Which fits: ChatGPT Enterprise or self-hosted Open WebUI for your team
ChatGPT Enterprise fits teams that want OpenAI to run the service and accept its documented controls: SAML SSO, admin-set retention, regional data residency for eligible new customers, and SOC 2 Type 2 reports. If your residency rule can be met by a selected region and your auditors accept OpenAI's attestations, the hosted service removes the need to patch, back up and monitor an application yourself. The trade-off is that ChatGPT Enterprise only runs as an OpenAI-hosted service, so the database, logs and model vendor sit outside your control. Admins can view, export and delete conversations and pull an audit log through the Enterprise Compliance API, which is the export path to confirm before you commit. Self-hosted Open WebUI fits teams that need to own the conversation store, logs and retention schedule, or that want one interface across Ollama, OpenAI and other OpenAI-compatible providers. Its documented SSO covers OIDC and LDAP, with SCIM 2.0 provisioning, role-based access control and authenticator-app MFA. Multi-instance deployments need PostgreSQL, Redis and shared file storage, so the operating burden moves to your team. Ask whether your platform team can own upgrades and security patches, and whether an offline mode is required, since Open WebUI can run entirely offline with Ollama.
The decision turns on three questions. First, where must the data sit: a regional OpenAI setting, your own EU or national infrastructure, or an isolated network. Second, what operating capacity you have for a stack of the interface, database, cache, model runtime and identity integration. Third, the Open WebUI License: deployments above 50 users in any rolling 30-day period may not alter or remove Open WebUI branding unless they hold an enterprise license or written permission from the copyright holder, so confirm your user count and branding plans with Open WebUI enterprise sales before rollout. Quote requests should state the expected seat count, since enterprise pricing is not published.
Which option fits which scenario
This table maps common buyer situations to the option that usually fits better, with the condition that tips the decision. Read each row as a starting point: the condition column tells you what to verify in your own environment before choosing.
| Scenario | Better fit | Condition that makes it so |
|---|---|---|
| Regulated team that needs customer-controlled logs and retention | Open WebUI (self-hosted) | You need the conversation database, logs and deletion schedule in your own systems, and an assessor expects evidence from those systems directly |
| Team that wants zero operations work | ChatGPT Enterprise | You have no capacity to run PostgreSQL, Redis, storage, upgrades and model hosting, and you accept OpenAI-managed retention and the Compliance API as the export path |
| Isolated or air-gapped network | Open WebUI with local models | ChatGPT Enterprise only runs as an OpenAI-hosted service, so the network must allow local model serving through Ollama or vLLM on your own hardware |
| Multi-provider model strategy | Open WebUI (self-hosted) | You want one interface over Ollama, OpenAI, Anthropic and other OpenAI-compatible endpoints, with model choice decided per team |
| Single-vendor model use with OpenAI-native features | ChatGPT Enterprise | Your users depend on OpenAI-hosted features and models and you want one vendor contract covering the service |
| Small pilot under 50 users | Open WebUI (self-hosted) | You can run it without the branding clause applying, since deployments of 50 or fewer users in a rolling 30-day period may alter branding; confirm the threshold against the current license text |
| Larger rollout that must keep Open WebUI branding | Either, after a license decision | Above 50 users in a rolling 30-day period, branding changes need an enterprise license or written permission, so get that quoted before rollout |
| Data residency in a specific region | Depends on your infrastructure | ChatGPT Enterprise offers regional residency for eligible customers; Open WebUI fits when you can host the whole stack in the region you require |
Where ChatGPT Enterprise and Open WebUI keep conversations
ChatGPT Enterprise keeps conversations in OpenAI's hosted service, and the workspace admin decides how long they stay. OpenAI documents that Enterprise admins control retention and that deleted conversations are removed from its systems within 30 days unless legally required. Admins can view, export and delete end user conversations, and the Enterprise Compliance API provides the audit log of conversations and GPTs. Data residency stores in-scope content at rest in a selected region, as described in the OpenAI data residency help article. Residency is not the same as inference location, so confirm with OpenAI in writing whether your region also covers inference, which is offered only in some regions and on top of data residency.
With Open WebUI, the conversation store is the one you run. Chat history, user accounts, uploads and any retrieval index sit in the infrastructure you choose. For a single instance, SQLite is the default, but the scaling guide requires PostgreSQL for multi-instance deployments because SQLite does not handle concurrent writes from multiple processes well. Multiple replicas also need Redis for shared session state and shared file storage so uploads and knowledge stay reachable from every replica. Retention, backup and deletion then become your procedures, set in your database and storage tools, not a vendor setting with a documented 30-day window.
Before you choose, confirm three things. First, which region OpenAI will use for data at rest, and whether inference also runs there for the models you need. Second, what the Compliance API export covers and how long your own copies must be kept. Third, where Open WebUI's database, file storage, vector database and model endpoints will run, since an external model API such as OpenAI's still processes prompts outside your network. Document each location in your data map, and assign an owner for backups and deletion requests, because these duties move from OpenAI to your team.
