LAuRA streamlines the creation of intelligent AI agents by offering a structured pipeline of planning, retrieval, execution, and memory management modules. Users define complex tasks which LAuRA’s Planner decomposes into actionable steps, the Retriever fetches information from vector databases or APIs, and the Executor invokes external services or tools. A built-in memory system maintains context across interactions, enabling stateful and coherent conversations. With extensible connectors for popular LLMs and vector stores, LAuRA supports rapid prototyping and scaling of custom agents for use cases like document analysis, automated reporting, personalized assistants, and business process automation. Its open-source design fosters community contributions and integration flexibility.

Moonbeam Exchange is a data science platform utilizing over 100 data sources to provide comprehensive market intelligence and innovation strategies. Through its brokerage network, Moonbeam aids startups, corporate innovation labs, and economic development organizations in accelerating innovation with deep industry insights and unconventional thinking. Its services include market intelligence reports, tailored innovation programs, and strategic sourcing, empowering businesses to make data-driven decisions, foster innovation, and maximize benefits from global innovation ecosystems.

Quadratic is a revolutionary spreadsheet application designed for modern data collaboration. It features built-in support for Python programming, SQL queries, and AI-powered tools. The platform allows teams to work seamlessly with data, utilizing advanced data science and analytical tools to gather insights efficiently. Users can pull data from various sources including SaaS, databases, CSV files, and APIs, and manipulate it directly within the spreadsheet interface. Ideal for data scientists, analysts, and collaborative teams, Quadratic allows for sophisticated data manipulation and decision-making.

Analytics Model is an advanced AI analytics platform that empowers users to generate personalized insights from their data quickly. By integrating over 500+ data sources, it creates a unified view for better decision-making. Users can describe the type of visualization or insight they need in plain language, and the platform generates the desired outputs in seconds. It’s equipped to handle large datasets, supports various chart types, and can be embedded within other platforms for enhanced user engagement.

GPT Agent provides a modular framework to build intelligent agents powered by the latest GPT models. Users start by defining task workflows through a visual editor, specifying inputs, actions, and output formats. The platform supports integration with external data sources and custom knowledge bases, enabling agents to perform complex research and summarization tasks. It also features API access for headless deployments and a web dashboard to monitor performance, tune model parameters, and review conversation logs. Whether automating customer interactions, generating reports, or managing schedules, GPT Agent offers end-to-end support from agent creation to scalable production rollout.

Chat-With-CUHKSZ provides a streamlined pipeline for building a domain-specific chatbot over the CUHKSZ knowledge base. After cloning the repository, users configure their OpenAI API credentials and specify document sources, such as campus PDFs, website pages, and research papers. The tool uses LlamaIndex to preprocess and index documents, creating an efficient vectorized store. LangChain orchestrates the retrieval and prompts, delivering relevant answers in a conversational interface. The architecture supports adding custom documents, fine-tuning prompt strategies, and deploying via Streamlit or a Python server. It also integrates optional semantic search enhancements, supports logging queries for auditing, and can be extended to other universities with minimal configuration.