ChatGPT Enterprise Training and OpenAI Consulting
ChatGPT Enterprise Training for Teams, Builders and Developers
Move your people from personal ChatGPT habits to a company workspace you can defend: shared GPTs with owners, projects and files used well, a one-page safe-use policy, and API advice for the developers going further.
ChatGPT Enterprise training from Kriv AI moves a workforce from scattered personal use into one governed company workspace: role sessions built on projects and files from people's own work, custom GPTs that each have an owner, and a short safe-use policy. For developers we add OpenAI API consulting, and because we work across models, we say plainly which workloads belong on which one.
workspace rollout
ChatGPT Enterprise Training Begins With the Workspace Rollout
When a company buys a ChatGPT workspace, the hard part is rarely introducing ChatGPT. Some staff may already use it on personal accounts, with their own habits about what they paste in and what they check. The rollout has to move that work into the company workspace and change those habits at the same time.
So our ChatGPT Enterprise training starts with three decisions made with your IT and compliance owners before anyone is trained. First, what happens to personal-account use once the workspace exists: whether it is allowed for non-sensitive work, and what must move across. Second, what your agreement with OpenAI and your workspace settings actually say about data handling, retention and administration. We read those with you; we do not summarize them from marketing pages. Third, who may create and share custom GPTs, and who may connect them to company data.
One honest note before you read further: we do not yet have a named ChatGPT client story to show you, and we would rather tell you that here than at the end of the page.
Who this is for
Organizations rolling out ChatGPT Enterprise or another OpenAI business workspace that has to stand up to compliance, privacy or risk review, especially in healthcare, life sciences, financial services and insurance. It also fits engineering teams starting on the OpenAI API who want design review before they build. It is not for individuals looking for a personal ChatGPT course.
openai consulting
OpenAI Consulting for API Builders
Some work outgrows the chat interface: it needs to read internal systems, run at volume, or leave an audit trail. Our OpenAI consulting is for the engineering and data teams building that work on the OpenAI API.
The work is design and review, delivered as two 3-hour technical sessions followed by review of your build. We help define the single task the model is responsible for, build an evaluation set before the code gets large, decide where a person must approve an action, and set up logging so a risk or audit team can see what the system did and why. For regulated clients, we write that documentation to the policy and frameworks you already answer to, such as SR 26-2 or HIPAA.
This is also where ChatGPT consulting that knows only one vendor goes wrong. Model choice is a design decision, and we treat it as one.
custom gpts
Custom GPTs With an Owner Record
Custom GPTs are easy to make, so a workspace can fill with dozens of them, each built by one person, some answering from files nobody has checked in months. Our custom GPT lab is two 3-hour sessions on use cases the business has approved, and every GPT leaves with a written owner record.
| What it records | Why it matters | |
|---|---|---|
| Owner and backup owner | Two named people, by role as well as name. | The GPT survives its builder changing jobs. |
| Purpose and refusals | What it answers, and what it must decline or hand to a person. | Users know its limits; reviewers can test against them. |
| Knowledge files | Each file, its source system and the date it was last checked. | Stale files produce confident wrong answers. |
| Sharing scope | Who can use it, and whether it can reach any connected company data. | Keeps a team GPT from becoming a company-wide one by accident. |
| Test set and review date | Ten to twenty questions with expected answers, rerun on every change and at each review. | Changes are checked, not assumed. |
employee sessions
ChatGPT Training for Employees, Built on Projects and Files
Instead of one session per job title, our employee sessions are organized around the ways people actually work in ChatGPT. Each group brings real material, and each session ends with something they keep. Formats are proposals; your plan's features are confirmed in discovery.
1. Briefing and checking (everyone, 90 minutes)
How to give ChatGPT context, how to check what comes back, and what the safe-use policy means in practice. Participants leave with three tested prompts for their own work.
2. Projects for ongoing work (team leads and analysts, 2 hours)
Setting up a project for a recurring piece of work, deciding which files belong in it, and keeping it current.
3. Working with files and data (finance, operations, 2 hours)
Analyzing spreadsheets and documents, with a fixed habit of reconciling every figure to the source file.
4. Research and drafting with sources (sales, HR, compliance, 2 hours)
Researching, drafting and reviewing, with a rule that anything leaving the team cites where it came from.
