Fin-R1 is a large language model designed specifically for the financial field, aimed at enhancing financial reasoning capabilities. Jointly developed by Shanghai University of Finance and Economics and Caiyue Xingchen, it is fine-tuned and reinforced learning based on Qwen2.5-7B-Instruct, possessing efficient financial reasoning capabilities and is suitable for core financial scenarios such as banking and securities. This model is free and open-source, facilitating user adoption and improvement.

Scira is an AI-powered search engine designed to provide users with a more efficient and accurate information retrieval experience through a powerful language model and search capabilities. It supports multiple language models, such as Grok 2.0 and Claude 3.5 Sonnet, and integrates search tools like Tavily, providing features such as web search, programming code execution, and weather queries. Scira's main advantages are its simple interface and powerful feature integration, making it suitable for users who are dissatisfied with traditional search engines and want to use AI to improve search efficiency. This project is open-source and free; users can deploy it locally or use the online service provided according to their needs.

This product is a full-stack application that leverages LLM (Large Language Models) and LangChain technology, combined with LangGraph, to retrieve and analyze stock data and news. It uses ChromaDB as a vector database to support semantic search and data visualization, providing users with deep insights into the stock market. It is primarily aimed at investors, financial analysts, and data scientists, helping them quickly acquire and analyze stock-related information to support decision-making. The product is currently open-source and free, making it suitable for users who need to efficiently process financial data and news.

Gemini-Search is an AI search engine that emulates Perplexity, utilizing Google's Gemini 2.0 Flash model and Google Search API to deliver real-time web search results and citations, helping users quickly access accurate information. Its main advantages include fast response times and a clear user interface, enhancing efficiency in information retrieval. The product is currently free and suitable for users of all sizes.

ModernBERT-large is a state-of-the-art bidirectional encoder Transformer model (BERT style) pre-trained on 2 trillion tokens of English and code data, with a native context length of up to 8192 tokens. This model incorporates the latest architectural improvements such as Rotary Positional Embeddings (RoPE) for long-context support, local-global alternating attention for enhanced efficiency with long inputs, and padding-free and Flash Attention for improved inference speed. ModernBERT-long is suitable for tasks involving the handling of long documents, such as retrieval, classification, and semantic search within large corpora. The training data primarily consists of English and code, which may result in lower performance with other languages.

MarS is a financial market simulation engine driven by a generative foundational model (LMM), capable of dynamically generating sequences of orders based on historical financial market data in response to various conditions, including user-injected interactive orders, fuzzy target scenario descriptions, and current/recent market data. MarS matches generated order sequences and user interactive orders in real-time within a simulation clearinghouse, producing fine-grained simulated market trajectories. The flexibility of MarS allows it to support various downstream applications such as forecasting, detection systems, analysis platforms, and agent training environments.

kelindar/search is a Go language library that provides functionality for embedded vector search and semantic embeddings, built on llama.cpp. This library is particularly suitable for small to medium-sized projects that require powerful semantic search capabilities while maintaining a simple and efficient implementation. It supports GGUF BERT models, allowing users to leverage advanced embedding techniques without delving into the complexities of traditional search systems. The library also offers GPU acceleration for fast computations on supported hardware. If your dataset contains fewer than 100,000 entries, this library can be easily integrated into your Go application to implement semantic search features.

Claude Financial Data Analyst is a Next.js application that combines Claude AI capabilities with interactive data visualization, specifically designed for analyzing financial data. This product offers intelligent data analysis through chat, supports multi-format file uploads, and generates various charts based on the analysis. It is applicable not only in finance but also adaptable to areas like environmental data, sports performance, and social media analysis.

EasyFin is an AI-driven stock analysis platform that uses advanced artificial intelligence technology and big data analysis to provide users with accurate and comprehensive stock analysis and investment advice. The main advantage of EasyFin lies in quickly analyzing large amounts of data, intelligently recommending investment strategies, providing real-time market dynamics, and helping users make wiser investment decisions. EasyFin is positioned to provide high-quality investment analysis tools for investors, traders, and financial professionals.

Amsflow offers an all-in-one solution for modern investment analysis, leveraging smart tools to accelerate analysis and provide users with unique advantages. The product has rich background and is positioned to offer comprehensive market analysis services.

AI Answer Generator is an online tool powered by advanced AI models that can instantly generate accurate answers related to the input question. Users just need to enter their question to get immediate and relevant answers without registration or technical skills. This tool is applicable for knowledge lookup, fact verification, learning research, brainstorming, writing translation and language learning, productivity, Q&A, as well as general curiosity and inspiration.

Reimbursable is a website designed to help users easily track medical expenses. It provides a detailed directory of HSA-eligible projects, helping users better manage and track medical costs. Users can quickly find specific project HSA eligibility through the search function.

Thunder.vc is a technology-driven investment bank that helps founders raise funds, execute mergers and acquisitions, and plan exit strategies. It has raised over $1.2 billion and connected over 6800 investors.

Baidu Search Open Platform's AI Open Program offers application developers the opportunity for precise traffic distribution to hundreds of millions of users. With the support of AI technology, developers can quickly integrate with the Baidu search engine, improving application exposure and user visits. The platform also provides multi-dimensional incentive support to help developers find suitable business models.

Ai2 PaperFinder is an online tool dedicated to helping researchers quickly find the literature they need. The platform brings together over 8 million full-text papers and 108 million abstracts, with powerful literature retrieval and synthesis capabilities. Through simple keyword searches, users can quickly access relevant research, greatly improving research efficiency. The product is born from an urgent need for research literature and is priced as free, suitable for all types of researchers.

Fin-R1 is a large language model designed specifically for the financial field, aimed at enhancing financial reasoning capabilities. Jointly developed by Shanghai University of Finance and Economics and Caiyue Xingchen, it is fine-tuned and reinforced learning based on Qwen2.5-7B-Instruct, possessing efficient financial reasoning capabilities and is suitable for core financial scenarios such as banking and securities. This model is free and open-source, facilitating user adoption and improvement.