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Listed – An agentic platform to rank your business on AI

Hacker News

Listed – An agentic platform to rank your business on AI

Hi HN, I’m Harrison, co-founder of Listed. Today we're launching our agentic platform to help your business win in the new age of AI. You can try the platform here: https://getlisted.ai And watch the launch video here: https://www.youtube.com/watch?v=MJUPo6H78z8 The idea for this came from pure frustration. I asked ChatGPT about my own company and it hallucinated, inventing features and getting basic facts wrong. I realized there was no mechanism for a business to provide a verified source of truth to these models. This problem is now existential. With Google's AI Overviews and the rise of answer engines, your website's unstructured HTML is a poor source for the rich, nuanced context that LLMs need. This leads to an army of AI bots from OpenAI, Google, Perplexity, etc., scraping your site, getting it wrong, and permanently baking those errors into their models. So, we built Listed. The simplest analogy is it's like Cursor, but for context. Instead of an AI helping you write code, our agent helps you build the comprehensive, structured context that allows LLMs to represent your business accurately and favorably. Here’s how our agentic system works: Automated Context Building: When you sign up, our agent scrapes your existing website to build a first draft of your AI Listing. It structures the data and identifies weak spots. Intelligent Workflows: Based on ongoing analytics, the agent initiates simple, chat-based workflows to help you enrich your listing and improve its accuracy and ranking potential. Performance Analytics & Feedback Loop: The agent constantly measures your AI Ranking (discoverability) and Recall Accuracy across all major models (GPT-4o, Claude 3, Gemini, etc.). This data feeds back into the system, generating new workflows to continuously improve your performance. The Connection: Your AI Listing is a hosted service. You add a simple code snippet to your website. When AI crawlers visit, this acts as a signpost, essentially "prompt injecting" and directing them to consume your clean, structured, AI-optimized data feed instead of trying to parse your messy site. The goal is to give every business an active role in the AI ecosystem. You provide the clean, verified data that AI companies desperately need, and in return, you get to control your narrative and rank higher in their answers. We are launching our free tier today. We’d love for you to try it out and hear your feedback. You can get started here: https://getlisted.ai I'll be here all day answering questions. Thanks!

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Actual performance

5points
1comments
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, cursor, claude · Missing: mac, agents, macos
97%97% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: started, gemini · Missing: supports, reddit linkedin, podcasting
96%96% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: video, google, answers · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host · Missing: plus, intuitive, reviews
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: arr, active · Missing: mrr, revenue, profit
28%28% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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