Alternatives

Products that do what Ajah does

Self-hostable LLM safety layer with RAG verification

1AL
Any-LLM – Lightweight router to access any LLM Provider▲125
We built any-llm because we needed a lightweight router for LLM providers with minimal overhead. Switching between models is just a string change : update "openai/gpt-4" to "anthropic/claude-3" and you're done. It uses official provider SDKs when available, which helps since providers handle their own compatibility updates. No proxy or gateway service needed either, so getting started is pretty straightforward - just pip install and import. Currently supports 20+ providers including OpenAI, Anthropic, Google, Mistral, and AWS Bedrock. Would love to hear what you think!
2025 · github.com
2AS
Amla Sandbox – WASM bash shell sandbox for AI agents▲146
WASM sandbox for running LLM-generated code safely. Agents get a bash-like shell and can only call tools you provide, with constraints you define. No Docker, no subprocess, no SaaS — just pip install amla-sandbox
Jan 2026 · github.com
3RP
RAGstack – private ChatGPT for enterprise VPCs, built with Llama 2▲84
Hey hacker news, We’re the cofounders at Psychic.dev (http://psychic.dev) where we help companies connect LLMs to private data. With the launch of Llama 2, we think it’s finally viable to self-host an internal application that’s on-par with ChatGPT, so we did exactly that and made it an open source project. We also included a vector DB and API server so you can upload files and connect Llama 2 to your own data. The RAG in RAGstack stands for Retrieval Augmented Generation, a technique where the capabilities of a large language model (LLM) are augmented by retrieving information…
2023 · github.com
4UL
Using LLMs and Embeddings to classify application errors▲65
Hi Hacker News! We’re Vadim and Chris from Highlight.io [1]. We do web app monitoring and are working on using LLMs/embeddings to add new functionality to our error monitoring product. Given that there’s a lot of founders/engineers using LLMs in their products, we figured we’d share how we built the new functionality, their impact on our workflows, and how you can try it out. Our goal was to build two features: (1) tagging errors (e.g. deeming an error as “authentication error” or a “database error”); and (2) grouping similar errors together (e.g. two errors that have a different…
2023 · github.com
5OS
Open-source model and scorecard for measuring hallucinations in LLMs▲65
Hi all! This morning, we released a new Apache 2.0 licensed model on HuggingFace for detecting hallucinations in retrieval augmented generation (RAG) systems. What we've found is that even when given a "simple" instruction like "summarize the following news article," every LLM that's available hallucinates to some extent, making up details that never existed in the source article -- and some of them quite a bit. As a RAG provider and proponents of ethical AI, we want to see LLMs get better at this. We've published an open source model, a blog more thoroughly describing our methodology (and…
2023 · vectara.com
6
Heym▲83
Self-hosted AI workflow automation with agents, RAG, and MCP
Apr 2026 · heym.run
7
Agihalo▲68
LLM Router for A.I Agent & Saas with x402
Jan 2026
8AO
Airgapped Offline RAG – Run LLMs Locally with Llama, Mistral, & Gemini▲9
I've built an airgapped Retrieval-Augmented Generation (RAG) system for question-answering on documents, running entirely offline with local inference. Using Llama 3, Mistral, and Gemini, this setup allows secure, private NLP on your own machine. Perfect for researchers, data scientists, and developers who need to process sensitive data without cloud dependencies. Built with Llama C++, LangChain, and Streamlit, it supports quantized models and provides a sleek UI for document processing. Check it out, contribute, or suggest new features!
2024 · github.com
9ML
Mnemo – local-first AI memory layer for any LLM (Rust, SQLite,petgraph)▲60
Jun 2026 · github.com
10HY
Helicone (YC W23) – OSS LLM Observability and Development Platform▲29
Hey HN, we're Justin and Cole, the founders of Helicone (https://helicone.ai). Helicone is an open-source platform that helps teams build better LLM applications through a complete development lifecycle of logging, evaluation, experimentation, and release. You can try our free demo by signing up (https://helicone.ai/signup) or self-deploy with our new fully open-source helm chart (https://helicone.ai/selfhost). When we first launched 22 months ago, we focused on providing visibility into LLM applications. With just a single line of code, teams could…
2025 · github.com
11OS
Open-source project that use LLM as deception system▲10
Hello everyone I wanted to share a project I've been working on that I think you'll find really interesting. It's called Beelzebub, an open-source honeypot framework that uses LLMs to create incredibly realistic and dynamic deception environments. By integrating LLMs, it can mimic entire operating systems and interact with attackers in a super convincing way. Imagine an SSH honeypot where the LLM provides plausible responses to commands, even though nothing is actually executed on a real system. The goal is to keep attackers engaged for as long as possible, diverting them from your real…
