Launched this week
LyzrGPT

LyzrGPT

Private, secure & model-agnostic AI chat for enterprises

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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.
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Launch tags:Sales•Marketing•Artificial Intelligence
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What do you think? …

Mohammed Faraaz Ahmed
Lyzr
📌
Hey Product Hunt 👋 We built LyzrGPT because enterprises told us the same thing again and again: “We want ChatGPT-level intelligence, but we can’t risk our data leaving our environment.” LyzrGPT is a private, enterprise AI chat platform that runs inside your own ecosystem. Your data stays with you. No vendor lock-in. Full control. You can also switch between multiple AI models (like OpenAI or Anthropic) within the same conversation and maintain secure, long-term context across sessions. We’d love your feedback: 1. What’s stopping your org from adopting AI chat today? 2. What security or compliance concerns do you face? Happy to answer questions in the comments. Thanks for checking us out 🙌
Pavan Teja
LyzrGPT
Maker
📌

Found great use cases for enterprise and individual uses, do check it out!!

Pradipta Ghoshal
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!

Rida Mahveen
Hunter

@pradipta_ghoshal Thank you for the kind words! That’s exactly the gap we’re addressing.

Curious Kitty
Product Hunt
When a buyer compares you to rolling their own stack with an open-source UI + an LLM proxy and buying a secure enterprise chat from a big vendor, what are the 2–3 decisive differences that reliably make them choose LyzrGPT—and where do you intentionally not compete?
Pavan Teja
LyzrGPT
Maker

@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!

Hashif Habeeb

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?

Pavan Teja
LyzrGPT
Maker

@hashif_habeeb 

The actual text content of relevant memories is sent to the LLM for inference - that's how AI works. But:

  1. We control what gets sent

  2. We control how much context

  3. Original files never leave our infrastructure

So essentially yes, your data lives with us, we just ask the AI questions about it.

Hashif Habeeb

@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
A great idea and really understands business needs for compliance. Checked a bit and the fact that you can create these agents or employees to handle tasks that usually are handled by humans without compromising on compliance or quality is amazing. I believe in the idea. Just as a feedback, I believe the landing page is quite dense and can benefit from a clearer structure. Wish you all the luck
Rida Mahveen
Hunter

@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

shreya chaurasia

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?

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