What are you building? Drop your AI product below
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Doing one of these because I get more from reading what others are building than from any newsletter.
I'll start.
Building AI Hive, an enterprise AI agent platform that helps mid-market and enterprise teams get from AI pilot to production in weeks instead of quarters. The hard problem we keep solving: compliance, model flexibility, and the lack of in-house AI talent on the customer side.
Product Hunt page: https://www.producthunt.com/products/ai-hive
Your turn. Drop:
- What you're building
- Who it's for
- The hardest part you're solving right now
Will read everything and upvote what resonates.
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Replies
Building MartinLoop.
It’s for founders, developers, and teams running AI coding agents like Claude Code, Codex, Cursor, OpenCode, or custom agents in real repos.
The hard problem we’re solving: AI agents can write code, but they still run wild. They loop, waste tokens, change files, wait for approval, and leave teams guessing what happened.
MartinLoop adds the missing control layer: budgets, safety checks, verifier gates, rollback, notifications, and run receipts so every agent run is easier to trust.
Product Hunt: https://www.producthunt.com/products/martinloop
Website: https://martinloop.com
appreciate any upvotes and Stars on github, (download the open source and if its useful first ofc)
@keesan12 congrat on your launching mate. I have followed and upvoted your product. Hope that you can stil upgrade the product and earn more clients and followers later on
If possible can you do the same, upvote or give some review for AI Hive also, thank you very much in advance
https://www.producthunt.com/products/ai-hive/
What you're building
ReadyToPlay24 is a team management app that replaces the WhatsApp group chaos for sports organizers. The captain creates a group, adds a match — the app automatically sends push notifications to all players and manages the waitlist. When someone drops out, the first person on the waitlist gets a push notification and jumps in automatically. No more manual counting, no more "who replied?", no group chat scrolling. Available as a PWA (web + iOS) and native Android app, in 8 languages.
Who it's for
Three main users:
- Casual group organizers — someone who runs a weekly 5-a-side game with friends and is tired of managing it all through a chat group
- Coaches — running training sessions for 2–3 groups, needing attendance tracking and PDF reports per session
- Amateur league organizers — managing 10+ teams, needing rotation logic, stats, and season reports for sponsors
Players (non-captains) join for free — only the organizer pays. That's a key part of the model.
The hardest part you're solving right now
Getting organizers to make the switch. The product solves a real pain, but people are deeply habitual about WhatsApp groups — it's "good enough" even when it clearly isn't. The friction isn't the app, it's the moment you have to convince 12 people to install something new.
What's working: a 14-day free trial (no card required) for both Pro and Max plans, and the fact that players don't need to pay — that removes the biggest objection. But distribution is still the core challenge.
@jaroslaw_prazmo thanks for dropping this, Jarosław!
the "convince 12 people to install something new" problem is genuinely the hardest part of any group coordination tool, and you've already identified the right answer: don't make the players pay or install anything heavy. the captain bears the friction so nobody else has to. that asymmetry is what makes group adoption actually possible. distribution is still the grind, but the model is solid.
What you're building
TAM Network. the alternative to LinkedIn for everyone who builds and serves. coders, plumbers, nurses, designers. instead of titles and endorsements you publish receipts of work that customers and peers countersign. recruiters filter by 'who actually did this' instead of 'who has been at the company longest.'
Who it's for
the 92 percent of workers who do not write code, and the recruiters who need to verify them. solo founders and trades who have no portable credential they can carry between jobs.
The hardest part I'm solving right now
day-one cold-start for non-coders. an empty profile feels worse than no profile. early answer: a 'receipt builder' that turns one customer text message into a signed entry in under 30 seconds.
aug 12 launch. site: thetamnetwork.com
@thenameisarian appreciate you sharing this, Mustafa, we've talked about the credential layer before and it keeps coming up for good reason.
the cold-start problem for non-coders is the right thing to be obsessing over right now. an empty profile that mirrors LinkedIn feels like a step backward, so the receipt builder converting a customer text into a signed entry in under 30 seconds is exactly the kind of wedge that makes the first session feel worth it. looking forward to the Aug 12 launch.
What we're building
Nuvela AI is an AI-powered healthcare companion built by a registered nurse. It transforms complex medical documents into plain-English care guides with personalized explanations, medication insights, red flags, and questions to ask your provider, helping patients feel informed and confident, not overwhelmed.
Who it's for
Anyone trying to understand their healthcare: from patients and caregivers to parents and older adults. If you've ever left a doctor's office with paperwork you couldn't make sense of, Nuvela AI is for you.
