Marqo provides an AI-powered search platform that optimizes search conversion by understanding and interpreting user intent. The platform connects product catalogs and user behavior data to build a personalized search engine model. Marqo replaces manual tagging with automated analysis and delivers highly relevant search results. Its core features include multimodal search, personalized recommendations, and customization based on business goals, making it an effective solution for ecommerce and content search applications.

ConsX is a next-gen equity research center that combines human expertise with AI-driven insights to generate hedge-fund-level research for over 6,000 companies in real-time. It aims to provide strong returns with reduced risk through its AlphaFlex Portfolio, leveraging growth and safety strategies that adapt to market conditions. This makes it an ideal platform for investors who want to build generational wealth.

PaperLens combines cutting-edge AI technology with intuitive design to help you find the most relevant academic research. With features like RAG-Powered Search, Research Assistant Chatbot, saving papers, and smart filtering, PaperLens ensures you get precise, real-time results for every query. Whether analyzing complex papers or compiling literature reviews, PaperLens streamlines the research process, making it more efficient and user-friendly.

Querative is an AI-powered tool designed to enhance your search capabilities. It interprets your natural language queries and converts them into advanced search parameters, optimizing searches across multiple platforms such as LinkedIn and Instagram. The tool helps you save time and effort by generating an optimized query and opening results in a new tab using a regular search engine, combining traditional search familiarity with advanced optimization techniques.

Summative Info Researcher Agents offers a modular framework of AI-driven agents designed to perform end-to-end research tasks. It automates web searches, scrapes content, extracts relevant data points, and synthesizes findings into clear, structured summaries. Built atop popular LLMs and extensible via plugin tools, the project allows users to define multi-step workflows, chain agents together, and adjust settings for domain-specific queries. Its flexible architecture supports integration with custom APIs, database connectors, and scheduling systems to fit academic, business, or personal research needs.