Stop wrestling with CUDA drivers, Python dependencies, and complex Docker configurations. We provide a pre-configured, fully-managed Open WebUI environment so you can immediately start building, testing, and deploying next-generation AI applications.
This is your LLM workbench. Forget the DevOps overhead and focus purely on innovation. Our service provides a robust, isolated Open WebUI instance that acts as a powerful orchestration layer for any local or API-based Large Language Model. It's the perfect backend and experimentation platform for developers building AI-native applications, researchers testing new theories, and engineers fine-tuning models.
Why be locked into one ecosystem? Our platform lets you "manage multiple local LLMs" effortlessly. Load GGUF models via Ollama, pull directly from Hugging Face, or connect to any OpenAI-compatible API endpoint. A/B test prompts across different models side-by-side, compare latency and output quality in a single UI, and benchmark performance to find the optimal model for your use case without ever changing your code.
This is more than just a chat interface. We provide a complete environment for building complex applications. Prototype data analysis workflows with a built-in, sandboxed Python code interpreter. Implement powerful Retrieval-Augmented Generation (RAG) pipelines out-of-the-box by connecting to integrated and managed vector databases like ChromaDB and Qdrant. Grant models real-time access to information with built-in web search functionality.
Go beyond simple question-and-answer. Use our sandbox to design, build, and test multi-step agentic workflows. You can easily define custom tools and functions that the LLM can invoke, allowing it to interact with your proprietary databases, internal software, or any external API.
This is the ultimate testbed for building the next generation of autonomous AI agents.
Accelerate your development cycle. Use the intuitive web interface for rapid experimentation, prompt engineering, and building RAG pipelines. Once you have a working model chain, integrate it directly into your application. The entire stack is accessible via a built-in, OpenAI-compatible API endpoint. The logic you prototype in the UI is the same logic you'll use in production, ensuring a seamless transition from idea to deployment.
Quickly test, benchmark, and compare open-source models without the setup and teardown of local environments.
Rapidly prototype and integrate LLM features into your products with a stable, ready-to-use backend API.
Build and refine complex RAG pipelines, testing different chunking strategies, embedding models, and vector stores in a live environment.
Experiment with cutting-edge concepts like multi-agent systems and custom tool usage in a flexible, pre-configured sandbox.
Everything you need to build, test, and deploy AI applications at scale.
Seamlessly switch between local models (Ollama, GGUF) and API providers (OpenAI, Anthropic, Cohere) in a single interface.
Built-in ChromaDB and Qdrant support for RAG applications. Upload documents and start querying your knowledge base immediately.
Sandboxed Python environment for data analysis, visualization, and complex computations. Perfect for AI-assisted development.
Real-time web search capabilities and custom tool integration. Build agents that can interact with external APIs and services.
Isolated environments, secure API endpoints, and comprehensive logging. Your development work stays private and secure.
Deploy your prototypes instantly with a standard API interface. Drop-in replacement for OpenAI API calls in your applications.
Skip the setup complexity and start building production-ready AI applications today.