Data + AI Observability for Snowflake

Monte Carlo’s Data + AI Observability Platform gives your team full visibility into the health of your AI systems — from data input to agent output — natively on Snowflake’s AI Data Cloud.

Partnership

Validated at every level of the Snowflake ecosystem

The highest tiers of technical validation and partner recognition from Snowflake — so your team can buy and deploy with confidence.

Elite Technology Partner

The highest tier in the Snowflake Partner Network, recognizing technical depth and joint customer success.

Snowflake Ready Technology

Officially validated for performance, security, and reliability on the AI Data Cloud.

Snowflake Intelligence Partner

The #1 observability platform for Snowflake AI agents — natively integrated with Snowflake Intelligence, Cortex, and CoCo.

Available on Snowflake Marketplace

Procure directly through Snowflake Marketplace — counts toward committed spend and simplifies procurement.

Cortex Agent Observability Partner

First Data + AI Observability platform with native monitoring for Snowflake Cortex AI agents.

Industry Competency Badges

Recognized across Financial Services, Healthcare, Retail, Media, and Technology for verified customer success.

Capabilities

Observability at every layer of your stack

Monte Carlo covers the full journey — from raw Snowflake data through to what your AI agents produce.

Data layer

• Data observability: Automated monitoring across every Snowflake table, schema, and pipeline.
• Automated anomaly detection: ML-powered monitors learn your data patterns and flag deviations in volume, freshness, schema, and distributions — no thresholds needed.
• End-to-end lineage: Column-level lineage from ingestion through dbt to every downstream BI tool and AI model — zero instrumentation required.
• Custom SQL monitors: Define business logic rules on any Snowflake table. Runs on your compute — no data leaves your environment.
• Impact analysis: When a table breaks, instantly see every downstream consumer — dashboards, AI models, Cortex agents — before you remediate.

Agent layer

• AI agent reliability: Input validation and context reliability for Snowflake Cortex agents.
• Pre-flight data validation: Monitor the Snowflake tables your Cortex agents retrieve from. Catch stale or anomalous data before it reaches the agent context window.
• Context reliability scoring: Score the quality and freshness of every data input to your agents — always know if an agent is reasoning on data you can trust.
• Cortex & CoCo integration: Native integration with Snowflake Cortex Agents and Cortex Code — no additional instrumentation for full pipeline visibility.
• Snowflake Intelligence monitoring: As a Snowflake Intelligence partner, Monte Carlo surfaces data health signals directly within the Intelligence layer.

Output layer

• AI output observability: Monitor what agents produce and trace failures back to root cause.
• Agent output monitoring: Track what your Cortex agents produce over time — detecting drift, degradation, or unexpected behavior before it reaches customers.
• Root cause tracing: When an agent misbehaves, trace the failure back through the full stack to the specific Snowflake table or pipeline that caused it.
• Incident routing: Route AI-related incidents to the right owner instantly — with Slack, PagerDuty, and Jira integrations and automatic blast radius scoping.
• SLA & reliability tracking: Set reliability targets for your AI systems. Track data SLAs, agent uptime, and input quality trends over time.

Agent Observability

If the data is wrong, the agent is wrong.

Monte Carlo is the first observability platform built to monitor the full Cortex agent loop — from data input through agent output — so your team catches failures before customers do.

• Discover all Cortex Agents in a single click — no instrumentation
• Monitor data quality before agents consume it
• Trace every agent decision back to its Snowflake source
• Works natively with Snowflake Intelligence, Cortex, and CoCo
• Available directly on Snowflake Marketplace

Customer Stories

How Axios Is Delivering Reliable AI with Agent Observability

The Challenge:

Axios needed to monitor across their data + AI lifecycle including agent context, performance, behavior, and outputs.

The Solution:

Leveraged Agent Observability for full agent visibility integrated into a robust incident management workflow.

How JetBlue Improved Internal “Data NPS” By 16 Points YoY

The Challenge:

When a data migration improved data usage, increased access brought increased scrutiny. And the trustworthiness of the data took center stage.

The Solution:

Operationalizing data + AI observability and leveraging Monte Carlo's in-app features to measure the outcomes.

Nasdaq's Journey to Reliability with Monte Carlo

The Challenge:

Nasdaq generates 6,000 reports per day across 35 services and 2,200 users. The question is—how do you make that much data reliable?

The Solution:

The team deployed Monte Carlo to monitor its entire data lake via a multi-step deployment.

Ready to trust your Snowflake data and AI?

Join 300+ Snowflake customers using Monte Carlo to eliminate data downtime and build reliable AI.