Private AI architecture
A practical architecture for models, data, permissions, retrieval, tools, logging, and human review.
Custom AI solutions
Custom AI solutions built around your data and workflow.
MPG ONE designs AI systems around the way your organization actually works: your data, permissions, teams, tools, approval rules, public responsibilities, and growth goals.
Workflow-specific tools
AI workflows designed around the tasks that matter most to your team, department, or customer experience.
Search and retrieval systems
AI systems that help people find, understand, and use approved internal knowledge.
AI launch support
Training, documentation, measurement, and improvement cycles so the system is adopted, not abandoned.
Use cases
Where this service fits.
Use this page to match a real business need with the right kind of MPG ONE support, from early planning to managed execution.
- Private assistant for leadership or operations
- Knowledge retrieval for policies, manuals, and archives
- AI reporting across teams and campaigns
- Workflow automation with human approvals
- Custom dashboards powered by AI summaries
- AI integration with existing software and processes
Operating model
How the work moves from idea to system.
Understand the operating reality
We study the current workflow, data shape, user roles, risk points, and the outcome the system has to improve.
Choose the right architecture
We select the model approach, data layer, integration path, access rules, and evaluation method.
Build the useful version
We build the smallest version that can prove value with real users and real tasks.
Expand carefully
We add workflows, improve reliability, connect systems, and support adoption once the core works.
Deliverables
What you can expect to receive.
- Custom AI roadmap
- Architecture and integration plan
- Data and permissions map
- Prototype workflow
- Testing and evaluation plan
- Adoption and improvement plan
FAQ
Questions people ask before they start.
What makes a custom AI solution different?
A custom AI solution is designed around your actual workflow, data, users, permissions, and outcomes instead of being a generic chatbot or template.
Can a custom AI solution stay private?
Yes. Privacy depends on architecture, data handling, vendor choices, permissions, and deployment model, all of which should be designed before launch.
Where should we start?
Start with one workflow where better retrieval, automation, or decision support would save time or improve quality. Prove value there before expanding.
Custom AI solutions