Anna Mobile LLM Agent is a conversational AI framework designed for seamless integration within the Anna Money mobile app. It employs large language models to interpret user natural language inputs, fetch real-time account and transaction data via secure APIs, and perform tasks such as expense categorization, transaction summarization, and budgeting advice. Developers can configure custom tools, triggers, and context memories to tailor the agent to specific financial workflows. With built-in support for OpenAI, Azure OpenAI, and local transformers models, as well as a React Native front-end, the agent ensures responsive, secure, and personalized financial assistance on both iOS and Android devices.

AppShip is a comprehensive platform designed to streamline the application development lifecycle. It allows developers to build, deploy, maintain, and monitor their applications seamlessly across multiple B2B app stores. By utilizing AppShip, businesses can reduce the time and complexity involved in managing multiple versions and updates of their apps, ensuring a more consistent user experience and opening up new opportunities for growth in various marketplaces.

This open-source framework combines the AgentSimJs agent modeling library with Three.js's 3D graphics engine to deliver interactive, browser-based multi-agent simulations. Users can define agent types, behaviors, and environmental rules, configure collision detection and event handling, and visualize simulations in real time with customizable rendering options. The library supports dynamic controls, scene management, and performance tuning, making it ideal for research, education, and prototyping of complex agent-based scenarios.

Practical AI Agents provides developers with a comprehensive framework and ready-to-use examples to construct autonomous agents powered by large language models. It demonstrates how to integrate API tools (e.g., web browsers, databases, custom functions), implement RAG-style memory, manage conversation context, and perform dynamic planning. You can adapt examples for chatbots, data analysis assistants, task automation scripts, or research tools. The repository includes notebooks, Dockerfiles, and configuration files to streamline setup and deployment across environments.

The Ten AI Agent platform provides a graphical builder where users connect various data sources—cloud documents, databases, or APIs—and define an agent’s purpose and tone. Agents can answer user queries with context-aware responses, summarize large documents on demand, and trigger automated workflows such as ticket creation or email notifications. A built-in analytics dashboard tracks usage, performance, and user satisfaction. Agents can be customized with unique personalities and fine-tuned prompts without writing code. Once ready, they can be deployed via embed code, REST APIs, or integrations with Slack, MS Teams, and other messaging platforms to deliver seamless conversational experiences across channels.