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Alternatives

Products that do what AI Generated Shark Tank does

I've been working on a platform that uses LLMs to turn any random idea into 2-3 minute episodes - one of the newer ones is JARS Tank, where you can pitch inventions to a panel of AI investors. Would love to hear your thoughts!

  1. 1

    Shark Tank for Product Hunt. Get advice from real investors.

    2015

  2. 2

    Pitch Your Idea To The Sharks And Maybe Get a Deal 🦈

    2023

  3. 3
    Pitchdeck151

    Snapchat meets Shark Tank

    2015

  4. 4

    Your million dollar product idea is...

    2019

  5. 5IP

    To be specific, the content is generated by a GPT-2 based model. https://amzn.to/2TCc0v2 Let me know if you have any questions :-)

    2020

  6. 6LG

    Hi there, I've decided to jump on the AI train and put something together with low effort & high reward, to see if it can get any traction. What do you think? Is it a promising area? Do you guys have ideas for me? There is obviously going to be sea of LLM generated content out there and one project adding up to it might not necessarily be what world needs. In the same time there is something intriguing about the area. Well, please play with it and let me know what y'all think. Much appreciated.

    2023 · canonica.ai

  7. 7RA

    Hey HN, I'm a founder at Ovlo a supply chain company.I had a problem. After every batch of customer interviews/research/feedback sessions, I'd run ideas through an LLM to help me decide what we should build next. Except it was obvious to my cofounder I wasn't really validating anything. LLMs are incredibly good at agreeing with you in subtle ways, especially when you feed them context that already reflects your thoughts. I'd ask "Does this make sense?" and get a beautifully worded essay about why yes, obviously, this is the best thing ever. I was using AI as an echo chamber without…

    Dec 2025 · roundtable.ovlo.ai

  8. 8IE

    Hi HN! I spent the last year traveling and feeling purposeless after shutting down my last startup (Zage YC S’21) in Dec 2022. There were some obstacles I couldn’t overcome and decided to return investors 50% of their capital. To afford (and justify to myself) traveling, I started consulting as an engineer and product designer. I started (https://backspace.nyc) and it was a good time. I (and some friends) built a handful of AI experiences and learned a lot along the way. The hardest thing about running a services business shipping and selling AI experiences powered by LLMs was…

    2024 · loom.com

  9. 9AT

    I have a favour to ask. I’ve been working for a while on Kalavai, a project to make distributed AI easy. There are brilliant tools out there to help AI hobbyists and devs on the software layer (shout out to vLLM and llamacpp amongst many others!) but it’s a jungle out there when it comes to procuring and managing the necessary hardware resources and orchestrating them. This has always led me to compromise on the size of the models I end up using (quantized versions, smaller models) to save cost or to play within the limits of my rig. Today I am happy to share the first public version of our…

    2024 · github.com

  10. 10OA

    A friend and I are launching an alpha first thing in 2011. We're trying to gain some momentum and whatnot, so we're opening early registration as of tonight. We're planning to develop a Bayesian network to derive suggestions. If you're interested in seeing our progress, check it out. Edit: Any and all suggestions, criticism, advice, etc is highly appreciated!

    2010 · osmoar.com

  11. 11AA

    Hi HN! Last night, I live streamed myself coding this Llama 2 Agent on a Single GPU (Colab). After 6 hours it actually has some good results. How it works is it takes in your intuition (e.g. "I think x would be cool") and develops a business idea (with a name and branding colors) and a business plan. After the business plan is developed, it criticizes this plan recursively until the "Investor" prompt is satisfied with the plan. After all this it will generate the final MVP idea and pass it to a the React Engineer Agent I live coded 2 days ago…

    2023 · github.com

  12. 12MS

    For years, I have struggled to understand my cash flow and save for the future. In addition to that, my wife has many credit cards and accounts that complicate matters. I am building a tool that connects all our accounts, helps us create a budget, and tracks and adjusts expenses on the fly. I am also sprinkling some AI magic on it for financial suggestions. I am looking for feedback on the implementation. More importantly, I am looking for more beta testers to improve the product.

    2023 · financemadelovely.com

  13. 13AA

    Hey folks, I'm Yuval. I run a tiny startup called Glitter AI. It's just me full-time here, with a couple of freelances to help here and there. A couple of months ago, I went from managing zero requests to hundreds -- overnight (won Product of the day on Product Hunt). As someone who gets VERY easily distracted (maybe you relate), I had to find some sort of way of handling all the chaos if I didn't want to burn out. I came up with a pretty cool automation flow that I thought folks on HN here may be interested in reading about :) So here goes: Most of my interactions come through Intercom.…

    2024

  14. 14BS

    Today we are thrilled to announce the release of a public Kalavai pool dedicated to host Petals workers. This is part of our wider effort to offer easy access to compute to AI developers. Do you find this useful? What other tooling would you like to see running on crowdsourced hardware?