5. Regulated-data clinic (any team handling sensitive data, 1 hour)
Worked examples of what can and cannot go into the workspace under your agreement and policy, using redacted versions of real cases.
safe use policy
A One-Page Safe-Use Policy
A policy nobody reads protects nobody. We write a single page with your compliance and IT owners, and teach it inside every session. A sample table of contents:
1. Where to work
Company workspace for company work, and what that means for personal accounts.
2. Data you never enter
Named data classes, such as protected health information or customer financial data, unless legal and compliance have confirmed your agreement and controls allow it.
3. Checking before sharing
Which outputs need human review before they leave the team.
4. Building and sharing GPTs
Who may create, share and connect them, and the owner record each needs.
5. Recording use
Where your own procedures require it, how use of ChatGPT is noted.
6. Who to ask
A named contact for questions and for reporting a mistake early.
model choice
An OpenAI Partner That Recommends by Workload
Kriv AI holds OpenAI Partner Network · Select tier. We do not yet have a public directory link for it, so verification is available on request.
We are deliberately multi-model. Kriv AI is also a Claude Partner Network, Select partner · Services Track, and trains teams on other AI platforms too. In practice that means we will tell you when a workload suits ChatGPT, when it suits a different model, and when it matters more which model fits your cloud, contracts and data rules than which one tops a benchmark. Many organizations run more than one model; what should be single is the governance.
Our most fully documented training delivery is Claude Code training, not ChatGPT work: 12 live training sessions, 26 training documents and 5 role-specific starter kits in 3 weeks.
how it runs
How a ChatGPT Engagement Runs
It starts with a short discovery call about your workspace status, which teams are in scope, whether developers are involved, and what your reviewers need. Next comes a working session on the three rollout decisions and the safe-use policy, and we collect real material from each group. Then the sessions, GPT labs and, where needed, API sessions run, with GPTs reviewed against their owner records before they are shared. You keep the policy, owner records, prompts and session materials, plus a short readout of what changed and what to do next.
get started
Get Started
ChatGPT Enterprise training and OpenAI consulting are scoped and priced after a short discovery call, because the mix of sessions, labs, policy work and API review depends on your size and starting point. Our pricing page explains how we scope engagements.
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Straight answers
Frequently asked questions about ChatGPT Enterprise Training for Teams, Builders and Developers
Our employees already use ChatGPT. Do they still need training?
Usually the habits they formed on their own are the issue. People who taught themselves often skip checking, paste data they should not, or never set up projects and files well. Training on their own material, inside the company workspace and alongside a clear policy, turns individual habits into practices the organization can explain to an auditor.
What should happen to personal ChatGPT accounts after we roll out a workspace?
Decide it explicitly and write it down. Some organizations allow personal accounts for non-sensitive work; others require all work-related use in the company workspace. Either way, the policy should name the data that never goes into a personal account, and the rollout should help people move ongoing work across rather than abandon it.
Can ChatGPT be used with patient or customer financial data?
That depends on your agreement with OpenAI, your workspace configuration and your own compliance obligations, not on training. Our default policy keeps protected health information and customer financial data out unless your legal and compliance teams confirm the agreement and controls allow it. We help you document that decision either way.
Is Kriv AI an OpenAI partner?
Yes. Kriv AI holds OpenAI Partner Network · Select tier. We do not yet have a public directory link for it, so verification is available on request. Kriv AI is also a Claude Partner Network, Select partner · Services Track, which is why we describe ourselves as a multi-model firm and recommend models by workload.
When should we build on the OpenAI API instead of a custom GPT?
When the workflow needs to read or write internal systems, run at volume without someone in a chat window, or leave a complete record of what happened for audit. Custom GPTs suit shared, conversational help for a team. Our OpenAI consulting helps you decide, then design the evaluation, approval points and logging the API version needs.
How much does ChatGPT Enterprise training cost?
We do not publish a set price for ChatGPT training or OpenAI consulting. Each engagement is scoped and priced after a short discovery call, because the cost depends on how many groups you are training, the size of the GPT builder group, whether API work is in scope, and how much policy work is already done.
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Bring your requirements to a working session with the person who'll actually deliver.
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