The use case: how MongoDB deploys Profound
MongoDB uses Profound to monitor and measure how Answer Engines respond to questions about MongoDB, benchmarking LLM answers against gold standard answers and flagging inaccurate citations for the content team to fix. It also uses Profound Agents for citation aggregation reporting and schema markup recommendations.
More reported results
Figures published in Profound’s case study. They are not independently measured by usedby.
They achieved accuracy rates above 90% for MongoDB-related queries.
a schema markup recommendation Agent that cuts the time to update releases by almost 30%.
In the customer’s words
If an Answer Engine gives the wrong information about how to configure MongoDB, the developer doesn't have a bad experience with the AI, they have a bad experience with us.Other AI tools used by MongoDB
Other public relationships recorded on usedby.
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Profound users in Data & Analytics
Companies in the same sector, with public evidence.
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Go straight to the source
Based on Profound’s published case study. We check the public evidence; the results are reported by the vendor.
tryprofound.com- Last checked
- Oct 8, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 50%Checked
The figure is on the page; its label is our wording.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of MongoDB.
- MongoDB uses ProfoundChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Since working with Profound, MongoDB has seen a 50% increase in AI Search visibility.