ChatGPT Enterprise is the default first step into AI for many US companies — polished, secure, and familiar. But it is one vendor’s chat assistant, and that single fact shapes what you can build on it later. This is a factual comparison with osFoundry, which describes itself as a “Hybrid AI Orchestration Platform,” to help you decide which fits your goal. Every product fact below is cited; where a figure is not officially published, we say so.
At a glance
| osFoundry | ChatGPT Enterprise | |
|---|---|---|
| Category | Hybrid AI orchestration platform | Chat assistant + connectors |
| Models | Model-agnostic — bring your own providers | OpenAI GPT-5.5 family only |
| Trains on your data | No | No, by default |
| Agents & automation | Built around agents, automations, and apps | ChatGPT agent + Workspace Agents (credit-priced) |
| Replaces other SaaS | Designed to consolidate tools | Primarily augments your stack |
| Pricing transparency | Via dgm: $399 consult, $3,999/mo integration | Not public (contact sales) |
| Vendor lock-in | Low (multi-model) | High (OpenAI) |
What each product actually is
ChatGPT Enterprise is the business tier of ChatGPT: a conversational assistant with admin controls, higher limits, and connectors to your data. In 2026 it runs OpenAI’s GPT-5.5 family, with GPT-5.5 Instant becoming the default model on May 5, 2026. It includes a global admin console, analytics, GPTs, Projects, data analysis, and a growing set of agent features. It is, at its core, a very good assistant that your employees talk to.
osFoundry is a different category. Rather than a chat product, it is an orchestration layer: it runs AI agents, automations, and internal apps from one workspace, across the models and systems you already use, with the explicit aim of consolidating overlapping SaaS tools. The distinction matters because it determines what you can do a year after rollout — give staff a better assistant, or re-platform how work flows through your company.
Models and vendor lock-in
This is the biggest structural difference. ChatGPT Enterprise runs OpenAI’s own models, full stop — there is no documented way to plug in rival vendors’ models such as Claude or Gemini. Standardizing on it means standardizing on OpenAI’s roadmap, pricing, and availability. In a year when model names and capabilities are shifting on a near-monthly cadence, that is a real strategic dependency.
osFoundry takes the opposite approach: it is model-agnostic, so you connect the providers and keys you want and route each task to the model that fits — and switch models without re-platforming when economics or capabilities change. For US companies that want to avoid betting the business on one lab, that flexibility is the headline reason to consider it.
Data, privacy, and compliance
Both products are built for business-grade data protection, and this is an area where ChatGPT Enterprise is strong. OpenAI states it does not train on Enterprise data by default, gives admins control over retention, and removes deleted conversations within 30 days unless legally required. It holds SOC 2 Type 2, ISO/IEC 27001, 27701, and 42001, plus CSA STAR, supports SSO/SAML and SCIM provisioning, encrypts data in transit and at rest, and offers data residency in roughly ten regions, including the US.
osFoundry’s positioning centers on data ownership — keeping your data yours and out of anyone else’s training set. For a regulated US business in healthcare, finance, or legal, the right move with either platform is the same: confirm the current Data Processing Addendum, retention settings, and residency against your specific obligations before rollout. That verification is part of what dgm does during an integration assessment, so you are not taking a marketing page on faith.
Agents and automation
ChatGPT Enterprise has expanded well beyond chat in 2026. It added ChatGPT agent for multi-step web and file tasks, and Workspace Agents — launched April 22, 2026 as the announced successor to custom GPTs — which can be scheduled, shared, and deployed into tools like Slack and Salesforce. Two caveats matter for budgeting and architecture. First, Workspace Agents moved to credit-based pricing on May 6, 2026, so heavy automation adds consumption cost on top of seats. Second, deeper programmatic automation lives in OpenAI’s separate developer products such as AgentKit, billed under API pricing — a different product and a different bill from the Enterprise seat.
osFoundry is built around orchestration from the start: agents, automations, and apps in one workspace, designed to act across your systems rather than being layered onto a chat product. If your primary goal is to automate workflows end to end — not just give employees a smarter chatbot — that architectural difference is the point to weigh most carefully.
Pricing and total cost of ownership
OpenAI does not publish ChatGPT Enterprise pricing; it is negotiated with their sales team. Third-party buyer reports estimate roughly $45–$75 per user per month with a reported ~150-seat annual minimum, but these are not official OpenAI figures — treat them as directional and confirm directly. By contrast, ChatGPT Business is publicly listed at about $20 per seat per month (annual), and agent/automation usage adds consumption costs on top.
The cost conversation differs in kind, not just amount. ChatGPT Enterprise is a per-seat assistant that sits alongside your existing SaaS — so it adds to your software spend. osFoundry is positioned to consolidate several tools into one platform, which changes total cost of ownership rather than simply adding a line item. dgm’s engagement pricing is transparent and fixed: a $399 initial consultation and $3,999/month for full integration. The honest comparison is not seat-versus-seat but stack-versus-platform — which is exactly what a dgm assessment quantifies for your business.
Who each is best for
ChatGPT Enterprise is the stronger pick if your priority is a best-in-class assistant for knowledge workers, you are comfortable standardizing on OpenAI, and you want mature admin and compliance controls out of the box. osFoundry is the stronger pick if you want to stay model-flexible, automate across many systems, and reduce the number of SaaS tools you pay for — especially if avoiding single-vendor lock-in is a stated goal.
Which should a US company choose?
If you want the best OpenAI chat assistant for your team, ChatGPT Enterprise is a safe, capable choice. If your goal is to stay model-flexible, automate across systems, and replace overlapping SaaS, a model-agnostic platform like osFoundry is the more strategic foundation. Most companies do not have to choose blind: dgm runs a short assessment of your tools and workflows, shows which path — or which mix — delivers the most value for a US business, and then handles the integration end to end.