We've been a customer for the past year (https://speakeasy.com/docs). I was honestly highly skeptical about putting a RAG powered search in front of our documentation site instead of what we were using (FlexSearch / Nextra). Have been delighted to be proved wrong.
The learning I've had is that whilst the majority of queries go through standard search patterns (i.e. users search for something that's covered by documentation), a subset of queries are not answerable by our documentation but only implied by it. I've direct experience that Inkeep is serving a large part of that user segment and reducing our support burden.
As a very recent/specific example from last week, we had a community user generating a terraform provider for an internal use-case. By putting error messages from our CLI tooling into Inkeep's "Ask AI" feature, they discovered a nuance in "x-speakeasy-match" (the error message implied it created a circular reference, but didn't spell that out) and self-served a solution.
Inkeep effectively turned our documentation into a guided tutorial on our product, specific to the customer. Pretty strong ROI.
The learning I've had is that whilst the majority of queries go through standard search patterns (i.e. users search for something that's covered by documentation), a subset of queries are not answerable by our documentation but only implied by it. I've direct experience that Inkeep is serving a large part of that user segment and reducing our support burden.
As a very recent/specific example from last week, we had a community user generating a terraform provider for an internal use-case. By putting error messages from our CLI tooling into Inkeep's "Ask AI" feature, they discovered a nuance in "x-speakeasy-match" (the error message implied it created a circular reference, but didn't spell that out) and self-served a solution.
Inkeep effectively turned our documentation into a guided tutorial on our product, specific to the customer. Pretty strong ROI.