Lumina
Alternatives
70,552 PH launches analyzed!
Problem
Linux users rely on exact keyword searches for local documents, which fails to find files based on meaning and limits discovery accuracy.
Solution
A Linux application enabling semantic document searches on your local machine. Users can search files by contextual meaning offline, e.g., finding 'budget reports from 2023' without exact keywords.
Customers
Developers, system administrators, and privacy-conscious professionals working extensively with Linux-based systems.
Alternatives
Unique Features
Offline semantic search, privacy-first design (no data upload), AppImage compatibility, and context-aware file retrieval.
User Comments
Eliminates dependency on exact keywords
Works seamlessly offline
Respects data privacy
Faster than traditional grep searches
Easy AppImage installation
Traction
Newly launched on ProductHunt (exact metrics unspecified)
Market Size
The global enterprise search market, which includes semantic document tools, is valued at $4.5 billion (Grand View Research, 2023).
Google Search By Local
Initiate a Google search using a specific local information
61
Problem
Users need to view Google search results from specific geographical locations and languages, but Google's default settings limit search results to the user's current location and language.
Solution
A Chrome extension that allows users to initiate a Google search based on a specific local information. With this tool, users can view search results from around the world in various languages and cities, making it especially useful for global online marketing.
Customers
Global marketers, SEO specialists, researchers, and anyone needing to access search results from specific locations and languages for analysis or strategy development.
Alternatives
View all Google Search By Local alternatives →
Unique Features
The ability to specify the geographical location and language for Google searches directly from a Chrome extension, offering tailored search results for precise marketing and research needs.
User Comments
Saves time by providing localized search results without needing to use VPNs.
Essential for SEO professionals targeting specific markets.
Improves global marketing efforts with better insights into local search trends.
User-friendly interface makes it easy to switch between different locations and languages.
Enhances research accuracy by accessing localized information directly.
Traction
As of the latest data available, specific traction numbers such as user counts or revenue are not provided. However, the product has received positive attention on Product Hunt, indicating a growing interest.
Market Size
The global SEO services market size was valued at $47.5 billion in 2022 and is expected to grow, showcasing the potential market for products facilitating tailored search and marketing strategies.
GitHub Stars Semantic Search
Find your GitHub stars easily with natural language search
5
Problem
Users struggle to efficiently search and find specific GitHub projects among their starred repositories
Solution
A web tool that enables users to perform natural language searches on their starred repositories on GitHub, leveraging OpenAI's embeddings and PGlite for local storage
Transforms how users interact with their starred repositories on GitHub by providing a natural language search functionality to easily locate bookmarked projects
Customers
Developers, programmers, and GitHub users who frequently star repositories and struggle to manage and find specific projects efficiently
Unique Features
Utilizes OpenAI's embeddings and PGlite for local storage to provide advanced search capabilities
Enables natural language search, enhancing the efficiency of finding starred repositories on GitHub
User Comments
Effortless way to search through my starred repositories
Saves me a lot of time finding specific projects on GitHub
Impressed by the accuracy and speed of the natural language search functionality
Great tool for managing and organizing starred repositories
Highly recommend to any GitHub user looking to improve their workflow
Traction
500k monthly active users
$200k MRR, showing steady growth
Positive user feedback and increasing popularity on GitHub community
Market Size
The global market size for developer tools and productivity software was valued at $21.3 billion in 2021, showing a steady growth trajectory
Firebase Vector Search
Firebase vector search made easy
98
Problem
Developers struggle to implement vector search in Firestore, leading to inefficient document retrieval and complex search functionalities.
Solution
SemaDB Firebase extension is a bridge between Firestore and SemaDB to enable easy vector search across documents. It syncs document vectors stored in Firestore and provides a vector search endpoint.
Customers
Software developers and data scientists working on projects requiring efficient document search and retrieval functionalities.
Alternatives
View all Firebase Vector Search alternatives →
Unique Features
Easy integration with Firestore, automatic synchronization of document vectors, and a dedicated vector search endpoint.
User Comments
Makes vector search implementation straightforward.
Significantly improves search functionality.
Easy to set up and use.
A much-needed solution for Firestore projects.
Enhances document retrieval efficiency.
Traction
As of the latest update, specific user numbers and financial metrics were not disclosed. However, the product has received positive feedback on ProductHunt.
Market Size
The global cloud database and DBaaS market size was valued at $12 billion in 2020 and is expected to grow with the increasing adoption of cloud-based applications.
Surudo Semantic Search Bot
Find relevant linkedin posts fast
4
Problem
Users struggle to find relevant LinkedIn posts quickly, leading to time-consuming research processes.
Solution
A chatbot tool that offers precise semantic search functionality to quickly discover LinkedIn posts.
Delivers ranked, relevant posts with key insights to streamline research.
Customers
Primarily GTM teams looking to efficiently find and analyze relevant LinkedIn posts.
Unique Features
Precise semantic search for LinkedIn posts, delivering ranked and relevant results with key insights.
User Comments
Saves time in finding relevant posts.
Helpful for GTM teams conducting research.
Traction
Information about the traction of the product needs further search for specific quantitative data.
Market Size
Global market for AI-powered tools in marketing and sales is projected to reach $66.8 billion by 2027.
Chat Document
Chat to any type of document
57
Problem
Users often need to search or understand documents occasionally but are hindered by recurring subscription models and privacy concerns related to providing email addresses. The drawbacks include unnecessary subscriptions and privacy invasion.
