LyzrGPT
Private, secure & model-agnostic AI chat for enterprises
202 followers
Private, secure & model-agnostic AI chat for enterprises
202 followers
LyzrGPT is a private, enterprise-grade AI chat platform built for security-first teams. Deploy it inside your own ecosystem to keep data fully private. Switch between multiple AI models like OpenAI and Anthropic in the same conversation, avoid vendor lock-in, and retain secure contextual memory across sessions. Built for enterprises and regulated industries.
Lyzr
LyzrGPT
Found great use cases for enterprise and individual uses, do check it out!!
Lyzr
So many Enterprises can benefit from this! I have seen a couple of them spending months on R&D and then finally creating a somewhat okay, brittle internal solution. This will not only reduce that time drastically but also the employees finally get to use something that actually works and do not have to end up using the public softwares to get work done. Kudos to the team for such a good job!
@pradipta_ghoshal Thank you for the kind words! That’s exactly the gap we’re addressing.
Product Hunt
LyzrGPT
@curiouskitty Great question!
-> In a DIY stack, you pay all of the vendors individual plans and then setup the whole architecture, would you do that or rather top up just one form of credits?
-> Not only that, LyzrGPT can automatically switch the model for the exact use-case, giving you the best output at all times.
-> With the import memory feature, no more filling in long context messages, once you import your previous memory from our memory pocket modal, no matter what model you choose, your memory is present and up to date!
When you say data stays on your server, does that mean the files remain there but relevant information is still sent to GPT or Anthropic as context? How does that work?
LyzrGPT
@hashif_habeeb
The actual text content of relevant memories is sent to the LLM for inference - that's how AI works. But:
We control what gets sent
We control how much context
Original files never leave our infrastructure
So essentially yes, your data lives with us, we just ask the AI questions about it.
@pavan_teja8 Thanks Pavan, I'm a developer myself and have built RAG-based systems for enterprise use cases. Your explanation aligns with how this is typically implemented (embeddings + controlled context windows). In practice though, I've seen highly security-conscious enterprises lean toward fully on-prem or self-hosted models to avoid any data exposure during inference.
@zahran_dabbagh Thank you so much for taking the time to check us out and for the thoughtful feedback really appreciate it.Totally hear you on the landing page feedback as well. We’re actively iterating on the structure to make the value clearer and less dense, especially for first-time visitors. Inputs like this genuinely help us improve.
Hope you’ll continue following our journey
Running the AI chat inside the company’s own ecosystem is a big trust unlock.
Curious how difficult deployment typically is for enterprises with complex infra. Is this closer to plug-and-play or a guided rollout?