    2024 · kalavai-net.github.io

  15. 15IB

    I haven't seen anything like this so I decided to build it in a weekend. How it works: You see a bunch of things pulled from Wikipedia displayed on cards. You ask yes or no questions to figure out which card is the secret article. The AI model has access to the image and wiki text and it's own knowledge to answer your question. Happy to have my credits burned for the day but I'll probably have to make this paid at some point so enjoy. I found it's not easy to get cheap+fast+good responses but the tech is getting there. Most of the prompts are running through Groq infra or hitting a cache…

    Apr 2026 · sleuththetruth.com

  16. 16IO

    Hey folks, I’m the creator of WFGY — a semantic reasoning framework for LLMs. After open-sourcing it, I did a full technical and value audit — and realized this engine might be worth $8M–$17M based on AI module licensing norms. If embedded as part of a platform core, the valuation could exceed $30M. Too late to pull it back. So here it is — fully free, open-sourced under MIT. --- ### What does it solve? Current LLMs (even GPT-4+) lack *self-consistent reasoning*. They struggle with: - Fragmented logic across turns - No internal loopback or self-calibration - No modular thought units - Weak…

    2025 · github.com

  17. 17IB

    Hi HN, I'm the creator of this project. For the past months, I've been working on building an AI agent that could move beyond simple generation and tackle inventive challenges autonomously. The core idea was to create a system with a "metacognitive loop"—the ability to recognize when it's stuck on a fundamental problem and then launch a sub-mission to solve that specific bottleneck before continuing. The linked article is a deeper introduction to the system's architecture and a snapshot from a recent run. I tried to design it to be evidence-grounded and self-critical to avoid the pitfalls of…

    2025 · robw1se.substack.com

  18. 18IC

    For the last few months I have been analysing Peter Lynch’s books on stock picking and doing prompt engineering to check if AI could create useful stock analyses. To my surprise it started making reports that allow me to understand companies much faster with well cited sources. I hope you find it interesting and useful :) Perter Lynch’s books I analyzed: Learn to earn, One up on Wall Street, Beating the street

    Jun 2026 · github.com

  19. 19IM

    So hard to keep up with tooling and MLOps - I put it all in one place and got some tips from an experienced friend on what to use.

    2025 · readyforagents.com

  20. 20NB

    I've spent weeks curating technical implementation details of how companies are actually deploying LLMs and Generative AI in production. The database now contains over 300 case studies with detailed technical summaries (230,000+ words) focusing exclusively on architectural decisions, deployment patterns, and real engineering challenges. Key features: * Each case study is technically focused - no marketing fluff * 150+ entries from technical conference talks and panels (saving you 100+ hours of video watching) * Sophisticated filtering by technical stack, RAG implementations, monitoring…

    2024 · zenml.io

  21. 21PA

    Hey HN! I'm an indie hacker who builds SAAS products in my free time. I've got a friend who runs a small consulting firm and said this would be a useful tool for them so i thought why not release it as a standalone online tool for everyone. Basically the premise is, you enter some information about your services (or we just scrape your website and figure it out). Then you enter a description of the client brief, tweak the outline, and out comes a unique tailored proposal that you can tweak with AI. That's pretty much it! Would love to hear your thoughts. Thank you.

    2023 · pitchpower.ai

  22. 22

    Pitch → Get Grilled → Negotiate → Verdict → Become the Shark

    19d ago · pitchaura.in

  23. 23IS

    Hey HN! For that last 8 months I've been trying to make agents that can hack web applications to find vulnerabilities in them - An AI Security Tester. The system has 29 agents in total, a custom LLM Orchestration framework which works on the task-subtask architecture (old-school but works amazingly for my use case, and is pretty reliable) with custom agent calling mechanism. No Auo-Gen, Langchain and Crew AI - Everything custom built for pentesting. Each test runs in an isolated Kali linux environment (on AWS Fargate), where the agents have full access to the environment to undertake any…

    2025

  24. 24IR

    Democratisation of local AI is key. I've been working on pushing the limits of commercial hardware, squeezing any extra bit possible. My Scientific Agentic AI hareness helped me to reallocate every single bit of it. I rewrote the Kernel, I went down the CUDA rabbit hole until I have been able to explain any bit and any ms of computational power involved in the process pushing the Qwen 30B-A3B from 8 tok7s to 19 tok/s with llama.cpp up to 22.2 tok/s with my project and 109 tok/s on not novel content and speeding up the prefill by 5-9X

    Jul 2026 · github.com

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