The hardest problem we're solving
Making complex medical information both accurate and genuinely understandable while maintaining strict privacy and security. We're building an experience that feels less like using AI and more like having a knowledgeable nurse explain everything in a calm, human way.
🎉 Product Hunt Exclusive: Get 30% off the Basic Plan forever when you sign up through our Product Hunt launch.
Product Hunt Page: https://www.producthunt.com/products/nuvela-ai?utm_source=other&utm_medium=social
@nuvela thanks for sharing this, Samantha, really well framed.
the "built by a registered nurse" angle is probably your strongest trust signal and i hope it's front and center in your marketing. the accuracy + understandability tension you described is the exact thing most health AI tools get wrong, they optimize for one and tank the other. the fact that you're holding both at the same time is hard and worth talking about more openly.
@nolan_vu Thank you, I really appreciate that. That was exactly my goal from day one.
I never wanted Nuvela to just summarize documents. I wanted it to explain them in a way that's accurate, approachable, and genuinely useful without creating unnecessary fear or false reassurance.
That's a difficult balance, and it's something I think healthcare AI has to get right. Thanks for recognizing that, it means a lot coming from someone who picked up on that nuance.
@nuvela Thanks for coming back to this. The "accurate AND approachable without false reassurance" constraint is genuinely hard to hold, and most tools quietly drop one side of it to make the UX cleaner.
The fact that it came from a nurse background shows. That clinical instinct for what patients actually need to understand vs what just sounds thorough is not something you can prompt-engineer your way to.
What I'm building:
Cloudnan, a server management platform you operate by chatting with it. Connect your own VPS (server) or buy one in-app, then deploy from GitHub or a container registry (WordPress, Laravel, Node, whatever your stack is), run databases, and manage domains, monitoring, backups, and security. The AI does the actual server work, you just say what you want in plain language.
Who it's for:
Non-technical business owners, and the freelancers and small agencies who keep getting WhatsApp'd to fix their clients' servers. I was that freelancer. The goal is that the owner stops having to hire someone every time something breaks on their server.
The hardest part I'm solving right now:
Reliability and trust. It's easy to make an AI that talks about servers. It's hard to make one a non-technical person can trust to actually run one, diagnose why a site went down during a peak season (like flash sale), resize it, restart what crashed, without a human checking its work. Getting to "works on the first try, every time" for someone who can't tell when it's wrong is the real problem.
Product Hunt: haven't posted yet, launching officially tomorrow (wish me luck!)
Site: https://cloudnan.com
@budhilaw thanks for dropping this, Ericsson, good luck with your upcoming launch
the "works on the first try, every time" bar is genuinely hard to hit, especially for non-technical users who have no way to verify if something went wrong silently. the trust problem you described is real, and i think the flash sale / peak traffic scenario is exactly the scenario that will define whether people stick with it or not. would love to see how you handle confidence scoring when the AI makes a call that could go either way.
Hey Product Hunt community! 👋
I’m Rutvik, the founder behind PixelDrive. We just officially hit the launch stage today! 🚀
The motivation behind building PixelDrive came from a massive headache I faced constantly as a developer: the traditional pricing and architectural model of image generation APIs. Most platforms track every layout tweak, visual preview, or identical repeat asset request as a premium billable event. If you need to hotlink dynamic renders inside mass email campaigns or use them for high-traffic open-graph (`og:image`) tags, the costs run wild.
We wanted to change the paradigm by treating image generation like a modern, programmatic printing press built explicitly for developers and the AI era.
We approached the engineering with a few core principles:
1. The LLM should be the designer: We built a hosted 26-tool Model Context Protocol (MCP) server natively into the engine. This lets AI agents (like Claude or Cursor) programmatically spin up templates, read existing element layers, and nudge coordinate values to fix text overflows autonomously.
2. Identical requests should be free: If your API parameters match an asset already rendered, it pulls instantly from our global edge cache in 19ms at exactly 0 credit cost. Go ahead and hotlink it.
3. No translation glue-code: You can localize graphics on the fly across 70+ languages just by appending a simple `?lang=` parameter to your request.
We are hanging out on our launch page all day giving away 1,000 free credits to anyone who wants to play around with the engine and test the API.
👉 Check out our live launch page here: [Insert Your Product Hunt Launch Link]
I would love to hear from fellow builders, SaaS founders, and AI engineers:
* What does your current image automation pipeline look like?
* Are you running custom headless browser setups, or have you integrated MCP tools into your asset workflows yet?
