Private ChatGPT for business
Plan a controlled AI assistant around approved company knowledge, access rules, and internal workflows so teams can ask better questions without relying on a generic public chat flow.
What does the onboarding playbook say about enterprise data access?
Enterprise workspaces require approved sources, role mapping, and a documented escalation path before launch.
Source: Client Onboarding Playbook v4 · pg 3
Why teams use it
Deployed around your infrastructure and access model. Prompts and documents are scoped around approved systems, not generic public workflows.
Answers cite the playbooks, contracts, policies, and docs you approve — with sources shown so teams can verify instead of guessing.
Role-based channels per team: sales sees sales, finance sees finance. Shared where useful, walled where it matters.
Data boundaries
Private ChatGPT for business is a planning and implementation engagement, not a generic chatbot install. We define sources, access, escalation, and ownership before the assistant reaches employees.
Read the Private GPT case study →We connect the systems and documents you sign off on — nothing is ingested by default.
Permissions mirror your org: by role, team, or individual. Audit trails are planned into the workflow.
Deployment is scoped to the security review: private cloud or your own environment where required.
The assistant, its knowledge base, and its configuration are deliverables — not a black-box subscription you rent.
In production
“We needed an AI platform that understood our business, remembered our clients, and kept our data private. Private GPT delivered exactly that.”
FAQ
A private GPT is a ChatGPT-style assistant that belongs to your company. It answers from the documents, policies and procedures you approve, runs under your own access controls and data boundaries, and is scoped around your infrastructure instead of sending employees to generic public chat tools.
K3, a managed IT services provider, runs a private GPT workspace we built: GPT, Claude and other models in one place, memory across clients and projects, and custom workflows, inside data boundaries K3 approves. The full story is in our Private GPT case study.
Public chat tools are generic and may not match your internal knowledge, permissions, or governance needs. A private AI assistant is scoped around approved company sources, role-based access, auditability, and business-specific answers.
Private ChatGPT pricing depends on infrastructure requirements, number of users, data sources, integrations, and support model. We scope the right architecture and business case during discovery.
It can be scoped to approved document management systems, intranets, knowledge bases, wikis, and file storage. Discovery defines which sources, permissions, and answer-review rules are appropriate before launch.
Deployment timing depends on identity provider access, data-source readiness, security review, and integration complexity. We define the rollout plan after discovery and technical scoping.
Related: AI consulting · AI pricing guide · Book a call
Private AI, scoped first
Bring a sample knowledge workflow, and we will show how sources, permissions, and escalation rules would be scoped before launch.