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...
(I'm not from Inkeep but I've seen and used their product.)
I'm not sure how they do it but the answer quality and the UI is meaningfully better than all the other "chat with your docs"-type products I've tried.
In other words the promised outcome isn't very original but they've nailed the execution.
give the playground a shot and let me know what you think.
we answer 250k+ customer-facing questions/mo today for teams who really care about quality (Anthropic, Clerk, Pinecone, Postman) - we're brining that same care and high bar to our copilot for support teams.
the generative UI and conversational aspect is quite different than other copilots we've seen.
Entry price of $150/month just to try it - regardless of volume.
Pretty sure most people will go to whoever has a free tier, and even that space will be competitive.
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
glad to hear!
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.
I first asked for "How to track failures" and it told me some code and how to look at analytics. Eventually I figured out that I had to explicitly track for hallucinations / up and down events etc.. so I was overly broad but was able to drill down and understand the system so maybe I was unclear but it taught me how your app works.
Unrelated, but has Cursor achieved this kind of mind share?
Last week, I heard about a company (I think it was an YC company) describing themselves as "open source Cursor".
Also last week, a comment here on HN stuck with me: "I live inside Cursor" https://news.ycombinator.com/item?id=41651380
And now, the Cursor for Help Desk.
I've used Cursor, and I loved it. 10 to 1 over regular GitHub Copilot, and well worth the $20 dollars and I am a hobby programmer (management job during the day).
But... all this? It has become the reference point just like we had "Uber for...", "AirBnb for...". It seems like it happened so fast.
Seems like it, whenever I ask mid/senior devs for suggestions on an AI copilot they all recommend Cursor. Haven't tried it though, my bottlenecks involve people and outdated docs ^_^
it is definitely all the rage in the AI community. what made it better than Github Copilot for you?
One thing that’s better: I’m converting a codebase to a new major library version with a lot of breaking changes. The suggestions in Cursor are working really well for this. You can make an edit to fix a call (or whatever), go to the next place and it suggests a similar edit, then just start hitting tab as it figures out where else you would want to do the same thing. It also seems to have recent edits in context so when you go to the next file it’s already primed to continue.
Good question, took me a while to figure out why I preferred over Copilot.
Number one was the "apply" suggestions from chat, but now I think Copilot has it too.
Number two are the suggestions while I am typing to change multiple lines at once. Such a time saver.
Number three is how I can send entire files/folders as reference in the chat.
Also, it feels a bit snappier? The suggestions seem to come a bit faster than Copilot.
In terms of correctness / good good, they're both equally good (and bad).
To me it's all about how much time I am saving. When I sit down 30-90 minutes 3-4 times a week to code, I just feel like it helps me to get more stuff done.
Have been a Cursor user for ~1yr. I think they just nailed the key workflows people wanted - i.e. the fully conversational side bar with "apply" buttons and easily being able to attach the right files or code snippets you want.
VS Code may have caught up now, but haven't looked back.
Highly recommended. Congrats on the HN launch.
Inkeep works great at Pinecone and meaningfully reduced the number of support tickets with common questions/issues.
that's the goal. And now with Keep the goal is to help the support team answer those questions that come through faster too. Minimizing "time to answer" across the funnel is the goal.
There is a typo in the title of your example https://copilot-demo.inkeep.com/?ticketId=new-ticket
"Escelating to humans from Inkeep AI Slack bot" : "Escelating" --> "escalating"
ty!
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.
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.
windmill.dev looks an awesome solution thanks for the link :)
nothing like closing the content loop! try to make that direct.
How does this compare to Q for 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.
We've built something like this at Helpjuice.com - we call it Swifty AI Chatbot. It's pretty cool to see companies that are building a completely open platform that works with all. Nice work folks!
Upvoted – looking forward to supporting you guys more
It's not a good look to piggyback off competitors' launches like this. Let them have their moment.
How much did you spend on the domain??
Not too bad - $3k.
how is this different to all the other identical "we attached ChatGPT to a web app" competitors?
how do you ensure that companies don't use this to make it impossible to actually contact a human? or do you feel that isn't in scope for a product that's encouraging companies to make it impossible to contact a human?
this one is designed for support agents - not to be customer facing. Whole goal is to make it more scalable to provide high-touch human-based support for teams who are keen on that.
Agree customer-facing AI has to be done in a tasteful and mindful way.