Developing AI-powered applications that leverage proprietary data often requires extensive manual configuration of retrieval-augmented generation (RAG) pipelines. Setting up, maintaining, and scaling RAG infrastructure for diverse data sources can be time-consuming and complex, hindering rapid application development. Existing LLMs also lack inherent personalization and control for specific use cases.

Miriel provides a low-code dynamic RAG platform that simplifies the integration of AI into applications. The platform enables developers to connect to various data sources and build personalized AI applications with minimal coding. Miriel's intelligent indexing and retrieval are tailored to each data source, ensuring high-quality results. The platform's API allows developers to add data sources and make intelligent queries with just a few lines of code, accelerating deployment. Miriel also offers security features such as data encryption and token-level permission management, along with auditability and source attribution to eliminate the AI black box.

Dynamic RAG platform with intelligent indexing and retrieval tailored to each data source

Low-code API for connecting data sources and making intelligent queries with minimal coding

Data encryption and token-level permission management for enhanced security and control

Auditability and source attribution for transparency and accountability

Support for unstructured data (e.g., zoom calls, PDFs), structured data (e.g., SQL databases, GitHub), and streaming data (e.g., Discord/Slack chats, live video feeds)

Capabilities for pre-processing data, including entity recognition, pronoun disambiguation, and data deduplication

Miriel is designed for software developers and product teams looking to rapidly build and deploy personalized AI applications that leverage proprietary data.