Fin.flights 2.0 – AI-powered flight search

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fin.flights is an AI-powered flight search tool that uses natural language processing to find the best flights based on user queries. just released version 2.0 with significant improvements: - No login required: Start searching immediately without creating an account - Advanced AI: Utilizing latest LLMs for more accurate flight results - Natural language interface: Type queries as you would ask a friend - Global coverage: Searches flights worldwide with multi-language support - Free to use: Only upgrade if you find it valuable How it works: 1. Enter a natural language query (e.g., "cheapest business class flights from NYC to Tokyo in the next 3 months with max 1 stopover") 2. Our AI interprets the query and searches across multiple airlines and booking platforms 3. Results are displayed instantly, sortable by price, duration, or best value I built this because existing flight search engines often require too many inputs and don't offer the flexibility of natural language queries. Myy goal is to make flight search as simple as asking a knowledgeable friend. I'd love to get feedback from the HN community on the user experience, AI accuracy, and any features you'd like to see added.

Visit product View on Hacker NewsSep 29, 2024

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

84%84% 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: user · Missing: mac, agents, macos

80%80% 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: just released, exist, lua · Missing: https docs, excited, open source

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

14%14% 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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