AUM

AUM runs the entire AI stack on hardware you own. There are no cloud dependencies and no external API calls, so every query stays inside your infrastructure. You can deploy on on-premise servers, inside a private cloud or VPC, on an air-gapped machine with no internet at all, or spread across several local devices. The point is that you keep the infrastructure control, not a vendor.

AUM searches across your documents, folders and private files in seconds, and it holds up when the pile runs into millions of records. It works over the files you already have, whether that's PDFs, contracts, reports or internal notes. That means you stop digging through folders by hand and start asking the AI where a clause or figure lives. The search runs locally, so nothing is uploaded to index it.

You can build a dedicated enterprise AI brain for different teams or processes. A company might train one brain on HR policy, another on standard operating procedures, and a third for a specific department. Each one answers from the knowledge you give it rather than from the open web, which keeps answers on topic and grounded in your own material. That separation also lets you decide who can query which brain.

AUM connects to your business databases and lets you query them in everyday language. Instead of writing SQL or asking an analyst, you ask the question the way you'd ask a colleague and get the result back. It's aimed at people who want to run data analysis and answer hard business questions without being a data specialist. Answers come from your live data, not an outside copy.

AUM can act on your behalf, not just answer questions. Ask it to create documents, draft proposals, send emails or write into Notion, and it does those steps as part of a task. This is what turns the tool from a search box into something that saves real time, since the AI finishes the work instead of handing you instructions. The automation runs against your internal systems.

AUM works with open models such as Mistral, DeepSeek, Llama 3, Mixtral, plus lighter ones like Falcon, Phi-3 and BERT. You pick the model that fits your hardware and use case, and the platform lets you access newer models on your own machines without paying extra for them. The only real requirement is a machine with enough free computing power to run them.

The platform is built around the rules that block cloud AI in regulated work. AUM describes its architecture as aligned with HIPAA, GDPR and SOC 2, with role-based access control so you set granular permissions for who sees what. Because data stays on site, client confidentiality and internal IP stay under your control. This is the feature that usually decides whether a firm can adopt AI at all.