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Launch HN: Inkeep (YC W23) – Copilot for Support (think Cursor for help desks)

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41–50 of 62 posts

Re: Launch HN: Inkeep (YC W23) – Copilot for Support (think Cursor for help desks)

#41

We are customers at windmill.dev and we are really happy with it. It also motivates us to write ever better docs as it means more answers can be an answered completely by the bot.

Anyone downvoting this should know that other YC companies endorsing a product launch is a certified HN classic, and by downvoting it, you're violating a long and rich tradition.

Re: Launch HN: Inkeep (YC W23) – Copilot for Support (think Cursor for help desks)

#42
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.

Re: Launch HN: Inkeep (YC W23) – Copilot for Support (think Cursor for help desks)

#44

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 docum…

best way to frame the customer-facing AI: guided tutorials on-demand that can translate between user terminology and product lingo.

Re: Launch HN: Inkeep (YC W23) – Copilot for Support (think Cursor for help desks)

#45
post #37

How is this different/unique than the thousands of other competitors that pretty much promise the same thing? sorry if it sounds dismissive of your product, but that's my first impression, and probably a lot of other ppl's too, so would be good to get a good answer...

Feel free to correct me on that, but here's my understanding. The comprehensive support products cover four main sub-products: 1. FAQ/Knowledge bases with search functionality. 2. Conversational mediums and agent notifications (e.g., live chat widget, messenger support). 3. Ticket management systems and agent management, which is the core of Zendesk/Intercom. This is the most difficult to operationalize as it require…

are you implying that a custom implementation service for enterprises is a good business?

Re: Launch HN: Inkeep (YC W23) – Copilot for Support (think Cursor for help desks)

#48

Do you have any stats / benchmarks of how often it answers a question correctly that's present in the customer's documentation?

We measure the opposite now - % of questions where the bot was not able to find documentation to answer and it doesn't exist. This powers our insights reporting. We generally don't hear complaints about false positives here (i.e., cases where there were docs), so anecdotally, I'd guess 95%+ else our reporting wouldn't be very useful.

Re: Launch HN: Inkeep (YC W23) – Copilot for Support (think Cursor for help desks)

#49
post #16

Inkeep has been very solid for us and running in our Discord. https://milvus.io/community Robert spoke at our meetup and is awesome. https://www.youtube.com/watch?v=35JdjmiDvWI

The developer community of milvus vector database benefits a lot from the inkeep ask-ai-button in discord and milvus.io website. As a user we are happy with the rich feature set of inkeep, like integration with github/discord, admin tool to study user's questions to identify issues in product or documentation. These features are often overlooked when people talk about RAG solutions but they turned out to be very important from our experience using RAG in a real world scenario. This agentic workflow of Keep feels a great addition to the existing core RAG functionality.
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