2025
12FA
Foreman, a self-hosted LLM gateway for cost aware model routing▲15
Jul 2026 · github.com
13SH
Self-hosted gateway to access LLMs, Ollama, ComfyUI and FFmpeg servers▲13
2024 · openai.servicestack.net
14JS
Joinable's RAG-in-a-Box – fastest way to build a RAG App for your data▲5
Hey HN, I’m Julia, my team and I are building Rag-in-a-Box (https://www.joinable.ai/rag-in-a-box), hosted RAG service that let’s builders of any skill level launch their own RAG app loaded with their own data in minutes. [ What can you do ] 1. Load your documents (PDFs, CSV, PPTs, Word Docs, etc) and make them searchable instantly. All your data stays private and encrypted. 2. Choose latest open source LLM (Llama 4, Deepseek, GPT-oss, etc) to interact with your docs 3. Access your hosted RAG via API - build your own custom front end or integrate with your existing product…
2025 · joinable.ai
15
Ragie: Agent-Ready RAG-as-a-Service▲21
Smarter RAG with Agentic Retrieval & Context-Aware MCP
Sep 2025
16
Self-Hosted RAG with Llama 3▲1
100% offline RAG for engineers who can't use cloud AI
19d ago · philyeh.gumroad.com
17CA
ChunkBack – A Fake LLM API server for testing apps without paying▲6
Hi HN, I've been working with LLMs in production for a while both as a solo dev building apps for clients and working at an AI startup. The one thing that always was a pain was to pay OpenAI/Gemini/Anthropic a few dollars a month just for me to say "test" or have a CI runner validate some UI code. So I built this server called ChunkBack, that mocks the popular llm provider's functionality but allows you to type in a deterministic language: `SAY "cheese"` or `TOOLCALL "tool_name" {} "tool response"` I've had to work in some test environments and give good results for experimenting…
Nov 2025 · github.com
18MI
Mockingbird is an LLM that outperforms GPT4 on RAG▲9
Hi HN! I lead product at Vectara and we've just released a new LLM in our platform that outperforms GPT4 and Gemini 1.5 Pro on RAG tasks. Vectara is a Retrieval Augmented Generation (RAG) platform primarily deployed as a SaaS service which includes a generous free tier so you can try it for free. The way we've been able to offer a "better but cheaper" is that we focus a lot of our attention on taking smaller models (which can be hosted in a cost efficient way) and fine tuning them to specific tasks: in this case RAG. This ends up with a model that is less capable of arbitrary tasks like…
2024 · vectara.com
19RA
ragapi – an API for using LLMs on your own data▲12
2023 · ragapi.com
20AG
AxonFlow, governing LLM and agent workflows▲11
Hi HN, we’re building AxonFlow for teams running LLMs or agents in real production systems. Once agent workflows move past demos, failures are rarely model issues. They tend to show up as execution problems during real runs. Short 2-minute technical demo showing execution control and auditability in practice: https://youtu.be/FNgnESo9RtI AxonFlow is a self-hosted, source-available (BSL 1.1) control plane that sits inline in the execution path and governs LLM calls, tool calls, retries, approvals, and policy enforcement step by step. It does not replace your orchestrator and…
Jan 2026
21IM
I'm tired of my LLM bullshitting. So I fixed it▲5
As a handsome local AI enjoyer™ you’ve probably noticed one of the big flaws with LLMs: It lies. Confidently. ALL THE TIME. I’m autistic and extremely allergic to vibes-based tooling, so … I built a thing. Maybe it’s useful to you too. The thing: llama-conductor llama-conductor is a router that sits between your frontend (eg: OWUI) & backend (llama.cpp + llama-swap). Local-first but it should talk to anything OpenAI-compatible if you point it there (note: experimental so YMMV). LC is a glass-box that makes the stack behave like a deterministic system, instead of a drunk telling a story about…
Jan 2026
22
LLM Router · One API for every provider▲3
Dev tool that worries about your LLM API failures.
Aug 2026 · llmrouter.dpdns.org
23AB
A/B testing LLM silence with one system-prompt toggle▲10
Jun 2026 · twitter.com
24MR
Millwright – Rust-based, self-hosted LLM router▲10
Hey HN, With the news of OpenRouter possibly being acquired and proliferation of hosted LLM routers (i.e. Ramp Router, Vercel’s AI Gateway), I saw the need for a self hosted solution focused on cost savings, transparency, and performance. So, I built an open sourced router with a simple CLI interface that can easily sit between coding agents and GenAI workloads. For the curious and lazy, at the moment, Millwright has the tools for, - Providers: OpenAI-compatible APIs, Anthropic, Amazon Bedrock - Routing: policy-controlled model roles (cheap, mid, frontier), cheapest healthy route selection -…
Jul 2026 · github.com

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