Private AI for Confidential Work
Draft, summarize, and research approved files on infrastructure your organization controls, with managed access, activity logging, and ongoing support.
Private AI, built for confidential work.
Every deployment answers five practical questions: where it runs, which files it can reach, who can use it, what gets logged, and who keeps it working.
Dedicated deployment
The system runs on dedicated hardware in your office or in a private cloud environment. Prompts and files stay inside that deployment instead of being sent to a public AI service.
Confidential document work
Use approved files to draft, summarize, compare, and search. Access is tied to the identity and permissions already used to protect those files.
Reviewable activity
Prompts, responses, and administrative changes are logged so use can be reviewed during client, insurance, or compliance work.
Controls that match the work
Access groups, retention settings, and model behaviour are documented and configured around the organization's confidentiality requirements.
Ongoing management
Teclara handles model updates, monitoring, tuning, and support after launch. The service also includes operating guidance for the people responsible internally.
What changes when the work is confidential.
Putting client or regulated data into an AI service is a data-handling decision, not just a software choice. You need to know where prompts and files are processed, how long they are retained, whether they are used to train a model, who can access them, and what evidence is available later. The answers vary between consumer tools and business plans, so policy alone is not enough.
Private AI gives you a defined environment. We deploy a model that runs on dedicated hardware in your office or in a private cloud. Staff sign in with your existing identity, access groups determine who can use the system and which approved files it can reach, and prompts and responses are logged. Retention and operating limits are documented before the system goes live.
Teclara designs and validates the deployment, then stays responsible for model updates, monitoring, tuning, and support. This is an ongoing managed service, not a server handed over after installation.
Private AI can run as a standalone service. It also pairs with Managed Security & Compliance when the surrounding accounts, devices, and cloud environment also need ongoing security coverage.
Is Private AI right for you?
Use this when staff need AI to work with confidential documents and public services sit outside your approved data-handling boundaries.
Your contracts or policies limit where sensitive data can be processed
client, legal, financial, or operational information needs a defined boundary
Staff are already using AI for work
you need an approved alternative with clear access and data-handling rules
You want AI to work with files the organization already holds
drafting, summarization, comparison, and search are the practical use cases
You need a reviewable record of use
client, insurance, or compliance work may require evidence later
You need control over where the system runs
dedicated hardware and private cloud are both available
Frequently asked questions.
What does the Private AI service include?
Design, deployment, and ongoing management of a private AI system: model selection, hosting architecture, a controlled chat interface, sign-in and access groups, activity logging, and documented operating limits. The system supports drafting, summarization, comparison, and research over approved files. After launch, Teclara handles model updates, monitoring, tuning, and support.
What infrastructure does this run on?
There are two options: dedicated hardware in your office, which you can supply or Teclara can procure, or a private cloud environment with rented processing capacity. We confirm the workload, size the environment, and recommend a path during the scope review.
How does our client data stay private?
Prompts and selected files are processed inside the private deployment rather than sent to a public AI service. Sign-in and access groups limit who can use the system, and prompts and responses are logged for review. The access, retention, and operating rules are documented for each deployment.
Which models and platforms do you work with?
We use models that can run inside your private environment and select them for the work you need. The system can use your existing Microsoft 365 or Google Workspace identity for sign-in. If the requirements point outside what we support, we will say so during discovery.
How does an engagement start?
We start by reviewing the data involved, the target users, the intended workflows, the infrastructure options, and the evidence you need to retain. Teclara then designs the architecture, builds the deployment, and validates it with your team. Ongoing management begins after launch.
Keep confidential work inside a controlled AI environment.
We will review the workflows, data sensitivity, user groups, and infrastructure requirements, then tell you whether a private deployment is the right path.