HiFiles AI – Innovative document assistant and files chat

Hacker News

Hello HN readers! I’m Rares Pascut, and on behalf of the Typing AI Biometrics team, I’m excited to share a side project of ours: HiFiles AI. What is HiFiles AI? HiFiles AI lets you chat with your files—upload documents, ask questions, and get precise answers without manually searching through pages. What makes HiFiles AI stand out? Multiple Files, One Chat – Upload PDFs, Word docs, spreadsheets, presentations, and more. Cross-reference data across documents. Smart Search – Choose between Vector Search for similarity-based queries or Semantic Search for context-aware results. Dual AI Modes – Get strict file-based responses for accuracy or general AI knowledge for broader insights. Embeddable Chatbot – Integrate the AI assistant into your website or app. Privacy First – All interactions are encrypted and follow strict security protocols. Who is HiFiles AI for? Students – Simplify research and get personalized learning insights. Professionals – Boost productivity by interacting directly with work documents. Analysts – Extract and analyze complex data efficiently. Curious Minds – Dive deeper into materials interactively. Businesses – Optimize document management, automate workflows, and enhance decision-making. Pricing Free Plan available. Paid plans start at €9.99/month, with yearly discounts. Full details: https://hifiles.com/pricing How to Get Started? Sign up at https://hifiles.com and see how it transforms document interactions. We’d love to hear your thoughts, answer questions, and get feedback! Let’s chat smarter. With respect, Rares Pascut --- Disclaimer: HiFiles AI is a side project of Typing AI Biometrics ( https://typing.ai ).

Visit product View on Hacker NewsJan 31, 2025

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

89%89% 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: context, presentations · Missing: mac, agents, macos

71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, month, answers · Missing: mobile apps, ios, entrepreneurs

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

28%28% 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: active · Missing: arr, mrr, revenue

10%10% 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, paid, smart · 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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