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Finic – Open source platform for building browser automations

Hacker News

Finic – Open source platform for building browser automations

Last year we launched a project called Psychic that did moderately well on hacker news, but was a commercial failure. We were able to find customers, but none with compelling and overlapping use cases. Everyone who was interested was too early to be a real customer. This was our launch: https://news.ycombinator.com/item?id=36032081 We recently decided to revive and rebrand the project after seeing a sudden spike in interest from people who wanted to connect LLMs to data - but specifically through browsers. It's also a problem we've experienced firsthand, having built scraping features into Psychic and previously working on bot detection at Robinhood. If you haven’t built a web scraper or browser automation before, you might assume it’s very straightforward. People have been building scrapers for as long as the internet has existed, so there must be many tools for the job. The truth is that web scraping strategies need to constantly adapt as web standard change, and as companies that don’t want to be scraped adopt new technologies to try and block it. The old standards never completely go away, so the longer the internet exists, the more edge cases you’ll need to account for. This adds up to a LOT of infrastructure that needs to be set up and a lot of schlep developers have to go through to get up and running. Scraping is no easier today than it was 10 years ago - the problems are just different. Finic is an open source platform for building and deploying browser agents. Browser agents are bots deployed to the cloud that mimic the behaviour of humans, like web scrapers or remote process automation (RPA) jobs. Simple examples include scripts that scrape static websites like the SEC's EDGAR database. More complex use cases include integrating with legacy applications that don’t have public APIs, where the best way to automate data entry is to just manipulate HTML selectors (EHRs for example). Our goal is to make Finic the easiest way to deploy a Playwright-based browser automation. With this launch, you can already do so in just 4 steps. Check out our docs for more info: https://docs.finic.io/quickstart

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
95%95% 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.
Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, hacker news · Missing: https docs, excited, just released
89%89% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, new · Missing: mac, macos, cursor
81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% 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
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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