Private LLM Systems
Right-sized model selection, hardware planning, secure hosting, and operating patterns for local or dedicated private-cloud inference.
Private AI systems
AI that works inside your trust boundary.
Stormhold designs local and private AI systems for organizations that need automation, search, summarization, code assistance, and agent workflows without sending sensitive business data to public cloud models.
Private AI use cases
Internal Search Document Review Secure Agents Code Assistance ReportingControl the data path
Useful AI without uncontrolled leakage.
Private AI is not just a model choice. It requires identity, access control, storage, logging, retention, prompts, data pipelines, and deployment boundaries that match your risk.
01
Data boundary design
Map sensitive records, approved users, model access, retrieval stores, logs, and outputs before workflows are built.
02
Private model architecture
Select local, on-prem, or private-cloud options based on workload, sensitivity, latency, and operational capacity.
03
Security review before launch
Review prompt injection risk, access boundaries, audit trails, and failure modes before the system reaches production.
Internal RAG
Retrieval systems that let staff query policies, SOPs, case files, manuals, records, and training material with access control.
Agent Workflows
Workflow automation for research, document review, intake, reporting, triage, and internal decision support with human review points.
Data Sovereignty
Network, storage, identity, logging, and retention designs that support privacy obligations and make data movement understandable.
AI Threat Review
Review prompt injection, unsafe retrieval, tool permissions, over-broad access, sensitive logging, and model output controls.
Prototype to Production
Move from a useful prototype to a hardened workflow with security requirements, monitoring, and user guidance.
Private AI assessment
Start with one high-value workflow and the data it touches.
Stormhold can map the risk, prototype the workflow, and define the controls needed before broader rollout.
Questions buyers ask
Service-specific FAQ.
Short answers for scoping, privacy, authorization, deliverables, and production safety.
What makes an AI system private?
A private AI system is designed around approved data boundaries, controlled model access, private or local inference, logging decisions, retention rules, and identity controls.
Can private AI use existing company documents?
Yes. Stormhold can design internal RAG and knowledge workflows so staff can query approved documents with access control and auditability.
Does private AI eliminate all data risk?
No. Private AI reduces exposure to public model pipelines, but the workflow still needs security review for access control, prompt injection, unsafe retrieval, logging, and tool permissions.
Can you start with one workflow?
Yes. Stormhold recommends starting with one high-value workflow and the data it touches before broader rollout.
Private AI intake
Start with one workflow and the data it touches.
Stormhold can help scope a private AI pilot around sensitive documents, internal knowledge, agent workflows, or secure code assistance.