The open-source alternative to Carbon.ai. Build powerful RAG applications with any data source, at any scale.
Supavec is an innovative open-source platform designed to serve as a powerful alternative to Carbon.ai, allowing developers to build robust Retrieval-Augmented Generation (RAG) applications using any data source. With its user-friendly infrastructure, Supavec can be set up quickly, making it ideal for teams looking to scale their data-driven projects without the overhead of complex setups. Its extensive features cater to a variety of needs, making it a versatile tool for both small startups and larger enterprises.
The platform is engineered with modern technology and is celebrated for its exceptional performance and ease of use. By leveraging a strong backend powered by Supabase and offering seamless integrations, Supavec stands out as a compelling choice for anyone interested in harnessing the power of AI and analytics without the typical hassle associated with such systems.
OSS RAG-as-a-Service: Quickly spin up vector search and chat API in under 5 minutes, streamlining the development process.
Scalable Multi-Tenant Design: Built to accommodate multiple users without compromising on performance, ensuring a robust solution for growing teams.
Row-Level Security (RLS): Provides team-level data isolation, making it easier to manage access and privacy across different user groups.
Cost-Efficient Usage-Based Billing: Offers a flexible pricing model that grows with your needs, starting with free usage and scaling up as demands increase.
Batch Embeddings Optimization: Reduce OpenAI costs by up to 65% while improving performance through effective batch processing of embeddings.
Real-Time Analytics: Fully integrated with PostHog, enabling detailed tracking of product and API events for better insights.
Visual Debugging and Guided Onboarding: Enhance developer experience with live embedding previews and progressive disclosure to ease into the platform.
API Performance Options: Choose between streaming or standard responses to optimize latency and meet the needs of diverse applications.
