I'm building ClewSupport, a privacy-first AI ticketing system designed specifically for MSPs (Managed Service Providers).
Security and data privacy are huge concerns when integrating AI into IT support workflows. We want to solve this by ensuring client data remains completely secure and siloed, without sacrificing the speed and automation that AI brings to ticket resolution.
I d love to get your thoughts, feedback, or any questions you might have about our approach! What are your main challenges with AI data privacy right now?
Hi, I am Ibrahim a food delivery driver in Seattle, and solo founder. I built KipFire an iPhone app, four people who scared of the camera or have no content ideas. You pick a prompt card. ( funny. Question. Challenge.) and react to it on camera. Building, it was hard. But now I ve hit new wall. Marketing. I don t have marketing skills. I don t know many people who could try it, and tell me what s wrong.
I m Subhash, the maker of Chorus. Chorus All AI, One Place is now live on Product Hunt today, October 20:
https://www.producthunt.com/prod...
Chorus is an Android workspace for people who use several AI providers. Connect your own supported provider API keys, compare replies to the same prompt, and keep related chats, notes and saved prompts organized in Projects.
A small first task: after account verification and provider setup, select two available models in Compare and ask for a three-step spreadsheet-learning plan with an exercise per step. Check which answer gives you steps you can actually follow; agreement is not proof of accuracy. Copy useful comparison output before leaving the screen, since its result columns are not saved.
I'm currently working on a referral program for my hosting startup, and I'm trying to figure out how to make it worthwhile for both creators and the business.
Here's the model I'm considering:
Creators get a free server for one month to test the product before recommending it.
Each creator gets a personal promo code. When someone makes a purchase using that code, the creator earns 10% of the purchase amount as hosting credits.
Vision Transformers waste 90% of their compute recalculating stationary asphalt. NeuroFlow tracks semantic surprise in embedding space, physically eliminating background tokens before the encoder.
Result: 55.8x wall-clock speedup for ViTs on high-res video (1792p) with 97% fidelity. No fine-tuning required.
NeuroFlow is a dynamic routing framework for Vision Transformer video inference. It exploits temporal redundancy by tracking per-patch embedding-distance threshold via an Exponential Moving Average (EMA) of patch-level embeddings, effectively answering the architectural mismatch between O(N2) self-attention and highly redundant natural video streams.
With the growth of AI, .md files are being generated heavily. I have developed a low cost app to help view and even edit(paid version).
Other similar tools might have a subscription etc. but im making it a one time payment and use forever. Inviting beta testers to give me feedback on Testflight. https://testflight.apple.com/joi...
I m James Gallup, a college student and the founder of T4 Forge in Casper, Wyoming.
I built T4 because I could study for hours and still not clearly know what I was actually weak on or what I should study next. It uses a learner s own approved study material to create source-grounded adaptive practice, identify weak areas, focus review, and reassess whether improvement was demonstrated.
A distinction I care about: coaching does not automatically count as mastery. After getting help, the learner must later demonstrate improvement independently.
The core platform is built and entering open beta. Our live Kickstarter is funding and recruiting the founding learner cohort. I m keeping the main Product Hunt launch for when open beta is accessible.
