--- title: "Claude and OpenAI Enterprise Setup · Globalmeta" description: "We set up Claude and ChatGPT as a secure, governed workspace your teams actually use: access, connections to company data, use cases, training and ongoing operation." url: https://globalmeta.net/en/services/claude-and-openai-enterprise-setup language: en alternate_tr: https://globalmeta.net/hizmetler/claude-ve-openai-kurumsal-kurulum date_modified: 2026-11-07 publisher: Globalmeta usage: "Content may be quoted, cited and used for AI training and answers with attribution to globalmeta.net." --- Services / Claude and OpenAI Enterprise Setup # Claude and OpenAI Enterprise Setup We turn Claude and ChatGPT from a tool a few people try into a secure, measurable workspace your teams use every day. You buy the licenses from Anthropic or OpenAI; we handle the setup, the connection to company data, the use cases, the training and the operation. [Book a setup call](mailto:hello@globalmeta.net?subject=Claude%20and%20OpenAI%20setup%20call) ## Technology partnerships ## A license is not a setup When enterprise licenses go live, teams are left with a chat window. Who sees which data, how company documents are connected, which work the tool should do and how usage is measured: if these stay open, the investment stays with a few early users. We deliver the setup together with the answers. ## What we set up ### Workspace and access Enterprise account, users and roles, single sign-on (SSO, where the plan supports it), team and project spaces, admin settings. ### Secure connection to company data Document stores, internal systems and business apps through MCP and official connectors, scoped by permission. Which data reaches the model is agreed in writing during discovery. ### Use cases The tasks that create the most value per department, each with ready instructions, projects and templates. ### Security and governance Usage policy, data classification, personal data masking, logging and audit, rules aligned with KVKK, GDPR and your own policies. Our information security management system is ISO/IEC 27001:2022 certified. ### Training and adoption Role-based training, internal champions, usage tracking and feedback in the first weeks. ### Operation Monthly support after setup: new use cases, new connections, usage reports and continuous improvement. ## AI that answers from your company knowledge: RAG AI only really pays off when it knows your company. We connect Claude and ChatGPT to your documents and internal systems, so your teams get answers from your company's current knowledge, not from the general internet. The method behind this is called RAG (retrieval-augmented generation). ### What is it? The method that makes AI check your own documents before it answers. Think of an open-book exam: the answer comes from your company's own source, not from memory. ### What does it do? Your people stop hunting for the right document and simply ask: leave policy, purchasing steps, product details, proposal preparation. The answer comes right away, from your company's own knowledge. ### Why it matters to enterprises Answers rest on your current documents; when something changes, updating the document is enough. We build it for you so that everyone sees only what they are authorised to see, and every answer shows which document it came from. If the answer is not in your company knowledge, the assistant does not make one up; it hands the work to your team. [Technical definition of RAG in the Glossary](https://globalmeta.net/en/glossary/retrieval-augmented-generation) Use case · TEAM-SI ## The AI team Globalmeta runs its own work on It is possible to run many pieces of work at once, traceably, with a single person's approval. At Globalmeta we do this every day in our own work: AI agents we built with Claude handle commercial, creative, technology, finance and legal work together, and every critical step moves forward only with human approval. Below we show how this setup works, using our own example. ### What is it? An AI team with clear roles. At the top sits a single person who approves; below are the coordination and lead agents who distribute the work; at the base are specialist agents who handle client, product and support work. Every agent knows its own job. ### How does it work? Work reaches the right agent through a task card and comes back as a written delivery. Each agent records its decisions in its own log, so the next day it starts from the record, not from memory. Every critical step, such as going live, spending or writing to the outside world, moves forward only with human approval. ### What does it do? One leader runs many pieces of work at once without losing control. Who did what, with which approval, is always on record, and any risk is raised up the line as soon as it appears. Each task is done with the AI model that fits its nature and its cost. ### Example architecture Three layers wrapped in shared rules: the human who approves, the lead agents who distribute the work and the specialist agents who do it. The operating rules are the same for everyone; external systems such as the code repository, publishing infrastructure and email are reached only through an approval gate. **A real example**When it turned out that an internal system scheduled for shutdown was in use by another team, the lead agent stopped the work the same day, the developer agent rebuilt the system, and every live step went ahead one by one with human approval. If you are considering a way of working with AI agents for your organisation, we can design it with you on the same principles. ## Who it is for - Companies that have bought, or decided to buy, Claude or ChatGPT enterprise licenses - Companies with scattered AI use that want one secure setup - Teams working with sensitive data that need clear access and audit rules - Leaders who want AI past the pilot stage and into daily work ## Model-independent by design We can set up Claude and ChatGPT together or separately, with access through direct APIs, Amazon Bedrock, Azure or Google Cloud Vertex AI as the need requires. The setup is not locked to one vendor. ## How we work ### Discovery Typically 2–3 weeks. Users, priority work, data sources and security rules. Output: setup plan and success metrics. ### Setup and first use cases Typically weeks 4–6. ### Controlled rollout Typically 4–8 weeks. With real users, measured and refined. ### Operation Monthly support and new use cases. At the end of the setup we hand you a handoff map: which work the assistant finishes on its own, the moment it passes the work to your team, and how that handoff happens, on a single page. In the months that follow we measure these handoffs together and shrink the gap the assistant leaves, month by month. ## Works with our own tools Globalmeta's [hubApps](https://globalmeta.net/en/hubapps) products connect to Claude. With [shareHub](https://globalmeta.net/en/hubapps#sharehub), for example, a proposal or report prepared in Claude becomes an access-controlled, updatable link in one step. ## Frequently Asked Questions **Do we buy the licenses from you?** No. Claude user licenses are sold at Anthropic's prices and ChatGPT user licenses at OpenAI's. We support the purchase; our fee is for setup and operation. **Is our data used to train the models?** On enterprise plans, submitted data is not used for training by default (provider enterprise terms). We agree in writing which data connects to which tool and add masking and access limits for sensitive data. **What happens when our information changes?** You update the document, and the assistant starts answering with the new information. There is no need to retrain the AI or rebuild anything. To take a document out of use, simply remove it. **Claude or ChatGPT?** It depends on the work. In discovery we test your teams' tasks on both and recommend; setting up both is possible. **How long does it take?** Discovery typically 2–3 weeks, setup with first use cases by weeks 4–6, controlled rollout 4–8 weeks. The exact plan is in the proposal after discovery. **How is pricing set?** Discovery is fixed scope, setup is project-based, operation is a monthly service. Licenses and model usage are paid to the provider separately. **Do the AI agents make decisions on their own?** No. The agents prepare, research and recommend; critical steps such as going live, spending or writing to a customer go ahead only with the written approval of the authorised person. This rule is not left to choice; it is enforced by approval gates built into the setup. Related service - [AI-Native System Design and Solutions](https://globalmeta.net/en/services/ai-native-system-design-and-solutions): Related service · AI products that work with company data, RAG-based knowledge systems and AI agents.