Why companies are looking beyond ChatGPT Enterprise.

ChatGPT Enterprise launched in August 2023 as OpenAI's answer to enterprise data concerns. It promised no training on business data, SSO, and admin controls. For many companies, it seemed like the solution to the shadow AI problem — the 77% of employees already pasting company data into the free version of ChatGPT.

But as European regulatory frameworks matured, a more nuanced picture emerged. Italy's Garante fined OpenAI €15 million for GDPR violations. The EU AI Act introduced new transparency and compliance requirements. Samsung's internal code leak through ChatGPT became a cautionary tale for IP-sensitive organisations.

The core question shifted: is "we don't train on your data" enough, when your data still crosses the Atlantic to be processed?

This comparison lays out the facts. We built ORCA, so we're transparent about our perspective — but we also recognise that ChatGPT Enterprise is a strong product. The right choice depends on your specific requirements.

Feature comparison at a glance.

This table covers the dimensions that matter most for European businesses evaluating enterprise AI. We've aimed to be fair and accurate about both solutions.

Data sovereignty: the fundamental difference.

This is where the two approaches diverge most sharply, and it deserves careful analysis.

ChatGPT Enterprise processes all conversations on OpenAI's infrastructure, which runs on Microsoft Azure — primarily in US data centres. OpenAI offers a Data Processing Agreement (DPA) and relies on Standard Contractual Clauses (SCCs) to legitimise the EU-to-US data transfer under GDPR. Since the Schrems II ruling invalidated the EU-US Privacy Shield, SCCs have been under increasing scrutiny. The new EU-US Data Privacy Framework provides some relief, but its long-term stability remains uncertain.

For companies in regulated industries — healthcare, finance, legal, public administration — the risk assessment around transatlantic data transfers is complex and ongoing. Even if OpenAI's promises are honoured today, the regulatory landscape can shift.

ORCA eliminates this complexity entirely. Your data is processed on your own servers or in EU-based cloud infrastructure. There is no international data transfer to evaluate, no DPA to negotiate, no regulatory uncertainty to monitor. The GDPR analysis is straightforward: data stays within the EU, under your control.

This isn't a theoretical advantage. Italy's Garante — the data protection authority that fined OpenAI €15 million in 2024 — has repeatedly emphasised that data localisation within the EU is the most robust approach to GDPR compliance for AI systems.

Pricing: per-seat vs fixed infrastructure.

ChatGPT Enterprise uses a per-seat pricing model at approximately $60 per user per month, with annual commitment required. This means your AI budget scales linearly with adoption — the more successful the deployment, the more expensive it becomes.

For a 50-person team, that's roughly $36,000 per year. For 200 users, $144,000. And these costs are recurring, with pricing subject to OpenAI's decisions.

ORCA uses a fundamentally different model. You invest in infrastructure — either on-premise hardware or EU cloud resources — and that infrastructure serves unlimited users. The cost curve flattens as you scale. For organisations planning broad AI adoption across the workforce, this creates significant long-term savings.

The trade-off is that ORCA requires upfront infrastructure investment, while ChatGPT Enterprise is purely operational expenditure. For small teams (under 15-20 users), ChatGPT Enterprise's per-seat model may actually be more economical. We're transparent about this because choosing the wrong model for your scale wastes money regardless of which product you pick.

Model flexibility: one vendor vs the open ecosystem.

ChatGPT Enterprise gives you access to OpenAI's model family: GPT-4o, GPT-4, and GPT-3.5 Turbo. These are excellent models — GPT-4o in particular is highly capable across a wide range of tasks. The limitation is that you're locked into one provider's roadmap, pricing, and architectural decisions.

ORCA runs on the PRISMA stack, which supports multiple model families: Mistral (French, strong for European languages), LLaMA (Meta), DeepSeek (strong reasoning), Qwen (multilingual), and others. You can select different models for different use cases — a small, fast model for simple queries and a large, powerful model for complex analysis.

This flexibility has practical implications. When a new open-source model surpasses the current leader (which happens regularly — the open-source AI ecosystem moves rapidly), ORCA can adopt it. You're not waiting for one vendor to innovate; you benefit from the entire global AI research community.

It also means you can optimise cost-to-performance. A 7B parameter model running on modest hardware handles 80% of typical enterprise queries at a fraction of the cost of routing everything through GPT-4.

Document intelligence: RAG done right.

Both ORCA and ChatGPT Enterprise support document upload and question-answering. The implementations differ significantly.

ChatGPT Enterprise allows file uploads and can reference them in conversation. It's convenient and works well for simple use cases. However, you have limited control over how documents are indexed, chunked, and retrieved. The retrieval pipeline is a black box managed by OpenAI.

ORCA's RAG (Retrieval-Augmented Generation) system is built from the ground up for enterprise document intelligence. Documents are indexed locally using configurable chunking strategies optimised for your content type. Every answer includes source citations — the specific document, page, and paragraph where the information was found. This traceability is essential for regulated industries where you need to verify AI-generated answers.

ORCA also connects to your existing document management systems, SharePoint, network drives, and databases. It doesn't require documents to be manually uploaded — it integrates with where your documents already live.

Customisation and integration depth.

ChatGPT Enterprise offers Custom GPTs — pre-configured chatbot personas with specific instructions and knowledge. It's a good feature for creating departmental assistants. The API provides additional flexibility for developers.

ORCA goes deeper. Because you control the entire stack, customisation is limited only by your requirements, not by a vendor's feature roadmap:

When to choose what.

We believe in helping you make the right decision, even if that means recommending a competitor. Here's our honest assessment:

Ready to see ORCA in action?

We offer a working pilot on your real data in 2-4 weeks. No PowerPoint presentations — a functional system you can test with your team. Learn more about ORCA or contact us directly.

Frequently asked questions