Hey Product Hunt Fam

I'm Kaavya, co-founder of Scribble, a creator campaign platform helping brands get visible in AI search.

Been deep in the GEO rabbit hole for a while now, running content campaigns and trying to figure out why good content disappears on ChatGPT and Perplexity. Lots of patterns emerged from watching enough campaigns, which eventually turned into a tool.

Here is something I built after watching too many founders lose deals to buried emails:

www.dailytaskproai.com

It reads your Gmail and Outlook every morning and scores every email 0 to 100 by revenue impact. The most important one is already ranked number 1 before you open anything. Emails above 80 get flagged as Revenue Risk automatically. Your top 5 actions land in a briefing at 7 AM.

The core insight that drove this: your inbox sorts by time received. A 18 lakh client email looks identical to a Swiggy receipt. Same font. Same size. Same position. Your inbox has no idea what matters. It never did.

I decided to become a hunter to give visibility to builders who can't pay for it.

If you think about it, Product Hunt is a platform where you trade time and feedback for visibility and feedback. And that's huuuuge for people who can't buy visibility but can invest their time.

I was in this case when I built Mailwarm (YC S20). Product Hunt helped us validate and find new customers. We went from $3K MRR to $8K MRR during launch week. That's when I understood how big PH can be for founders with no marketing budget.

Recently I started a builder community focused on Moroccans. I understood that building is not a problem anymore. The bottleneck is go-to-market.

After 15 years of building iOS apps for banks, e-commerce, B2C startups, and other industries, I decided to take the leap and build my own apps.

I love being able to work on my own products and seeing them slowly gain traction. It s very rewarding having something yours out there solving some people s problems.

Hey

I m Vivek, founder of @Calnize a smarter and simpler scheduling platform built to reduce calendar chaos and double bookings.

I started Calnize with a simple goal: Make scheduling feel effortless for individuals, startups, and growing teams without the complexity of traditional tools.

Would love to connect with fellow builders, creators, and productivity enthusiasts here

Hi everyone,

I'm Mona a marketer turned builder from Germany.

Hey I'm James, a software developer from Australia with 20+ years building things professionally.

Most of my career I've been the person behind the scenes solving hard technical problems, shipping reliable software, making other people's ideas work. Unravl is the first thing I've built entirely for myself, and now I'm figuring out the part they don't teach developers: how to actually get it in front of people who might find it useful.

No funding. No growth team. No playbook. Just me, the product, and a lot of learning in public.

If you've been down this road builder trying to find an audience I'd genuinely love to hear what worked for you. And if Unravl sounds like something you'd use, even better.

Hi Product Hunt, I'm an eCommerce Operations Analyst working with pricing, inventory, promos, and marketplace reporting.

Most of my day-to-day pain is less about "getting data" and more about trusting it: matching the same product across different marketplaces, catching promo changes before they expire, checking stock movements, and explaining why a real-time report is not useful if half the SKUs are matched wrong.

I'm especially interested in tools that help with:

• competitor price tracking

• SKU and product matching

• marketplace monitoring

• inventory and stock-change alerts

• reporting automation

• spreadsheet-to-dashboard workflows

Hi, I'm a research data engineer working with academic teams on data collection, cleaning, versioning, and reproducible analysis.

A lot of research data work breaks down before the model, chart, or paper ever happens. Sources change, scripts are undocumented, licenses are unclear, and six months later nobody can explain exactly how the dataset was created.

I'm especially interested in open science, dataset provenance, archival workflows, and practical ways to make research easier to rerun without slowing everyone down too much.

Curious how others here handle this: when you publish or share a data project, what do you document first... raw data, collection timestamps, cleaning scripts, licenses, environment files, or something else?