Berri is an API that enables the development of production-ready enterprise LLM (Language Model) applications. It simplifies the process of data ingestion, embedding storage, model-agnostic querying, and index and model finetuning. Berri also provides a playground for testing and easy deployment of applications.
🚀 Use Cases
- Data Ingestion and Embedding Storage: Berri takes care of data ingestion and offers efficient storage for embeddings and vector databases.
- Model-Agnostic Querying: Berri supports querying databases and works seamlessly with major LLM providers, including OpenAI, Google, and Open Source.
- Finetuning: Berri allows users to improve their results through index and model finetuning in a simple and user-friendly manner.
- Testing: Users can utilize Berri’s playground to test results across instances and easily deploy their applications once satisfied.
- Enterprise Applications: Berri is designed to meet enterprise needs, offering features like security, compliance guarantees, dedicated servers, self-hosting options, and dedicated 1:1 support.
- Ingestion and Embedding Storage: Berri simplifies the process of data ingestion and provides efficient storage for embeddings and vector databases.
- Model-Agnostic Querying: Berri supports querying databases and is compatible with major LLM providers, including OpenAI, Google, and Open Source.
- Finetuning: Users can improve their results through index and model finetuning, which is made simple with Berri.
- Testing Playground: Berri offers a playground for testing results across instances, ensuring optimal performance before deployment.
- Simple Pricing: Berri offers a free starter plan, allowing individuals and prototypers to get started, and scalable Pro and Enterprise plans for more advanced needs.
- Enterprise Support: The Enterprise plan includes features such as unlimited instances, self-hosting options, dedicated servers, security and compliance guarantees, and dedicated 1:1 support.
- Notable Use Cases: Berri has helped companies like Hosteeva and Wellness XYZ increase automation, reduce latency, and simplify LLM app flows.