OmniBot is an advanced AI assistant that runs LLMs directly in your browser using WebGPU, ensuring complete data privacy by processing all information locally on your device. Designed for a seamless AI interaction, it allows offline usage after an initial model download and supports custom memory integration for personalized responses. Ideal for professionals and AI enthusiasts, OmniBot simplifies maintaining privacy while using powerful AI capabilities directly on a browser.

Mindlake utilizes a large language model (LLM) to synthesize and analyze discussions related to ongoing projects across different platforms like messaging apps and project management tools. By consolidating communications, it enhances team collaboration by reducing information overload, allowing users to focus on key insights and action items. Its intelligent search features make it easier for teams to retrieve vital information quickly, ensuring everyone stays on the same page and enhancing overall workflow efficiency.

Rhippo revolutionizes the way teams collaborate with their LLM chatbots. By creating a 'brain' that injects relevant context into your prompts and maintains an updating knowledge database, it ensures that only important project information is shared. The setup is swift, taking less than 10 minutes, and includes integrations with Slack and Google Drive for seamless communication. Rhippo promises improved responses with state-of-the-art embedding models, guaranteeing data transparency through Google Drive.

Divine Agent is a comprehensive AI agent platform that simplifies the design, development, and deployment of autonomous digital workers. Through its intuitive visual workflow builder, users can define agent behavior as a sequence of nodes, connect to any REST or GraphQL API, and select from supported LLMs like OpenAI and Google PaLM. The built-in memory module preserves context across sessions, while real-time analytics track usage, performance, and errors. Once tested, agents can be deployed as HTTP endpoints or integrated with channels like Slack, email, and custom applications, enabling rapid automation of customer support, sales, and knowledge tasks.

This system automates compliance audits by embedding policies and regulatory documents into a vector store, using retrieval-augmented LLM queries to analyze and report compliance gaps. Users ingest their compliance corpus, configure the vector database, and ask tailored audit questions. The AI agent retrieves relevant sections and produces structured audit reports, highlighting potential violations, recommending actions, and logging each step for traceability.

Rewrite.ly is a powerful Chrome extension that provides LLM-powered shortcuts to improve writing quality and efficiency. With a simple right-click, users can access built-in options to adjust tone, add emojis, convert text to bullet points, and more. Customize your writing style and create unique shortcuts to suit personal or professional needs, enhancing workflows and productivity by tenfold.

ai-agents-trial is an open-source Python project demonstrating how to build autonomous AI agents using LLMs. It provides modular abstractions for agent planning, tool invocation (e.g., web search, calculators), and memory management. Developers can define custom tools, chain actions across multiple steps, and persist context across sessions. The codebase uses OpenAI APIs alongside helper utilities to orchestrate workflows, making it ideal for rapid prototyping of chat-based assistants, research bots, or domain-specific automation agents. Integration points allow extending functionality with new connectors and data sources without altering core logic.

AI Diagnostic Assistant collects patient-reported symptoms through a simple interface and sends them to a configured LLM (such as GPT-3.5 or GPT-4). It analyzes the input to generate a list of possible medical conditions, provides probability rankings, severity assessments, and suggested actions. The tool can output a structured report for further review and can be extended with custom prompts, integration modules, or alternate LLM endpoints. It is designed for rapid prototyping and preliminary diagnostic support, not as a substitute for professional medical evaluation.