Finance
Banking, insurance and fintech.
Support policy search, internal knowledge, compliance review, customer support and analyst workflows without moving regulated data to a public LLM.
Regulated organisations need AI that can be inspected, governed and operated without exposing sensitive data to public cloud providers. LLM Machines brings generative AI inside the control boundary.
The common thread is not one industry. It is sensitive data, audit exposure and a low tolerance for uncontrolled AI processing.
Support policy search, internal knowledge, compliance review, customer support and analyst workflows without moving regulated data to a public LLM.
Summarise contracts, search matters, draft internal memos and inspect citations while keeping privileged material inside the firm perimeter.
Assist staff with internal procedures, research, documentation and support knowledge while respecting strict data handling requirements.
Deploy AI for document search, drafting and internal assistance in environments where sovereignty and auditability are procurement requirements.
Keep operational knowledge, maintenance records and incident workflows inside controlled systems aligned with NIS2-style expectations.
Use private code assistance, repository search and architecture support without sending source code or product plans to third-party AI services.
Private AI needs more than a model. It needs identity, permissions, logs, source grounding and a deployment model security teams can approve.
Users authenticate through enterprise identity. Roles and data permissions limit who can query what, and connector credentials stay in the on-box vault.
RAG grounding, source-aware answers, usage logs and audit trails make it easier to understand what the system did and why.
Start with one sensitive workflow, one team, and a deployment path your security team can inspect.