System Architecture
Enterprise RAG for private intelligence
ISA-RAG uses a modular, service-oriented architecture for secure document ingestion, retrieval and governed AI responses. This page shows the architecture at a high level; authenticated users can inspect the deployment details.
Data Flow
End-to-end flow from knowledge ingestion to retrieval-augmented response generation.
Controlled access
Requests pass through an authenticated access layer before reaching internal services.
Ingestion pipeline
Documents are parsed, normalized, embedded and indexed for retrieval.
Encrypted end-to-end
Transport encryption and managed secrets protect system boundaries.
Authenticated Detail
Detailed architecture is restricted
Runtime metrics, deployment topology, storage layout and operational defaults are only shown after sign-in.
Architecture Layers
Public overviewAccess & Governance
A controlled entry layer authenticates requests, applies policy and routes traffic to internal capabilities.
Document Intelligence
Uploaded knowledge is normalized into searchable units while preserving metadata required for grounded answers.
Retrieval & Reasoning
The assistant retrieves relevant context before generation so responses can stay aligned to the approved corpus.
Operational Controls
The platform is designed around isolated services, encrypted transport, observability and repeatable deployment.
Deployment Options
ISA-RAG can run in private infrastructure or cloud-native environments. Public documentation intentionally avoids exposing runtime topology, exact network configuration and sizing details.
Private infrastructure
Self-managed deployment
Suitable for organizations that need tight control over data locality, identity integration and network boundaries.
Cloud-native
Managed platform deployment
Suitable for teams that prefer managed databases, elastic compute and cloud-native operations while preserving least-privilege design.