Deploy trusted AI at scale — without scaling the team managing it

Monte Carlo is the agent trust platform that intelligently monitors, troubleshoots, and improves your AI agents and their underlying data in production — ensuring enterprise data quality and giving you the confidence to move from human-guided to fully autonomous, without the risk.

Monitor the full trust stack

Detect issues across data pipelines to agent context, behavior, and outputs

Troubleshoot faster with AI

Automatically trace failures to root cause across data and agents

Improve performance at scale

Reduce token costs, latency, and silent drift without adding headcount

How Monte Carlo supports data + AI leaders

Agents fail in ways traditional monitoring can't catch — bad retrieval context, hallucinated outputs, silent behavioral drift, runaway token costs. Monte Carlo closes the full trust loop across both data and AI, so every undetected failure gets caught before it erodes stakeholder trust or gives leadership a reason to pull the plug.

Intelligently monitor every dimension of agent trust — at any scale

From the pipelines feeding your agents to the context they retrieve, the decisions they make, and the outputs they produce — Monte Carlo monitors the full trust stack so no silent failure slips through, no matter how many agents you're running.

• Auto-scale coverage as your agent deployments grow — no manual configuration required
• Catch context quality issues in RAG and tool calls that no other vendor monitors
• Surface cost inefficiencies, latency bottlenecks, and behavioral drift at the aggregate level — actionable intelligence, not raw logs

One platform across your entire data and agent ecosystem

Agent frameworks, LLM tools, and legacy observability each cover one slice. Monte Carlo connects them all — platform-agnostic integrations with Snowflake Intelligence, Databricks Genie, and 100+ more — giving every team a unified view of reliability, cost, and performance across data and AI.

Trace any agent failure back to its source — in seconds

When an agent fails, the cause could be anywhere — a broken pipeline, bad retrieval context, a model behavior change. Monte Carlo's agent lineage connects every output back to its source data, and the Troubleshooting Agent diagnoses the issue and prescribes a fix before downstream consumers feel the impact.

Keep leadership and stakeholders ahead of every incident

Trust starts with visibility. Automatically route alerts to the right owners, surface business impact instantly, and keep stakeholders informed across Slack, Tableau, Alation, and your ticketing tools — so incidents never become surprises.

• Understand the impact—find out instantly what downstream data + AI products were impacted by a break and what teams need to know about it.
• Right message, right time—reduce business impact with automated alert routing that lets impacted users know when breaks occur and keeps stakeholders informed throughout the process.
• Warn users where they’re working—Improve engagement and build trust with warnings everywhere users need them—from Slack all the way to Alation and Tableau.

CUSTOMER STORIES

Trusted by enterprises deploying AI at scale

Our customers scale trust, reduce risk, and deliver better business outcomes. See how you can too.

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 it's entire data lake via a multi-step deployment.

Get started fast—scale faster.

Fast setup—even faster time to value. Connect to Monte Carlo in seconds, start monitoring out of the box and automatically scale with your environment.