We re building an AI-first way to search and discover flights focused on simplifying decisions, not overwhelming you with options.

But here s the truth: This is still early.

I m building PartFinder a tool that helps manufacturers spot risky parts in their supply chain before they become a problem.

You can upload a BOM or parts list, and PartFinder looks at things like lead-time changes, supplier concentration, geography exposure, disruption events, and replacement difficulty. The goal is to show which parts are exposed, why they re risky, and what actions teams can take next like finding alternates, checking suppliers, or starting RFQs.

We re mainly focused on mid-market manufacturers that don t have huge procurement/risk teams and are often stuck using spreadsheets, supplier portals, ERP data, and tribal knowledge.

Would love feedback from anyone in manufacturing, procurement, hardware, or supply chain. Is this something your team deals with, or do you already manage this well enough manually?

Hey Product Hunt! I'm Awadeen, a tech entrepreneur from Egypt.

Most people with a business idea hit the same wall: they don't know how to model it, validate it, or figure out if it'll actually work. Not because they're not smart. Because business strategy has always been locked behind expensive consultants, exclusive incubators, and MBA programs most of us never attended.

So I built InnoCanvas. Your AI co-founder. (The kind that never asks for equity.)

You describe your idea. It builds your business model, validates your strategy across five dimensions, and connects you with four specialist AI advisors: marketing, finance, legal, and tech. Not a template. Not a chatbot. A thinking partner that knows your idea and helps you stress-test it.

I reviewed a few early-stage startup products recently and noticed the same pattern repeatedly:

users dropping during onboarding
weak conversion funnels
unclear feature priorities
operational friction slowing growth

Most early-stage startups don t fail because their technology is weak.

They struggle because product execution becomes inconsistent while trying to scale with limited resources.

Hey Product Hunt community

I'm Nolan, and today we're officially introducing AI Hive to this community.

What we built: An enterprise AI agent platform that lets you build, deploy, and run AI agents entirely within your own infrastructure no data ever leaves your network.

Why we built it:

Most engineering teams know they should be running agentic workflows. The demos look incredible. The speed is real.

But the first few production attempts often go sideways, not because the AI is bad, but because the governance layer wasn't there.

The AI Velocity Pod Starter Kit is everything we wish existed when we started: a framework distilled from 300+ shipped products, 38-day average delivery cycles, and a lot of painful lessons about what breaks when you give agents too much autonomy too fast.

What's included:
Sprint structure template (intent build QA diff review)
Acceptance criteria writing guide (the #1 bottleneck in agentic workflows)
Parallel QA agent setup run validation concurrently, not sequentially
Governance checklist for regulated industries (HIPAA, GDPR, OWASP-aligned)
Access scope matrix which systems agents should (and shouldn't) touch

I have been a software engineer for 25 years and an engineering manager for 6. I know how to build things. What I could never figure out was how to remember everything I built, reviewed, commented on, or responded to on any given day.

My calendar tracked meetings fine. Everything else just disappeared. PR reviews, Jira comments, ad hoc requests from leadership, performance review prep, one-off conversations that turned into two hours of unplanned architecture discussions. By Friday I could barely reconstruct Tuesday. I eventually started keeping a running Google doc of everything I touched each day, including meetings. It was exactly as tedious as it sounds.

AI has made building products dramatically easier.

A solo founder can now create a landing page, prototype an app, generate designs, write code, and launch faster than ever before.

That is exciting.
But it also changes the game.