Financial Stock Analysis Agent leverages AI and machine learning to automate every step of stock research. It connects to financial APIs to fetch real-time price, volume, and historical data. Then it computes technical indicators (e.g., RSI, MACD, moving averages) and analyzes company fundamentals like earnings, revenue growth, and financial ratios. The agent visualizes key trends, identifies potential buy or sell signals, and evaluates risk metrics such as volatility and drawdown. Users can query the agent for customized insights, backtest strategies, and receive detailed reports in natural language or plotted charts, accelerating investment research and decision-making.

Experience the future of web browsing with Bookmarks AI, a cutting-edge Chrome extension powered by Google's advanced Gemini Pro API. Bookmarks AI goes beyond traditional summarization, offering a dynamic and intelligent way to interact with your bookmarked content. It allows you to delve into your bookmarked web pages, answer custom queries with AI, analyze individual or multiple pages, and evaluate content against set criteria. Whether for research, productivity, or personal management, Bookmarks AI transforms the way you interact with online content.

ChatGPT Prompt Helper is a versatile browser extension that improves the usability of ChatGPT by providing users with customized prompts and management tools. This extension allows users to quickly generate and edit prompts, access frequently used queries, and optimize their interactions for better responses. By streamlining the process of creating engaging and effective prompts, it enhances your overall experience, making communication with ChatGPT more productive and enjoyable. It is ideal for users seeking to maximize the capabilities of AI conversation.

LlamaIndex is a developer-focused Python library designed to bridge the gap between large language models and private or domain-specific data. It offers multiple index types—such as vector, tree, and keyword indices—along with adapters for databases, file systems, and web APIs. The framework includes tools for slicing documents into nodes, embedding those nodes via popular embedding models, and performing smart retrieval to supply context to an LLM. With built-in caching, query schemas, and node management, LlamaIndex streamlines building retrieval-augmented generation, enabling highly accurate, context-rich responses in applications like chatbots, QA services, and analytics pipelines.