The use case: how Intercom deploys Honeycomb
Intercom uses Honeycomb with distributed tracing to observe Fin, its customer support AI agent, surfacing customer-centric and business-centric signals to improve end-to-end latency and reduce costs. They also set up SLOs to prevent degradation of their systems.
In the customer’s words
We were so focused on Fin’s latency that we lost touch with our own business by incurring extra operational cost. Luckily, thanks to the great tracing we already had, we were able to identify and fix the issue. To validate our fixes, we used the same query that Finance was using to quantify the extra LLM cost. We were happy to observe the LLM waste % going down, confirming our fix.Other AI tools used by Intercom
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Explore Intercom’s AI stack
Other companies using Honeycomb
Customers across industries, with public evidence.
AmperityConfirmed
Booking.comConfirmed
DepotConfirmed
DuolingoConfirmed
FenderConfirmed
FreshpaintConfirmedGo straight to the source
Based on Honeycomb’s published case study. We check the public evidence; the results are reported by the vendor.
honeycomb.io- Source published
- Nov 7, 2025
- Last checked
- Nov 13, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Intercom.
- The publication dateChecked
Read from the page’s own metadata, never guessed.
- Intercom uses HoneycombChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Hear how Intercom used Honeycomb to surface customer-centric signals to improve end-to-end latency of its Fin.ai customer support agent