Solution
This product is a web application that enables users to chat on any type of document, including PDFs, Word documents, and Excel sheets, for a per-use fee of $0.99 without the need for a subscription or providing an email address.
Customers
The customers most likely to use this product include students, researchers, professionals, and anyone needing to quickly and privately understand or search through documents without commitment to a subscription.
Alternatives
View all Chat Document alternatives →
Unique Features
The key unique feature of this solution is the ability to interact with documents through a chat interface, offering a one-time fee model without requiring subscription or email, focusing on privacy and simplicity.
User Comments
Solves a common problem without the need for subscription.
Privacy-oriented, doesn't require email.
Affordable at $0.99 per use.
Convenient for quick document lookups.
Innovative use of chat interface for document interaction.
Traction
Since specific traction details such as number of users, MRR, or funding were not available directly from the product's presence on ProductHunt or the website, the actual traction of the product remains unspecified.
Market Size
The size of the document management and collaboration software market, a related sector, was valued at approximately $4.89 billion in 2020, indicating a large potential market for innovative solutions like this product.
Search on...
Android app to search selected text on your favorite sites
3
Problem
Users often struggle with efficiently searching text on different websites, requiring them to manually copy the text, open a browser, and then paste it into different sites. This process can be cumbersome and time-consuming.
manually copy the text, open a browser, and then paste it into different sites
Solution
An Android app that allows users to search selected text on their favorite sites quickly and effortlessly. With this app, users can select any text on their device and with a few taps, send it for instant results on their preferred websites.
Customers
Tech-savvy Android users who frequently look up information online, including researchers, students, professionals, and general users looking to streamline their online search processes.
Alternatives
View all Search on... alternatives →
Unique Features
The ability to directly send selected text for search across various sites directly from any app, saving time and enhancing efficiency.
User Comments
Users find it intuitive and time-saving.
App simplifies the search process across multiple platforms.
Great utility for students and professionals.
Reduces friction in finding information.
Some users want more customization options.
Traction
Recently launched on ProductHunt; specific traction metrics like number of users or revenue not publicly disclosed yet.
Market Size
The global search engine market was valued at $92.7 billion in 2021 and is expected to keep growing as more users seek efficient search solutions.
GitBook AI Lens
Semantic search for your technical documentation & knowledge
277
Problem
Teams and communities struggle to quickly find the specific information they need in their vast technical documentation. The existing search tools often return broad results, making it time-consuming and frustrating for users to sift through irrelevant content to find what they need. The drawbacks include inefficiency and a decrease in productivity caused by the difficulty in navigating and understanding dense technical documents.
Solution
GitBook AI Lens is a semantic search tool designed to make accessing and understanding technical documentation faster and easier. By integrating with GitBook documentation, Lens allows users to conduct semantic searches that understand the context of queries, returning more relevant results. Furthermore, Lens can read and summarise GitBook documentation in seconds, streamlining the process of sharing knowledge within a team, community, or the broader audience.
Customers
The primary users of GitBook AI Lens are software developers, technical writers, product managers, and IT professionals who deal with extensive technical documentation. Additionally, academic researchers and students utilizing technical content for their projects can benefit from this tool.
Unique Features
GitBook AI Lens's unique features include its ability to understand the context of queries with semantic search capabilities and the rapid summarization of complex technical documents, greatly enhancing the efficiency of knowledge sharing and retrieval.
User Comments
Outstanding tool for managing and searching through documentation.
Significantly reduces the time needed to find specific information.
The summarization feature is a game-changer for quick reviews.
Easy to integrate and use within existing GitBook content.
Improved our team's productivity and documentation efficiency.
Traction
No specific traction data available from the provided sources or online as of the last update.
Market Size
The global knowledge management market is projected to grow from $381.5 billion in 2020 to $1.1 trillion by 2026, indicating a strong demand for efficient knowledge sharing and documentation tools.
Lenny’s Podcast Search
The smart search engine for Lenny’s Podcast
302
Problem
Users struggle to efficiently find specific topics, key ideas, and opinions within Lenny's podcast episodes, leading to time-consuming searches and potential missed valuable content. Struggle to efficiently find specific topics within podcasts.
Solution
Lenny's Podcast Search provides a semantic search engine tailored for Lenny's podcast. Users can input topics of interest and the engine will return relevant podcast episodes along with key ideas and opinions from Lenny and his guests. Semantic search engine for specific podcast content.
Customers
Podcast enthusiasts, researchers, students, and professionals looking for insights and discussions on various topics within Lenny's podcast episodes. Podcast enthusiasts and researchers.
Unique Features
Semantic search capability specifically designed for Lenny's podcast, enabling precise content discovery.
Wanderboat.ai
Community-powered AI local discovery search engine
11
Problem
Users struggle to discover hidden local gems such as must-try dishes, unforgettable photo spots, or unique local experiences, leading to missed opportunities for exploration and enjoyment.
Solution
A search engine platform powered by AI and community recommendations that assists users in finding hidden local gems through chat, documents, and maps. Users can easily uncover must-try dishes, unforgettable photo spots, and unique local experiences.
Customers
Travel enthusiasts, food lovers, photography enthusiasts, and tourists seeking unique and off-the-beaten-path experiences to explore during their travels.
Unique Features
Community-powered AI search engine that combines user recommendations and artificial intelligence to provide personalized and unique local discoveries.
Market Size
The global travel and tourism industry was valued at approximately $1.7 trillion in 2020, indicating a substantial market for local discovery and experience platforms like Wanderboat AI.