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.

OpenNARS is built upon the principles of Non-Axiomatic Logic, enabling the system to perform deduction, induction, and abduction using truth-value pairs that reflect uncertainty. It maintains an experience-based memory of statements and dynamically recruits inference rules based on available resources, ensuring robust performance in real-time environments. The engine’s belief revision mechanism updates confidences as new information arrives, improving decision accuracy. Developers can integrate OpenNARS via provided SDKs in Java, C++, Python, JavaScript, Dart, or Go, and deploy it on desktops, servers, mobile devices, or embedded systems. Typical applications include cognitive robotics, autonomous agents, and complex problem-solving tasks where adaptive learning and efficient knowledge management are essential.

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.