Your Fabric data stays in OneLake. Your AI queries leave the building.
Microsoft Fabric consolidates your enterprise data in OneLake. But every AI query over that data — with Azure OpenAI, Copilot, or any cloud LLM — sends your data context to an external endpoint. The data lives in Fabric. The inference does not.
For enterprises in regulated industries, this is an architecture problem. Fabric enforces data residency on storage. It cannot enforce data residency on inference. That gap is where enterprise data leaves your control.
4MINDS closes the gap. LLM inference runs inside your environment — on your Fabric capacity or your Kubernetes cluster. OneLake data stays in OneLake. Inference stays inside your perimeter.
OneLake AI integration: direct connection, no data relay
4MINDS integrates with Microsoft Fabric Lakehouses and Warehouses via the OneLake REST API. Authentication runs through Microsoft Entra, the same identity infrastructure you already govern. Synchronization is event-driven: 4MINDS detects changes and syncs only updated data, not full dataset transfers. Structured tables, Delta Lake files, and unstructured documents in OneLake are all supported. 4MINDS is listed on the Microsoft Marketplace.
Why cloud LLMs on Microsoft Fabric send your data out
Microsoft Fabric stores your enterprise data in OneLake. Azure OpenAI, Copilot, and other cloud LLM services can query that data, but they send your data context to an external inference endpoint. Fabric enforces data residency on storage. It cannot enforce data residency on the inference call.
For most enterprises, that's a tolerable architecture. For regulated industries (financial services, healthcare, defense), it often isn't. Your compliance team approved Fabric. They did not approve sending your Fabric data to an external AI API.
Azure OpenAI is a static cloud model trained on public data. It doesn't know your business, your terminology, or your processes. 4MINDS Ghost Weights trains a shadow copy of the model on your Fabric data (Lakehouse tables, pipeline outputs, corrections), passes it through an eval gate, and atomically swaps it into production with zero downtime. The model learns your business continuously, on your data, without leaving your network.
Custom LLMs on your Fabric data. Four architectural steps.
4MINDS connects to your OneLake endpoint using your existing Fabric workspace credentials via Microsoft Entra. No data is copied outside your tenant.
LLM inference runs inside your Kubernetes cluster or on your Fabric capacity — not on 4MINDS infrastructure. Your GPU, your compute.
4MINDS ingests your Lakehouse data into an on-prem knowledge graph. Multi-hop queries traverse entity relationships extracted from your actual data.
The model adapts to your Fabric data patterns continuously. Every update passes an eval gate before reaching production.
Enterprise AI on Microsoft Fabric: five ways to build with 4MINDS
Ask questions against Lakehouse tables, Delta Lake files, and data warehouse datasets in plain English. 4MINDS runs inference inside your Fabric environment. The answer comes back. The data never left.
Deploy agents that read pipeline outputs, detect anomalies, and trigger downstream actions, all within your Fabric workspace. Agent state persists inside your infrastructure, not on external servers.
Ghost Weights connects to your OneLake data as a continuous training source. Your Lakehouse tables, documents, and pipeline outputs become the training signal. The model updates on a cycle, and every update passes an eval gate before it touches production.
Every Ghost Weights model update carries a timestamped eval result. Regulated industries get a built-in audit trail proving the model met quality standards before deployment. The architecture enforces it automatically.
For workloads that require zero external network connectivity, 4MINDS deploys fully air-gapped. LLM inference, model updates, and knowledge graph queries all run inside your perimeter with no egress path to external networks.
Built for the Microsoft Fabric stack
- Deploys on AKS, any managed Kubernetes, or on-prem Kubernetes clusters. Works alongside your existing Fabric capacity.
- On-prem or fully air-gapped, with no external API dependencies. Air-gapped mode has zero egress paths to external networks.
- Uses your existing Entra service principal for all OneLake access. Your identity governance policies apply without modification.
- Builds a knowledge graph from your Fabric data. Multi-hop queries traverse entity relationships, not a flat similarity index.
Fabric stores it. 4MINDS queries it. Neither sends it out.
Microsoft Fabric enforces data residency on storage through OneLake. 4MINDS enforces data residency on inference through on-premises deployment. The model runs in your facility. Your network. Under your control. True sovereignty is architectural, not geographical.
Run your first LLM query on OneLake data in one session.
30 minutes with a 4MINDS engineer. We connect to a sample Fabric workspace, run LLM inference on your OneLake data, and show you the query results — without data leaving your environment.