LangGraph Agent combines LLMs with a graph-structured memory to build autonomous agents that can remember facts, reason over relationships, and call external functions or tools when needed. Developers define memory schemas as graph nodes and edges, plug in custom tools or APIs, and orchestrate agent workflows through configurable planners and executors. This approach enhances context retention, enables knowledge-driven decision making, and supports dynamic tool invocation in diverse applications.

RotimeApp provides a flexible scheduling solution that dynamically adjusts to your actual waking hours. Whether you're an early riser or a night owl, RotimeApp helps you seamlessly align your daily routines with your natural sleep patterns. This ensures you stay on track with your tasks and appointments without the stress of fixed schedules. RotimeApp offers features such as task reminders, adjustment notifications, and routine optimization, making it the perfect tool for anyone looking to manage their time more effectively.

Wellpin is a sophisticated scheduling assistant that enables users to easily coordinate meetings and appointments. It eliminates the hassle of back-and-forth communication by providing personalized meeting links and smart conflict detection. Ideal for remote and hybrid teams, Wellpin ensures users can manage their schedules efficiently, connecting with colleagues without unnecessary delays. Its user-friendly interface and advanced features make it a go-to solution for anyone looking to improve their meeting organization and productivity.

Self-Determining AI Agents is a Python-based framework designed to simplify the creation of autonomous AI agents. It features a customizable planning loop where agents generate tasks, plan strategies, and execute actions using integrated tools. The framework includes persistent memory modules for context retention, a flexible task scheduling system, and hooks for custom tool integrations such as web APIs or database queries. Developers define agent goals via configuration files or code, and the library handles the iterative decision-making process. It supports logging, performance monitoring, and can be extended with new planning algorithms. Ideal for research, automating workflows, and prototyping intelligent multi-agent systems.

TalentScreen-AI is a cutting-edge recruitment tool that automates the interview process using advanced AI technology. It provides real-time, human-like interview experiences and generates instant performance reports. This allows HR teams and recruiters to make more informed decisions quickly and efficiently. The platform eliminates the need for scheduling hassles, supports candidate flexibility, and ensures unbiased, consistent interviews.

Agent-Go provides a modular framework for building autonomous AI agents in Go. It integrates LLM providers (such as OpenAI), vector-based memory stores for long-term context retention, and a flexible planning engine that breaks down user requests into executable steps. Developers define and register custom tools (APIs, databases, or shell commands) that agents can invoke. A conversation manager tracks dialog history, while a configurable planner orchestrates tool calls and LLM interactions. This allows teams to rapidly prototype AI-driven assistants, automated workflows, and task-oriented bots in a production-ready Go environment.