I built a way to keep the reels you save, even after the creator deletes them
Hi everyone, I'm the developer of LifeFeed AI.
My Instagram Saved folder had hundreds of recipe and travel reels. When I finally went back to cook one, it said "This video is no longer available". So I built LifeFeed around one idea: what you save should stay yours.
Keep the video: share a reel, TikTok or YouTube video to LifeFeed, then tap Save offline (on your phone) or Save to cloud. It keeps playing even after the original post is deleted.
AI reads the video: what's said in it becomes text you can search.
Key details: ingredients with amounts, prices, promo codes, places and dates, pulled out of the video.
Ask Savvy: "How much garlic goes in that pasta reel?" and it answers from your saves.
It works on iPhone, Mac, Android and the web, in 12 languages. Free to start; saving videos and video text are part of Pro.
Grey: a way to browse focused
Hello everybody,
I've constantly had to deal with distracting colors, ads, and videos popping up. Often, when I was searching for how to fix something, colors would flash, my dopamine would spike, and I would get distracted.
Recently, I've built the extension called grey. Basically, it grayscales all of your tabs and everything that you are looking at. I also added a feature that lets you set custom safe items, which show the color for a selected picture even if you reload or leave the page. The extension also lets you set a break timer and, more generally, make a website stay ignored. The extension includes time tracking, reporting how often it greys out each website, plus additional power tools in its settings.
Aurgus
Hey Product Hunt!
I m Mono, founder of Aurgus.
I ve spent much of my career working in enterprise Order-to-Cash (OTC), revenue management, and financial systems. I ve seen firsthand how companies struggle to manage complex financial agreements using traditional enterprise platforms like Vistex.
The reality is that implementing these systems can take 9+ months, cost millions, and involve layers of configuration. Meanwhile, many mid-sized businesses are left managing rebates, commissions, chargebacks, and other financial agreements through spreadsheets.
I am building a contributor community around an open source banking gate, not an audience
Hi everyone, I am Rohan B. a third year Computer Engineering student from Pune, India. I build BankShield HumanGate, an open source gate that asks for passkey proof and device proof before money can move in a banking app. It is scheduled launched on Product Hunt, but this post is not about the launch. It is about the people I hope will build this with me.
The honest reason is simple. I am one student maintaining a security project, and attackers share tooling and techniques with each other every day. A gate designed by one mind carries the blind spots of that one mind. This project only becomes serious if other builders attack it, question it, and improve it in the open.
Real contribution here looks like this. You can propose a new attack case, especially a money movement scenario, and if it is accepted it joins the shared test set that every implementation must handle. You can port the gate to a new language, because the specification is written down and the Python, Go, and Rust implementations already prove themselves against the same 3000 shared cases. You can do hard review, read the gate logic, open an issue, and argue with the design, because a found weakness is a real contribution. And you can make the specification and the docs clearer for the next person who arrives.
Joining works plainly. Start with the contributor interest issue in the repository and introduce yourself with links to work you have already shipped. I read every profile personally, because this is banking security and trust matters, and then I share a short contributor form before deeper work begins. What counts here is finished work: a merged attack case, a passing port, a review that changes the design.
What should an AI rough cut hand back to the editor?
I m working on CutNow, an editing tool for creators who already have the source footage. We re testing a simple handoff: make an editable first cut from hour-long material, then open it in Jianying Pro to adjust shots, narration and captions.
The test I care about is what happens when a reviewer wants two seconds back. Can the next editor find the source shot, extend it, check the next voice-over line and re-export only what they changed? If you regularly cut recaps or narrative clips, what would you want preserved in that handoff before you trusted an automated first cut?

Ceptize Daily — The Software Opportunity Signals
==>| Ceptize Daily #33 (2026.10.08) |<==
On 08 Oct 2026, I collect 943 products which are launched on Product Hunt on 07 Oct 2026. I picked out 25 random products having clean & full description. I rejected 18 products, remaining 7 products. I extract 118 potential features, rejected 114 features, remaining 4 features which become software opportunities passing uniqueness test. Finally, I picked out 4 software opportunities having high commercial attractive.
Build an audience first, or launch and grow later?
Hiring in healthcare? A CV won't tell you who can actually do the job
Hi, I'm Gregory, the maker of StormInterview, and we just launched on Product Hunt.
In healthcare a CV tells you someone is "experienced", but not whether they can talk you through a clinical audit or calm a worried patient at 3am. Most applicants never get the chance to show that, because only the few who look good on paper are invited for a conversation.
Launching Monday (July 27) — would love tagline feedback
Launching Monday 7/27 NTS, a workspace for solo operators (tasks, clients, invoices) with one unusual mechanic: finished work builds visible momentum. Current tagline: "The solo-operator workspace that turns work into momentum." Two alternates I keep circling: "Tasks, clients & invoices that build momentum as you work" / "Turn your real work into momentum." Does the first one earn its 57 characters, or is there a sharper cut? Happy to return the favor on yours.
It's live if you want to poke around
We Built a Bot Detection Engine Because Our Own Marketing Data Was Bad
So here's what happened. We were running campaigns, watching our click metrics climb, feeling pretty good about performance. Then we started digging into where those clicks actually came from.
Half of them were bots.
Not simple ones either. Headless browsers mimicking human behavior perfectly. Selenium scripts automating clicks at scale. Click farms using mobile devices. Advanced stuff rotating IPs, spoofing geolocation, faking mouse movements, generating realistic referrer patterns. Fingerprinting evasion. Timing tricks. Some were so good they looked completely human.
We realized most link tools just count clicks. They don't ask if those clicks are real.