Private AI Workspaces
Turn AI into a governed internal productivity layer on your own knowledge.
Private AI Workspaces covers Internal assistants, secure knowledge search, role-based access, private prompts, controlled model access.
Common use cases
Assess
Understand your environment, goals, and constraints.
Design
Architect the right approach for your requirements and budget.
Source
Procure the right platforms at the right price and availability.
Implement / migrate
Deploy and migrate with engineers, validated and integrated.
Optimize
Tune for performance, cost, and security over time.
Renew / support
Operate, support, and manage renewals as one accountable partner.
Related business challenges
We recommend the right fit for your environment, not a single vendor.
What's included in Private AI Workspaces?
Private AI Workspaces covers Internal assistants, secure knowledge search, role-based access, private prompts, controlled model access. We define the capability, explain where it fits, and clarify the decisions you need to make.
When should we use it?
Turn AI into a governed internal productivity layer on your own knowledge. Typical triggers include refreshes, migrations, consolidation, new projects, security or compliance needs, and renewals.
How does it integrate with our current tools?
We design around your existing environment and vendors - integrating with what you keep and replacing only what no longer fits.
What should we prepare before a meeting?
A short picture of your current environment, goals, timeline, known vendors, and any constraints - we'll guide the rest.
What vendors does TechPower support?
Anthropic, OpenAI, Microsoft, AWS, Google Cloud, Databricks, Snowflake, Weaviate, and more - see Partners. We recommend the right fit for your environment, not a single vendor.
Design a private AI workspace
Talk to an engineer about private ai workspaces, we'll scope the right approach for your environment and timeline.
Design a private AI workspace