AgenticRAG provides a modular architecture for creating autonomous agents that leverage retrieval-augmented generation (RAG). It offers components to index documents in vector stores, retrieve relevant context, and feed it into LLMs to generate context-aware responses. Users can integrate external APIs and tools, configure memory stores to track conversation history, and define custom workflows to orchestrate multi-step decision-making processes. The framework supports popular vector databases like Pinecone and FAISS, and LLM providers such as OpenAI, allowing seamless switching or multi-model setups. With built-in abstractions for agent loops and tool management, AgenticRAG simplifies development of agents capable of tasks like document QA, automated research, and knowledge-driven automation, reducing boilerplate code and accelerating time to deployment.

Folderer integrates AI technology with your GitHub repositories, transforming your ideas into production-ready code. The AI understands your project requirements, generates high-quality, customized code, and seamlessly commits changes to your GitHub repository. You interact with Folderer through a chat interface, refining the code according to your needs. This AI-powered workflow saves time, reduces errors, and allows you to focus on core development tasks.

PySpur provides an integrated environment for constructing, testing, and deploying AI agents via a user-friendly, node-based interface. Developers assemble chains of actions—such as language model calls, data retrieval, decision branching, and API interactions—by dragging and connecting modular blocks. A live simulation mode lets engineers validate logic, inspect intermediate states, and debug workflows before deployment. PySpur also offers version control of agent flows, performance profiling, and one-click deployment to cloud or on-premise infrastructure. With pluggable connectors and support for popular LLMs and vector databases, teams can prototype complex reasoning agents, automated assistants, or data pipelines quickly. Open-source and extensible, PySpur minimizes boilerplate and infrastructure overhead, enabling faster iteration and more robust agent solutions.

Toolhouse is a developer platform designed to build and deploy AI agents and workflows without the hassle of boilerplate code. It comes with pre-built agentic frameworks like RAG, evals, API integrations, memory, cache, prompts, and tools, enabling developers to quickly build and ship functional AI products. With robust support for third-party app integrations, Toolhouse offers a seamless development and debugging experience, significantly accelerating the production lifecycle.