Defined data boundaries
Understand where information travels and which services can access it.
Trusted and Supported By
Make control part of the design.
Bring AI inside your data boundaries.
Controlled access
Connect AI capability to the permissions and responsibilities of your users.
Operational visibility
Plan evaluation, monitoring, maintenance, and ownership alongside deployment.
Architecture shaped by your requirements.
Choose an environment around your infrastructure and data constraints. Compare on-premises, private-cloud, and hybrid options with the work your team needs to support.
- Review infrastructure and data boundaries
- Compare deployment options and tradeoffs
- Clarify capacity and operational requirements
Make approved company information available to authorized users. Shape retrieval around the sources, access rules, and source visibility the workflow needs.
- Identify approved knowledge sources
- Plan retrieval and source references
- Respect existing information access boundaries
Define who can use the environment and who is responsible for administering it. Connect user access to the permissions and responsibilities already present in your organization.
- Map user roles and access needs
- Define administrative responsibilities
- Plan identity connections and permission checks
Plan for operation alongside deployment. Establish the evaluation, logging, maintenance, and handover practices needed to understand behavior and support the environment.
- Evaluate behavior on representative tasks
- Agree on logging and monitoring requirements
- Prepare maintenance ownership and handover
Deployment architecture
Choose an environment around your infrastructure and data constraints. Compare on-premises, private-cloud, and hybrid options with the work your team needs to support.
- Review infrastructure and data boundaries
- Compare deployment options and tradeoffs
- Clarify capacity and operational requirements
Knowledge connections
Make approved company information available to authorized users. Shape retrieval around the sources, access rules, and source visibility the workflow needs.
- Identify approved knowledge sources
- Plan retrieval and source references
- Respect existing information access boundaries
Identity and permissions
Define who can use the environment and who is responsible for administering it. Connect user access to the permissions and responsibilities already present in your organization.
- Map user roles and access needs
- Define administrative responsibilities
- Plan identity connections and permission checks
Evaluation and operations
Plan for operation alongside deployment. Establish the evaluation, logging, maintenance, and handover practices needed to understand behavior and support the environment.
- Evaluate behavior on representative tasks
- Agree on logging and monitoring requirements
- Prepare maintenance ownership and handover
See where it could work.
Internal knowledge assistant
Help authorized staff find information in approved company documents.
Controlled document processing
Extract and summarize information within an agreed environment.
Private AI workspace
Provide a defined place for teams to use approved models and workflows.
Before we begin.
Does private AI mean on-premises?
It can, but the appropriate setup depends on your infrastructure and requirements.
Does private deployment guarantee security or compliance?
Deployment is one part of the solution. Security and compliance also depend on configuration, processes, and ongoing operation.
Can it connect to existing systems?
Integration depends on available interfaces, permissions, and the selected architecture.
Solving the problems that move the business.
Define the right environment for your AI.
Tell us your data constraints and the work your team needs to support.
Discuss your project