Pay per monitor, up to 1,000
- 10,000 API calls / day
Scale
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- Monitoring for lakes: Databricks, Hive, Glue, Azure Data Lake
- Monitoring for databases: MySQL, Postgres, SQL Server
- Data Mesh support: Unlimited Data products, Domains
- Advanced Security: SSO, SCIM, Self-Hosted Storage, PII Filtering, Audit Logging
- Automation: Data exports, Webhooks
- Advanced networking: Self-Hosted Agent, PrivateLink (available add-on)
- Expert-guided onboarding
- 8+ hour support SLA
- Unlimited users
- Pay per monitor
- 50,000 API calls / day
Enterprise
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- Everything in Scale
- Monitoring for EDW: Oracle, SAP Hana, Teradata
- Multi-workspace support for testing and development
- Enterprise productivity + governance: ServiceNow, Data Catalogs
- Expert guided onboarding and scaling
- 4+ hour support SLA
- Unlimited users
- Pay per monitor
- 100,000 API calls / day
About Monte Carlo
Monte Carlo is an end-to-end Data and AI Observability Platform designed to help enterprise teams monitor, trace, and troubleshoot data inputs and AI agent outputs in production. It addresses the "Data + AI Trust Gap" by ensuring data quality and reliability for AI systems, preventing issues like drift, hallucination, or biased results from AI outputs, and incomplete, inaccurate, or delayed data inputs.
The platform provides comprehensive visibility across the entire data and AI ecosystem, from ingestion to consumption. It empowers data engineers, analysts, and governance leaders to understand and take ownership of data and AI health, scale trust, reduce risk, and deliver better business outcomes. Monte Carlo aims to accelerate AI adoption and innovation by building trust in AI systems.
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Monte Carlo FAQ
Monte Carlo is an end-to-end Data and AI Observability Platform that helps enterprise teams monitor, trace, and troubleshoot data inputs and AI agent outputs in production. It ensures data quality and reliability for AI systems, preventing issues like drift, hallucination, or biased results.
The pricing for Monte Carlo is not explicitly stated on the provided pages, but it is positioned as an enterprise solution, suggesting a paid model. Users are encouraged to request a demo to learn more.
Based on the available content, Monte Carlo does not appear to offer a free tier or trial. It is presented as a comprehensive enterprise platform, and users are prompted to request a demo.
Monte Carlo is designed for enterprise teams, including Chief Data + AI Officers, data engineers, data analysts, and governance leaders, who need to ensure the reliability, quality, and trustworthiness of their data and AI systems in production.