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Self-hosted AI enterprise search runs inside your AWS, Azure, GCP, OpenShift cluster, GovCloud region, or air-gapped environment. That means three things your legal and procurement teams can put in writing: 1️⃣ Data residency. Your documents, embeddings, and query logs never leave the boundary you control. 2️⃣ Permissions that hold across every connected system. If a user can't see a file in SharePoint, they can't surface it in search. Document-level access controls are enforced in real time, across every system in your stack. 3️⃣ AI that doesn't require a compliance exception. Choose whether AI-generated answers call a commercial API or run entirely in your own infrastructure. When your regulations require zero third-party data processing, you can deliver it. See if self-hosted AI search is right for your company 👇

What security reviews reviews rarely surface is a more basic question: at what point does the vendor's infrastructure touch your data? A search platform has to read your documents to index them. Board materials, customer records, Slack conversations, source code. All of it passes through vendor-controlled infrastructure while it is being parsed and processed. A data contract governs what the vendor is permitted to do after that. ❌ It does not change what they had access to during ingestion. For organizations in regulated industries like government, financial services, insurance, and healthcare, that distinction is the whole conversation. Learn more about what makes self-hosted AI search different 👉

At what point does the vendor's infrastructure touch your data? An AI search platform has to read your documents to index them. A data contract governs what the vendor is permitted to do after that. It does not change what they had access to during ingestion. Knowing this gap, CTOs want the following questions answered before legal review: 1️⃣ What infrastructure does our data pass through during indexing? 2️⃣ Who operates that infrastructure? 3️⃣ At what point, if any, does it leave our network? The only way to answer all three cleanly is a deployment where the entire pipeline runs inside your own network: connectors, search index, embedding model, retrieval layer. None of it passes through infrastructure you don't own and operate. That is what we built Atolio to be.

At what point does the vendor's infrastructure touch your data? An AI search platform has to read your documents to index them. A data contract governs what the vendor is permitted to do after that. It does not change what they had access to during ingestion. Knowing this gap, CTOs want the following questions answered before legal review: 1️⃣ What infrastructure does our data pass through during indexing? 2️⃣ Who operates that infrastructure? 3️⃣ At what point, if any, does it leave our network? The only way to answer all three cleanly is a deployment where the entire pipeline runs inside your own network: connectors, search index, embedding model, retrieval layer. None of it passes through infrastructure you don't own and operate. That is what we built Atolio to be.

Self-hosted AI enterprise search runs inside your AWS, Azure, GCP, OpenShift cluster, GovCloud region, or air-gapped environment. That means three things your legal and procurement teams can put in writing: 1️⃣ Data residency. Your documents, embeddings, and query logs never leave the boundary you control. 2️⃣ Permissions that hold across every connected system. If a user can't see a file in SharePoint, they can't surface it in search. Document-level access controls are enforced in real time, across every system in your stack. 3️⃣ AI that doesn't require a compliance exception. Choose whether AI-generated answers call a commercial API or run entirely in your own infrastructure. When your regulations require zero third-party data processing, you can deliver it. See if self-hosted AI search is right for your company 👇