Detailed Introduction
Wavefront is an open-source enterprise AI middleware designed to unify data, models, and services into composable workflows and agents. It provides a unified API layer, fine-grained RBAC, and observability, with native support for Retrieval-Augmented Generation (RAG) and the Model Context Protocol (MCP), enabling teams to deliver governed, auditable AI applications in complex enterprise environments.
Main Features
- Unified API layer for connecting databases, storage, and external services.
- Enterprise security with SSO and role-based access control (RBAC).
- Native RAG and MCP support for knowledge-driven agents and retrieval pipelines.
- Built-in observability and evaluation via OpenTelemetry, Prometheus, and Grafana.
- Visual Studio for drag-and-drop workflow design and YAML import/export.
Use Cases
Wavefront is suited for teams building production AI solutions in enterprises, such as conversational automation for contact centers, underwriting and risk workflows, compliance automation, and multi-source RAG platforms. It supports both self-hosted and cloud hybrid deployments.
Technical Features
Built on a modular architecture and the Flo AI framework, Wavefront supports Python and TypeScript components and provides CLI, server, and client tooling. Its plugin-based design simplifies integrating new models, data sources, and observability tools while preserving operational visibility for production systems.