@Banshee_1212 · X

building a deepfake detection platform,

@iASHeeesh · X

@Griffithjade626 · X

@Laharmckenzie · X

ds246 · HN

Spendict – a performance marketer's verdict for AI agents, over MCP

@AIWMCX1 · X

Consultants don’t need more noise. AIWMC Quantis helps turn messy business ideas into clear scenarios, runway views, and risk signals — so you can spend less time rebuilding analysis and more time giving the client a real answer.

Dgeloe4-yb · GitHub

market-pilot Evidence-grounded market research prototype with traceable AI workflows.

anuj_sachan1 · Product Hunt

DueDocs AI property contract review for Australian buyers and pros.

@raeezatameez · X

dropping mine - would love your take!

u/maybeImakemoney · Reddit

I built the thing. Now I am not sure the base use case is one people will pay for. Founder here. This started as a side learning project to see whether an LLM could answer questions about Excel data, back when they could not do it well. I built the first version on n8n, with workflows that ingested files, generated metadata with an LLM, and answered questions against the converted data plus that metadata. Then I started using it for my own analysis and report generation, saw that the time sav

u/zx9rams · Reddit

I built a Bible tool designed so the AI can't just make things up. I've been building this for a while and the part I actually care about is the architecture, because an AI that reads the Bible is exactly the thing nobody should trust by default. So its built the opposite way, the model is treated as untrusted and the code owns every real decision. every quote is checked word for word against the Hebrew and Greek before it shows, so the model cant paraphrase scripture into an answer eve

@AMaxim62228 · X

Check out what I just built with Lovable!