christophepas

100%, at much lower cost and accessible by SMBs on top of that. You can typically retrieve any data from your Intercom tickets, CRMs, Slack conversations, websites and documentation tools. We'll be also adding meeting transcripts but for now our customers build a custom sources and index these with our API.

Building back office tools is such a nightmare... Classic thing I had to build over and over when I freelanced, this would have helped a lot.

We've been using Forest for... 5 years? for our team, you created something special!

You take Notion as an example and I couldn't agree more.

We are their competitor and followed your exact line of thought trying and not releasing GPT in editor to avoid noise, and building ASK, an engine powered by semantic search, GPT (and a lot of other fun models for refinements), to answer all questions you could have on your knowledge base.

It's private, fast, works with real time edited documents, and it's already in production for thousands.

Check it out: slite.com/ask

We tackle this hard with slite.com, we just introduced slite.com/ask to find answer no matter how badly organised your documents are, and we offer document status to track outdated and up to date docs across your space (and we're still enhancing it, very much first version).

These among many others to help it not become a behemoth as you say.

We built the technology in house and don’t rely on chatgpt, but GPT alone, and services offer it in a similar way algolia or elastic offer search for instance, it keeps data private.

We just released a new feature for Slite, Ask, in private beta.

Slite is a team workspace that hosts all kinds of knowledge: wiki, docs, projects, discussions, and decisions. When we started playing with ChatGPT, we really wanted to offer a similar experience, by basing answers on your team documents.

It felt like a parallel change of paradigm: ChatGPT to get answers from the web, Ask to get answers from your internal knowledge.

The technology under the hood is of course different: It uses GPT3 and advanced semantic search, with special ponderation based on your team activity, document linkage and so on. And of course it respects privacy - its answers are only based on what you can access.

The interface is less conversational - for now. But it's already a massive upgrade from your classic search experience, and it goes beyond that. You can really ask it anything, even stuff that's not specifically documented. The engine will look at various sources and compile them to answer.

First testers love it, and we believe it can radically change the way we work with documentation in the future. Check it out!

We just released a new feature for Slite, Ask, in private beta.

Slite is a team workspace that hosts all kinds of knowledge: wiki, docs, projects, discussions, and decisions. When we started playing with ChatGPT, we really wanted to offer a similar experience, by basing answers on your team documents.

It felt like a parallel change of paradigm: ChatGPT to get answers from the web, Ask to get answers from your internal knowledge.

The technology under the hood is of course different: It uses GPT3 and advanced semantic search, with special ponderation based on your team activity, document linkage and so on. And of course it respects privacy - its answers are only based on what you can access.

The interface is less conversational - for now. But it's already a massive upgrade from your classic search experience, and it goes beyond that. You can really ask it anything, even stuff that's not specifically documented. The engine will look at various sources and compile them to answer.

First testers love it, and we believe it can radically change the way we work with documentation in the future. Check it out!

Slite

Super clear and useful!

The performance definitely is something we improved a lot, and indeed relational data - I guess you mean roll ups in database- is not something we allow at the moment, thanks for sharing again!

Thanks for sharing! What was inferior about Slite (and when did you use it)?

I’m working on it, would love to hear your takes, especially as in term of performance and speed we worked heavily this year and believe to have reached something superior to alternatives.