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

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

#1
Hi HN, We’re Nick and Robert, founders of Inkeep (https://inkeep.com). We help companies turn their content into AI support copilots. So far, we’d focused on customer-facing experiences (e.g. find us as an “Ask AI” button in the docs of companies like Anthropic and Pinecone). Today, we’re excited to share our new copilot, Keep, which is designed specifically for support agents.

It’s a conversational sidebar you can use as an app for Zendesk or Chrome Extension for any support platform. There’s a demo video at https://vid.inkeep.com/cx-copilot or you can try the live sandbox with example tickets at https://try.inkeep.com/cx-copilot.

Why? Most AI support tools today are focused on trying to have AI answer customer questions before they even reach support teams (‘deflection’). We’d focused on that too. However, we heard from many of our customers that while they care about deflection, they care even more about providing high-quality, fast human support when users need it. Some teams don’t even want customer-facing AI at all and just want AI tools to help their team be more efficient. We created Keep with these scenarios in mind.

Keep does a few neat things we haven’t seen elsewhere:

1. Provides intelligent suggestions: if Keep is confident, it’ll create a draft answer and tell you the sources it used. If the ticket is long, it’ll summarize the conversation so far and outline the remaining to-dos. All automatic and contextual to the ticket.

2. Is fully conversational: ask for clarifications, revise draft answers, and iterate as needed.

3. Uses ‘Generative UI’: suggestions are rendered as glanceable, interactive UI components. For example, a draft answer has buttons like “Shorten” & “Concise” that prompt the AI to revise the answer. UI components are interweaved within normal text.

4. Turns tickets into FAQs: can generate an FAQ from a closed ticket and lets you iterate on it and save it when done.

5. Leverages many content types: uses your docs, help center, previous support tickets, Slack threads, etc.

We were inspired by tools like Cursor, Claude Artifacts, and v0. These experiences go beyond plain-text conversations by interweaving interactive code blocks or UI previews into their answers. This makes answers digestible and intuitive (and fun) to iterate on.

Some technical details, for those interested: We use the Vercel AI SDK to optimistically stream the React components by using our Chat APIs, which are powered by Claude Sonnet 3.5 and our RAG service. Our APIs follow the OpenAI chat completion format so are generally compatible with any LLM tooling. Our `inkeep-qa` API generates draft answers and the `inkeep-context` API generates structured outputs and tool calls (docs: https://go.inkeep.com/ai-api). For an example of how these APIs are used, check out our Intelligent Support Form example (demo: https://try.inkeep.com/ai-form, repo: https://quickstart.inkeep.com/ai-form).

If you want to try Inkeep on your product's content, just fill out the form in our landing page. You’ll get a demo in your inbox powered by your public content — NO “call us”, “book a demo”, or “schedule a meeting” required. Note: we do check that your email domain matches your content to prevent spam.

Curious to hear about your experiences when working with customer/support questions and any ideas on how else the copilot could be useful for those scenarios.

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

#4
I tried this question "How do you track for failures of the service?" I had to drill down multiple times but it did give me a good understanding of the service. I did notice that it was also giving results in javascript. Looks interesting and I have problems with my own RAG app https://www.securday.com

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

#6

I tried this question "How do you track for failures of the service?" I had to drill down multiple times but it did give me a good understanding of the service. I did notice that it was also giving results in javascript. Looks interesting and I have problems with my own RAG app https://www.securday.com

was this in the support copilot or our public-facing bot on our landing page? for my fyi what did you mean by 'failures' of the service, can look to create some content relating to that.

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

#9

How are you measuring the confidence of the answers? This is one of the biggest challenges I've seen with AI, it provides wrong answers to hard questions, which wastes the user's time.

Take a look at https://docs.inkeep.com/ai-api/openai-chat-completion-endpoi...

tl;dr we define a JSON schema with a few semantic labels that represent a gradient in confidence. On our end we prompt it with certain examples and guidance for when to use each label. This is generally a better approach than e.g. asking an LLM to give a numeric score.

We also have trained embedding-based classifiers as non-LLM heuristics.

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

#10
post #7

How does this compare to Q for Business? https://aws.amazon.com/q/business/

My understanding is that Q is a general purpose internal ai/search service - similar to Glean or Microsoft's equivalents.

Our tool focuses on support use cases (customer-facing or internal-facing), which means we can go deep with workflows like detecting gaps in your documentation and focusing our efforts on quality around these scenarios. Generally our support copilot intro'd here also generates dynamic UIs so goes beyond a normal chat interface.

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