Enterprise AI.
Your infrastructure.
Your data.
DMAG AI helps organizations deploy private AI assistants, enterprise RAG and secure AI infrastructure inside environments they control—without depending on public AI services for sensitive workloads.
Private AI Environment
Illustrative deployment
AI Gateway
Policy + authentication
Local Model Runtime
Private inference
Enterprise RAG
Permission-aware retrieval
Knowledge Layer
Documents + databases
Monitoring
Health + usage
Platform
Private AI without building an AI platform from scratch.
DMAG AI brings together the infrastructure, retrieval, security and operational layers needed to deliver useful enterprise AI while keeping deployment control inside the organization.
Private AI Platform
Deploy enterprise AI services within infrastructure you control.
Enterprise RAG
Search internal documents, policies, manuals, contracts and knowledge with citations.
Security by Design
Identity, permissions, auditability and deployment controls built into the architecture.
Hardware-Aware Deployment
Right-size compute, memory and model capacity for the workload instead of forcing one hardware configuration.
Operational Visibility
Monitor resource usage, latency, ingestion health and model availability.
Expandable Architecture
Start with private knowledge search and grow into document AI, workflows and enterprise agents.
Architecture
Designed around control, not data export.
The architecture can be deployed for organizations that need local models, local retrieval, internal identity integration and tightly controlled network boundaries.
Your Organization
Employees, applications and internal business workflows.
DMAG AI Gateway
Authentication, policy enforcement, routing and auditability.
Local AI Models
Models run inside your approved infrastructure.
Private RAG
Permission-aware retrieval across company knowledge.
Enterprise Data
Files, databases, SOPs, contracts and internal systems.
Local-Only Control
Designed for deployments where sensitive data stays in your environment.
Industries
Built for organizations where data control matters.
Manufacturing
Engineering
Legal
Financial Services
Healthcare Operations
Government Contractors
Approach
Start small. Prove value. Scale deliberately.
The first engagement should solve one high-value use case well, then expand based on measured demand.
Assess
Understand data, users, infrastructure, security requirements and high-value AI use cases.
Design
Define the model, RAG, identity, storage and compute architecture for the environment.
Pilot
Deploy a focused private AI use case and validate quality, security and usability.
Scale
Expand users, knowledge sources, workloads and hardware capacity as demand grows.
Start a conversation
Exploring private enterprise AI?
Talk with DMAG AI about your use case, data environment, infrastructure constraints and security requirements.