OpenAI partner network

OpenAI solutions for the enterprise

From ChatGPT Enterprise to the API and agents, we deploy the OpenAI ecosystem in your organisation — with the security and governance your sector demands.

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Use cases

Where OpenAI models earn their keep

Six functions where we deploy OpenAI — from finance to software engineering, always governed.

Finance

Variance analysis, executive summaries and assisted controls over accounting flows — with source traceability and systematic human validation.

Human resources

Job posts, interview summaries, answers to internal policy questions — inside a governed workspace, not on personal accounts.

Customer support

Reply assistants wired to your knowledge base, sourced drafts for advisors and controlled escalation to a human.

Sales & marketing

Meeting prep, proposal personalisation and multichannel content built from your product references.

Legal

Preliminary contract review, clause comparison and assisted regulatory watch — the lawyer keeps the decision, the AI prepares the file.

Software engineering

Codex and the OpenAI API to speed up code review, tests, migrations and technical documentation inside your existing pipelines.

Looking for a promotion? Use our ChatGPT Business discount eligibility page. A request is free, but it does not guarantee a code, discount or activation.

FAQ

Frequently asked

What is the difference between ChatGPT Enterprise and Business?

The choice depends on required administration, usage, security and contractual features, not just organisation size. We verify the current features and terms of both offers against your requirements before recommending a plan.

Is our data used to train OpenAI's models?

Not by default: on ChatGPT Enterprise, ChatGPT Business and the OpenAI API, your content is not used to train the models. We document these commitments in your compliance file, configure retention controls and back it all with a clear internal usage policy.

Should we use the OpenAI API or ChatGPT Enterprise?

They serve different needs. A ChatGPT workspace equips people for day-to-day work; the API supports custom applications and integrations. The project may combine them, but each needs its own access, cost and data-handling assessment.

How long does a ChatGPT Enterprise rollout take?

The schedule depends on procurement, account configuration, data access and the selected workflows. We agree a phased rollout with training and acceptance criteria after scoping, then track adoption and useful outcomes.

Choose the workspace and the integration separately

Equipping employees with a ChatGPT workspace and building an application with the OpenAI API are different projects. The first concerns accounts, permitted use, administration and adoption. The second requires software engineering: identity, data access, tool permissions, evaluation and operating costs.

We scope the task before recommending an offer. The assessment records user groups, information sensitivity, existing Microsoft or other cloud infrastructure, integration requirements and procurement constraints. Features, retention options and contractual commitments must be checked for the actual plan and deployment at the time of purchase.

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Connect ChatGPT to business workflows with MCP

A useful integration should answer a specific operational question or prepare a clearly defined action. We first inspect the underlying ERP or CRM interface, then expose the approved operation through an API or an MCP server supported by the selected client.

The connector checks identity and permissions independently of the model's instructions. A request to prepare a quote is not permission to issue it. For consequential writes, the workflow identifies the target and proposed content, asks for approval and checks the recorded result before reporting completion.

Codex for development teams

A coding assistant needs a reproducible project environment, clear instructions and a way to verify changes. We help teams define a pilot around bounded tasks such as a regression test, a documented bug or an isolated refactoring. Repository access and command permissions remain constrained to the approved work.

Assessment includes review effort, test quality and defects discovered after generation. A generated patch is not a deployment. The team retains control of merging, secrets, customer data and production actions, with the same delivery gates used for other code changes.

Claude Code and Codex workflows

From initial assessment to operational handover

The delivery plan names the pilot scope, owners, evaluation material and acceptance criteria. We check the behaviour on incomplete questions, missing documents, unauthorised users and unavailable dependencies. Costs are measured against the actual workload rather than extrapolated from a polished demonstration.

The handover records configuration, access roles, the models and clients tested, incident procedures and the scope of ongoing support. Your organisation should know how to revoke access, pause an integration and evaluate a change before making it available to more teams.

Credentials & badges