Dante AI is a powerful AI agent that specializes in task automation and workflow optimization. It combines natural language processing and machine learning techniques to interact intelligently with users, understand their commands, and execute tasks efficiently. Its versatile features include integration with various applications, real-time data analysis, and automated scheduling. Whether you're looking to organize projects, manage schedules, or streamline communication, Dante AI adapts to your needs, making it an essential tool for both personal and professional use.

Memonto functions as a middleware library for AI agents, orchestrating the complete memory lifecycle. During each conversation turn, it records user and AI messages, distills salient details, and generates concise summaries. These summaries are converted into embeddings and stored in vector databases or file-based stores. When constructing new prompts, Memonto performs semantic searches to retrieve the most relevant historical memories, enabling agents to maintain context, recall user preferences, and provide personalized responses. It supports multiple storage backends (SQLite, FAISS, Redis) and offers configurable pipelines for embedding, summarization, and retrieval. Developers can seamlessly integrate Memonto into existing agent frameworks, boosting coherence and long-term engagement.

The Great GPT Firewall provides a policy-driven gateway for GPT-based applications. It sits between your app and the GPT API, examining each request and response against user-defined JSON-schema policies. With both a command-line interface and easily importable library, you can define rules to block or modify disallowed prompts and outputs, log any violations, and receive real-time alerts. The tool supports extensible rule sets, custom handlers for violation events, and seamless integration into CI/CD pipelines, helping teams maintain content safety and regulatory compliance across diverse AI deployments.

AgentServe provides a unified interface for creating and deploying AI agents. Users define agent behaviors in configuration files or code, integrate external tools or knowledge sources, and expose agents over REST endpoints. The framework handles model routing, parallel requests, health checks, logging, and metrics out of the box. AgentServe’s modular design allows plugging in new models, custom tools, or scheduling policies, making it ideal for building chatbots, automated workflows, and multi-agent systems in a scalable, maintainable way.