Yes of course. We have done this before. Check out https://chatbotkit.com in particular https://chatbotkit.com/examples/travel-experiences. There are multiple ways this can be achieved depending on your data. If your data is already available in some sort of API that can be queried the simplest way is to use a skillset. The bot will be able to pull the requested information and talk to the user about it. Source: about 1 year ago

Maybe build your own with chatbotkit.com? Source: about 1 year ago

We are excited to announce the launch of ChatBotKit - a no-code conversational AI platform for building chatbots, customer support agents, study assistants, and much more! ChatBotKit is an easy-to-use platform that allows you to connect with other platforms such as Zapier, Slack, Discord, WhatsApp, Notion, and many others, making it easier to build an army of agents that do things on your behalf. Our team has... Source: about 1 year ago

Also chatbotkit.com if you are looking for something more professional with strong focus on APIs and integrations. Source: about 1 year ago

Https://lindy.ai/?kid=2NAN3C - worth a look if your time management, like mine, is critical to your weekly schedule and task list. Source: about 1 year ago

Nice to see yet another open source approach to LLM/RAG. For those who do not want to meddle with the complexity of do-it-youself, Vectara (https://vectara.com) provides a RAG-as-a-service approach - pretty helpful if you want to stay away from having to worry about all the details, scalability, security, etc - and just focus on building your RAG application. - Source: Hacker News / 3 months ago

You should also check us out (https://vectara.com) - we provide RAG as a service so you don't have to do all the heavy lifting and putting together the pieces yourself. Source: 6 months ago

Hi HN! I lead product for Vectara (https://vectara.com) and we recently worked with OpenSource connections to both evaluate our new home-grown embedding model (Boomerang) as well as to help users start more quantitatively evaluating these systems on their own data/with their own queries. OSC maintains a fantastic open source tool, Quepid, and we worked with them to integrate Vectara (and to use it to... - Source: Hacker News / 8 months ago

RAG is a very useful flow but I agree the complexity is often overwhelming, esp as you move from a toy example to a real production deployment. It's not just choosing a vector DB (last time I checked there were about 50), managing it, deciding on how to chunk data, etc. You also need to ensure your retrieval pipeline is accurate and fast, ensuring data is secure and private, and manage the whole thing as it... - Source: Hacker News / 9 months ago

I agree. My experience is that hybrid search does provide better results in many cases, and is honestly not as easy to implement as may seem at first. In general, getting search right can be complicated today and the common thinking of "hey I'm going to put up a vector DB and use that" is simplistic. Disclaimer: I'm with Vectara (https://vectara.com), we provide an end-to-end platform for building GenAI products. - Source: Hacker News / 9 months ago