Explore Singapore with AI and RAG
Singapore Legal RAG: Triple-AI Backend, Apple-Style UI.
What it does
A sophisticated RAG intelligence engine for Singaporean laws, policies, and history. Comes with a triple-AI failover backend (Gemini/Llama/Groq), semantic embeddings using FAISS, and an Apple-inspired interactive UI. Designed with precision and high availability in mind.
Does a similar job
all alternatives →
- IBI built a RAG engine to search Singaporean lawsFeb 2026 · github.com · ▲5
I built a "Triple Failover" RAG for Singapore Laws, then rewrote the logic based on your feedback. Hi everyone! I’m a student developer. Recently, I created Explore Singapore, a RAG-based search engine that scrapes about 20,000 pages of Singaporean government acts and laws. I recently posted the MVP and received some tough but essential feedback about hallucinations and query depth. I took that feedback, focused on improvements, and just released Version 2. Here is how I upgraded the system from a basic RAG to a production-grade one. The Design & UI I aimed to avoid a dull government…
- AOAnythingLLM – Open-Source, All-in-One Desktop AI Assistant2024 · github.com · ▲368
Hey HN! This is Tim from AnythingLLM (https://github.com/Mintplex-Labs/anything-llm). AnythingLLM is an open-source desktop assistant that brings together RAG (Retrieval-Augmented Generation), agents, embeddings, vector databases, and more—all in one seamless package. We built AnythingLLM over the last year iterating and iterating from user feedback. Our primary mission is to enable people with a layperson understanding of AI to be able to use AI with little to no setup for either themselves, their jobs, or just to try out using AI as an assistant but with *privacy by…
- TATurn any website into a knowledge base for LLMs2024 · embedding.io · ▲305
I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 19d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
