Feder and Monte Carlo: keep Monte Carlo, check the numbers you run on.
No, Feder is not a replacement for Monte Carlo. Keep Monte Carlo. Feder does a different job beside it: it reads what your connected apps recorded and compares each number with your own history, so you know when one cannot be trusted.
Why would I need this?
Because the question is not what the number is. It is whether you can trust it.
Is Feder an alternative to Monte Carlo?
No. Monte Carlo is a data and AI observability platform that monitors, troubleshoots and optimizes AI agents and the data underneath them. Feder does a different job: it watches the numbers your tools record and says when one cannot be trusted. Nothing here asks you to switch.
Do I need Feder if I have Monte Carlo?
They do different jobs, so one does not stand in for the other. Keep Monte Carlo for the job it does. Feder's job is to say when a number your tools record has gone quiet or moved outside your own history.
What does Monte Carlo do better?
Monte Carlo's table monitors give broad anomaly detection for freshness, volume and schema changes across many tables at once, with little setup.
In Monte Carlo's words:
Get broad, low-config anomaly detection for freshness, volume, and schema changes across many tables at once.
Table Monitor, read 2026-11-12.When something breaks, Monte Carlo can point to the specific failing query most closely tied to the incident.
In Monte Carlo's words:
Monte Carlo alerts you of the specific failing query that is highly associated with the incident.
Root Cause Analysis (RCA) Insights, read 2026-11-12.Monte Carlo retrains its anomaly models often on a rolling window of recent data, so expected ranges keep up with how the data changes.
In Monte Carlo's words:
Models are frequently retrained using a rolling window of recent data.
Anomaly Detection, read 2026-11-12.
What can go wrong with Monte Carlo's numbers?
Monte Carlo explains that gaps can form in its history for a table, and those gaps can make its anomaly detection less sensitive. It offers exclusion windows to handle such periods.
In Monte Carlo's words:
These gaps are undesirable because they can reduce the sensitivity of Monte Carlo's anomaly detection.
Exclusion Windows, read 2026-11-12.Monte Carlo notes that the trend on its data quality dashboard can lag by several hours, while the current score reflects the latest monitor runs.
In Monte Carlo's words:
The trend data is on a delay of up to 12 hours.
Data quality, read 2026-11-12.Monte Carlo explains that a monitor can fail to run at all. It marks that case with an error status, which is different from a monitor that ran and raised an alert.
In Monte Carlo's words:
Error status means the monitor entirely failed to execute, not that it ran and alerted.
Data quality, read 2026-11-12.
How does Feder work with Monte Carlo?
- Feder has no connection to Monte Carlo today, so it reads nothing from it.
- The two can run side by side: Monte Carlo keeps doing its job, and Feder checks the numbers your other tools record against your own history.
- Feder only reads. It never changes anything in a connected app.
What should I ask about my Monte Carlo setup?
- Which numbers on my dashboard are counted at the source, and which are modeled or estimated?
- If this number stopped counting tomorrow, who would notice, and when?
- What does a normal week look like for this number, in my own history?
Questions owners ask
- Does Feder replace Monte Carlo?
- No. Keep Monte Carlo. Feder sits beside it.
- Does Feder send data into Monte Carlo?
- No. Feder only reads.
- How accurate is Feder?
- We do not publish an accuracy number yet. When there is a measured one, it will be here with how it was measured.
Where do these claims come from?
Every quoted statement about Monte Carlo on this page comes from Monte Carlo's own pages, quoted above with the date we read them. We read them again by 2027-05-11. If one changes, this page changes or comes down.