Inkgest, Link to Gest

Hacker News

I built Inkgest over the past few months as a solo developer. The core idea: paste any URL, Inkgest scrapes the content using my own scraping API (not Firecrawl, no third-party, custom scraping API), sends it through an LLM, and generates publish-ready content in whatever format you need — newsletter, blog post, infographic, tables, LinkedIn post, or deep comparison table. A few things I built that I found interesting technically: - Wrote my own scraping backend in Hono.js instead of using a third-party service. Runs as a persistent server, so no cold starts. Handles JS-rendered pages. - The infographic renderer generates real SVG/React components from extracted data — doughnut charts, step flows, stat cards, comparison splits. No image generation APIs, all rendered code. - Built on top of my own SaaS boilerplate (buildsaas.dev), which handles auth, payments, email, and admin out of the box. Launched yesterday. 3 free credits to try everything, $9/month after that. Happy to share the product and discuss in depth about the AI agent, scraping techniques, and building SaaS products. inkgest.com

Visit product View on Hacker NewsFeb 27, 2026

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2points

Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

46%46% 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

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

27%27% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

26%26% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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