Dortana / Private AI
Private AI, Engineered Around Your Business.
Dortana designs, builds and deploys AI environments around enterprise data, workflows and infrastructure.
Private cloud · On-premise · Hybrid
Enterprise data and systems
Private AI intelligence
Models · Retrieval · Guardrails
Business operations
AI Adoption Creates a New Infrastructure Question.
External platforms make advanced models accessible fast. As AI moves into core operations, enterprises also weigh where data is processed, how systems integrate and how usage economics behave at scale.
Dortana determines where each approach makes sense.
External AI
Private AI
Not every workload belongs on private infrastructure. Not every workload belongs on an external API either.
Not Another Enterprise Chatbot.
Private AI is a stack, not a single model. Five layers work together, from raw data to the people using it every day.
Select a layer to see what it does.
The information an organization already holds. Structured records, files and internal systems, in whatever state they exist today.
The Right Model Depends on the Workload.
Dortana does not start from a fixed model. The same request can take different paths once its sensitivity, volume and complexity are known.
Sample request
“Summarize this internal policy document.”
Confidential content stays inside a controlled environment end to end.
We design around requirements, not model ideology.
From Feasibility to Production.
Understand the workload, data environment and technical requirements.
Private AI feasibility and architecture assessment.
Built for Environments Where Control Matters.
Two factors matter more than industry: how sensitive the data is, and how much volume the workload carries.
Compliance workflows
Highly sensitive, lower volume. A strong candidate for private or hybrid architecture.
Highly sensitive, lower volume. A strong candidate for private or hybrid architecture.
Internal knowledge
Moderate sensitivity and volume. Often a hybrid fit depending on the content involved.
Moderate sensitivity and volume. Often a hybrid fit depending on the content involved.
Workflow automation
Sensitive and repetitive. Private inference can pay off once volume is sustained.
Sensitive and repetitive. Private inference can pay off once volume is sustained.
Document processing
High volume, moderate sensitivity. Optimized smaller models fit well here.
High volume, moderate sensitivity. Optimized smaller models fit well here.
Customer operations
High volume, generally lower sensitivity. Often served well externally or hybrid.
High volume, generally lower sensitivity. Often served well externally or hybrid.
Technical knowledge
Lower sensitivity. External or hybrid models are frequently sufficient.
Lower sensitivity. External or hybrid models are frequently sufficient.
Illustrative industry examples
AI Connected to Actual Operations.
Employees ask a question in natural language and get an answer scoped to what they're allowed to see, with its source attached.
Deploy Where Your Requirements Demand.
Dedicated cloud infrastructure controlled around enterprise requirements.
Private AI Should Have a Business Case.
Building private infrastructure because it sounds appealing is not enough on its own. Dortana weighs the real costs against how a workload behaves in production.
The goal isn't replacing external AI everywhere. It's identifying where private architecture creates operational or economic value, and where it doesn't.
Current AI usage
Dortana assessment
Architecture
Outcome
AI Infrastructure Requires More Than a Model.
A model on its own does not make an enterprise AI system. Value comes from connecting intelligence with data, software, infrastructure and the people who use it. Dortana operates across that entire stack.
Start Your Private AI Assessment.
Tell us about your environment. We'll use it to understand whether a private, hybrid or externally hosted architecture may fit your organization.
01 / 06 · Your Organization
Your AI Infrastructure Should Fit Your Business, Not the Other Way Around.
Explore whether a private or hybrid AI architecture fits your organization.