AI · alternatives · 2026
24 alternatives to ReLLM
Permission sensitive, encrypted context api for GPT LLMs
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. ReLLM launched in 2023; newer entries below may have overtaken it.
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Hey, we're excited to share ReLLM! ReLLM provides developers with an API to quickly add permission sensitive context for LLM's such as chatGPT. ReLLM goes a step further and also encrypts all of your plain text data at rest. The Motivation: We built ReLLM, because while developing a different application we realized there was not a great way to provide our users context for their GPT questions that was limited to only the data they are allowed to see. ReLLM is fully functional with 2 API endpoints. One to embed data, and one to invoke chat with GPT.
2023 · rellm.ai · its alternatives →
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GPTGuard▲286Keep your ChatGPT conversations secure and private
2024 · gptguard.ai · its alternatives →
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New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
2023 · github.com · its alternatives →
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Rememberall▲201Open source solution for long term memory for LLMs
2024 · github.com · its alternatives →
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Twigg▲157Hi HN, we’re Jamie and Matti, co-founders of Twigg. During our master’s we continually found the same pain points cropping up when using LLMs. The linear nature of typical LLMs interfaces - like ChatGPT and Claude - made it really easy to get lost without any easy way to visualise or navigate your project. Worst of all, none of them are well suited for long term projects. We found ourselves spending days using the same chat, only for it to eventually break. Transferring context from one chat to another is also cumbersome. We decided to build something more intuitive to the ways humans think.…
Oct 2025 · twigg.ai · its alternatives →
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MaskLLM▲132Mask your LLM APIs for secure rotation and logging
2025 · maskllm.com · its alternatives →
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I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps. The deeper problem 1. Not portable – context is vendor-locked; nothing travels across tools. 2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance. 3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried. Demo video:…
2025 · github.com · its alternatives →
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Bash4LLM is a single-file Bash wrapper for interacting with LLMs from the terminal. I created it because I wanted something simple that worked without installing Python, Node, or any other runtime. It uses only Bash, curl, and jq. You can send prompts, start a small chat, process files line by line, stream output, and save session metadata in JSON format. I tried to make it safe and predictable: no use of the system /tmp, no use of eval. Groq is supported by default, and other providers can be added with dedicated Bash scripts in the extras/providers/ folder. Example: echo…
Jun 2026 · github.com · its alternatives →
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Author here. I wanted to keep my conversation with #Gemini about code handy while discussing something creative with #ChatGPT and using #DeepSeek in another window. I think it's a waste to have Electron apps and so wanted to chat with LLMs on my own terms. When I discovered the llm CLI tool I really wanted to have convenient and pretty looking access to my conversations, and so I wrote gtk-llm-chat - a plugin for llm that provides an applet and a simple window to interact with LLM models. Make sure you've configure llm first (https://llm.datasette.io/en/stable/) I'd…
2025 · github.com · its alternatives →
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Shared persistent memory across all your LLMs.
2025 · teamlayer.xyz · its alternatives →
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Chat LLMs▲17Engage in free conversations with advanced LLMs.
2025 · chats-llm.com · its alternatives →
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Current AI-assisted CLI tools are often part of larger systems and work better on Linux. I built llm-term to address these. It's a Rust-based tool that compiles into a single binary file. You only need to download the binary, add it to your PATH, and configure your OpenAI key to get started. While llm-term offers an option for gpt-4o, it works great with gpt-4o-mini. So it's not costly. I appreciate any feedback or suggestions.
2024 · github.com · its alternatives →
- 18CW
2024 · llmchat.co · its alternatives →
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The most secure Windows client for Multi-LLM / AI chat
2025 · llmsymphony.io · its alternatives →
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We’ve built the Cape API so developers can keep sensitive data private while prompting LLMs like GPT-4 and GPT 3.5 Turbo. With Cape, you can easily de-identify sensitive data before sending it to OpenAI. In addition, you can create embeddings from sensitive text and documents and perform vector searches to improve your prompt context all while keeping the data confidential. Developers are using Cape with data like financial statements, legal contracts, and internal/proprietary knowledge that would otherwise be too sensitive to process with the ChatGPT API. You can try CapeChat, our…
2023 · capeprivacy.com · its alternatives →
- 21
Hi HN, I’m the founder of Pangea. We’ve built a developer platform where you can easily add security to your code through a simple set of APIs - features like authentication, secrets management, audit logging, redaction of PII, restricting embargoed countries, known threat actor intelligence, etc. With the ChatGPT and LLM explosion, we thought of ways to reduce the risk of both the inputs and outputs from these services. Our NextJS sample app adds a security layer on top of ChatGPT with various security services that you can implement quickly. It’s basically a front end to the OpenAI API…
2023 · github.com · its alternatives →
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Good morning HN! For a while now I have been toying with this idea and now finally have a working prototype. This project allows you to encode secret messages into ordinary looking text by using arithmetic coding with a probability model derived from an LLM. By encrypting the message and then decompressing the encrypted message using the arithmetic coder, you get output which looks just like randomly sampled output from the LLM. Except, it actually encodes your secret messages in the specific choices of tokens. By using authenticated encryption, only a user who knows the key can know that a…
2025 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →