This JSON Blob returns '402 Payment Required'

Hacker News

Hey Hacker News, I’m proud to share my project, HighContext.ai, which lets developers charge pay-per-view access to their JSON data using the Bitcoin Lightning network. Here’s an example JSON blob: https://api.highcontext.ai/v1/blobs/Tg6tS6PhRufCLy7gbkl3E/r/2KsYLoAEdh4ImJUWjzHEQA/payme Why use HighContext to charge for your data? Today, millions of developers are building new AI models and agents that are eager to incorporate incremental training data in order to produce more accurate and reliable results. You can now let those developers—and their AI agents—quickly and easily transact with you using Lightning micropayments. Added benefits such as no chargeback risk, flexible pricing per API call, and an open payment system mean you’ll be exposing yourself to more potential customers and earning higher margin over time. Interested to give it a try? Visit https://highcontext.ai and upload your first JSON blob. Let me know what you think! John

Visit product View on Hacker NewsDec 15, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, model · Missing: mac, macos, cursor

87%87% 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 · Missing: supports, reddit linkedin, podcasting

85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: hacker news, io · Missing: https docs, excited, just released

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

20%20% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: margin, training · Missing: arr, mrr, revenue

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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