Let's chat in the comments! 🛠️
@therutvikpanchal The identical-request caching at 0 credit cost is the feature that actually changes the math for high-volume use cases. That's not a nice-to-have, it's what makes it viable for mass email and og:image at scale.
The MCP integration is interesting timing. AI agents generating and iterating on visual assets without a human in the loop is where image generation gets genuinely useful for production workflows.
@nolan_vu Exactly. We wanted pricing to align with real production workloads, not punish repeat renders. If you're generating the same asset thousands of times, paying for every identical request doesn't make much sense.
And that's also why we built the MCP server. The goal isn't just AI creating images it's AI being able to generate, iterate, and deploy production-ready visual assets as part of a larger workflow, with PixelDrive handling the rendering layer in the background.
I am Building creatrne - the platform where creators actually run their business. Pitches, deals, contracts, income, media kit, all in one place.
This for UGC and influencer creators who are tired of managing brand deals through DMs and gut feel.
The hardest part is creators make real money but they're financially invisible. No verified deal history, no income proof, nothing that counts outside their own bank account. That's what I'm fixing.
@priyatharshini_c The "financially invisible" framing is sharp. That's the exact gap. Creators have real revenue but no verifiable paper trail, which makes them look risky to brands even when they're not.
Verified deal history could become a proper trust layer for the whole creator economy if you get the data model right. Is the income verification tied to the platform or does it pull from external sources too?
I’m building WorkZo AI - an AI career platform that helps job seekers prepare for every stage of the hiring process, not just the interview.
It combines AI mock interviews with different recruiter personas, resume & ATS optimization, cover letter generation, job-specific preparation, instant feedback, and career guidance in one place.
It’s built for students, graduates, career changers, and professionals who want to increase their chances of landing interviews and offers.
The hardest challenge I’m solving right now isn’t building AI - it’s creating a product people keep coming back to throughout their job search, while making the experience feel genuinely personalized instead of another generic AI chatbot.
https://www.producthunt.com/products/workzo-ai?launch=workzo-ai-2
Always happy to connect with fellow builders. 🚀
@harithavijayakumar The retention problem is the honest hard part and I respect that you named it directly. Most job search tools get used once for a resume, then abandoned. Keeping people coming back across the whole hiring cycle, not just interview prep, is a fundamentally different product challenge.
What's your current thinking on the "return trigger"? Is it stage-based, time-based, or something the user sets?
Building BloodAI.
What you're building
It's an AI platform that helps people understand blood test reports in plain English by extracting biomarkers, highlighting abnormal patterns, and generating educational insights.
Who it's for
Right now it's built for patients, with the long-term vision of helping clinicians and hospitals through AI-assisted report interpretation.
The hardest part you're solving right now
The hardest problem we're solving is making AI outputs clinically useful, consistent, and trustworthy while staying educational rather than diagnostic.
Would love your feedback!
Product Hunt: https://www.producthunt.com/products/bloodai
@raghav_rajput1 The educational vs diagnostic line is exactly the right place to hold firm. The moment a health AI starts feeling like a diagnosis, trust collapses fast, either from users over-relying or regulators getting involved.
The consistency problem is hard though. Same biomarker, different context, different explanation. How are you handling that?
What I'm building
TradeDesk- A contractor business app that runs from your phone. Estimates, invoices, getting paid, job tracking, reciept scanning, and more. An entire business in your pocket, simple enough to use on a job site with dirty hands, not at a desk.
Who's it for
Tradespeople and contractors- especially for small crews and the ones who fly solo. I wanted to build the tool I'd want to have if I were the one swinging the hammer.
Hardest part to solve right now
Keeping it simple. The idea is to "flow like a river"- you never get lost or need a manual. Protecting the simplicity while still being powerful is the constant battle. (I'm also a solo builder)
@brittney_boatwright "Flow like a river" is a great internal design constraint for this audience. Tradespeople don't have patience for apps that make them think, they need it to just work, one hand, job site conditions.
The solo builder fighting feature creep to protect simplicity is a real tension. How are you deciding what stays out?
@nolan_vu The goal is for TradeDesk to be a a tool that makes everyday easier; not software that needs to be learned. If a feature adds friction, it waits.
And thank you for the reply.🖤
@brittney_boatwright Thanks for closing the loop on that, means a lot you took the time to explain the logic behind it.
"If a feature adds friction, it waits" is honestly a better filter than most roadmap frameworks I've seen at way bigger companies. Easy to say "no" to a feature on a slide, way harder when it's a real request from a real tradesperson asking for it. Curious if you've had to say no to something you personally wanted to build, that's usually where the discipline actually gets tested.