Honestly surprised something like this can get funded
For most people, the chat is the entrypoint to LLMs, and people are growing to expect more and more. So now it might be basic chat, web search, internal RAG, deep research, etc. Very soon, it will be more complex flows kicked off via this interface (e.g. cleaning up a Linear project). The same "chat UI" that is used for basic chat must (imo) support these flows to stay competitive.
On the engineering side, things like Deep Research are quite complex/open-ended, and there can be huge differences in quality between implementations (e.g. ChatGPTs vs Claude). Code interpreter as well (to do it securely) is quite a tricky task.
That being said, I think there is an opportunity for them to discover and serve an important enterprise use case as AI in enterprise hits exponential growth.
On another axis, if you are able to offer BYOK deployments and the customers have huge staff with low usage, it's pretty easy to compete with the big players due to their high per-seat pricing.
The common trend we've seen is that most of these other projects are okay for a true "just send messages to an AI and get responses" use case, but for most things beyond that they fall short / there a lot of paper cuts.
For an individual, this might show up when they try more complex tasks that require multiple tool calls in sequence or when they have a research task to accomplish. For an org, this might show up when trying to manage access to assistants / tools / connected sources.
Our goal is to make sure Onyx is the most advanced and mature option out there. I think we've accomplished that, so if there's anything missing I'd love to hear about it.
I have used vercel for several projects and I'm not tied to it, but would like to understand how onyx is comparable.
Benefits for my use cases for using vercel have been ease of installation, streaming support, model agnosticity, chat persistence and blob support. I definitely don't like the vendor lock in, though.
we have all of those!
> how onyx is comparable
For an AI-powered research assistant, Onyx might just work out of the box. We have ~45 connectors to common apps (https://github.com/onyx-dot-app/onyx/blob/main/backend/onyx/...), integrations with the most popular web search providers (https://github.com/onyx-dot-app/onyx/blob/main/backend/onyx/...), and a built in tool calling loop w/ deep research support (https://github.com/onyx-dot-app/onyx/blob/main/backend/onyx/...). If you wanted to customize, you could pretty easily tweak this / add additional tools (or even rip this out completely and build your own agent loop).