Who controls data, hosting and compliance evidence
The core difference between the two options is where conversations, retention settings and logs sit and who operates them. The cards below cover data location, hosting models, SOC 2 evidence, identity and the patching duties that follow from each choice.
Where conversations are stored
ChatGPT Enterprise stores workspace content in OpenAI's service, with regional residency available for eligible customers. With Open WebUI, the conversation database, uploads and retrieval index sit in your own infrastructure, so you decide the storage location, backup target and deletion process. Ask OpenAI which residency option applies to your account and region, and confirm where your own database and file storage will run.
Retention and deletion ownership
In ChatGPT Enterprise, workspace admins set retention, and OpenAI states that deleted conversations leave its systems within 30 days unless law requires otherwise. In Open WebUI, retention is whatever your database and backup policy enforces, including how long backups and logs keep deleted content. Write the retention rule for chats, uploads and backups before go-live, since an auditor will ask for it.
Hosting models Open WebUI supports
Open WebUI installs with Docker and Docker Compose, Kubernetes with Helm, or pip followed by open-webui serve. A single container suits a small pilot, while multiple replicas require PostgreSQL, Redis and shared file storage. Choose the method your platform team can patch and monitor, and confirm that your environment matches the scaling guidance before you add replicas.
SOC 2 Type 2 and compliance evidence
OpenAI documents SOC 2 Type 2 audits for ChatGPT Enterprise, which gives you a third-party report to hand to your assessors. An Open WebUI deployment has no equivalent report by default, so the evidence comes from your own controls, logs and change records. DeployOpen prepares systems, controls and evidence for assessments, but independent auditors issue the report. Ask any assessor which evidence they will accept before you design the stack.
Identity and access integration
ChatGPT Enterprise uses SAML SSO and admin-managed workspace roles. Open WebUI documents SSO through OIDC and LDAP, SCIM 2.0 provisioning, role-based access control with groups and API keys with authenticator-app MFA. Confirm that your identity provider can issue the claims and group mappings you need, and that offboarding removes access to chats and knowledge collections, not only the login.
Patching and upgrade responsibility
OpenAI operates and patches ChatGPT Enterprise, so the patch cadence is theirs to manage and report on. With Open WebUI, your team or a support partner owns image updates, dependency patches, database upgrades and model runtime updates such as Ollama. Put a named owner and a patch window in writing, and check release notes before each upgrade, since the project publishes new versions frequently.
What the Open WebUI License requires and when it matters
Since v0.6.6, released April 19, 2025, Open WebUI code is distributed under the Open WebUI License, which is a BSD-3-Clause style license with an added branding protection clause. Code through v0.6.5 remains under BSD-3-Clause. That split matters for any audit of which version your organization runs, because the terms that apply depend on the version you deploy, not on the project name. Confirm the exact version in your environment and keep the matching license text with your records.
The clause forbids removing or altering Open WebUI branding in a deployment that exceeds 50 users in any rolling 30-day period, unless one of three conditions applies: the operator holds an enterprise license, the copyright holder grants written permission, or the deployment stays at or below that threshold. Count users by the rolling window, not by headcount, and include contractors and service accounts that sign in. A rollout that starts small and grows past the threshold can trigger the clause without any change in the software.
Open WebUI offers enterprise licenses that allow white-labeling and custom branding, along with dedicated support. Pricing is not published and is quoted after contacting enterprise sales with an expected seat count, so ask for the quote in writing and treat it as a separate line from infrastructure, hosting and staff time. Have counsel read the full LICENSE file and the license history before you commit, confirm how the clause applies to your intended deployment and internal rebranding, and do not treat this summary as legal advice. Open source licensing is not a zero-cost promise, and the terms should be read in full.
Who patches and runs each stack
ChatGPT Enterprise runs only as an OpenAI-hosted service, so OpenAI operates the infrastructure, applies its own changes and carries the hosting obligations. Your team does not schedule upgrades, patch the application or size the servers. What you control is configuration: SAML SSO, admin retention settings, regional data residency where eligible and the Enterprise Compliance API for audit and export. OpenAI documents SOC 2 Type 2 audits for the service, which you can request as part of your vendor review.
- Platform upgrades: OpenAI rolls out changes on its own schedule, and your workspace admins see the effects without planning a maintenance window.
- Infrastructure and patching: OpenAI patches the hosting layer, and you cannot inspect or run the underlying systems yourself.
- Retention and deletion: Admins set retention, and OpenAI states that deleted conversations are removed from its systems within 30 days unless legally required.
- Monitoring and incidents: Availability and incident communication come from OpenAI, so you rely on its status channels and contract terms rather than on telemetry you collect.
- Audit evidence: Ask for the current SOC 2 Type 2 report, the subprocessor list and the breach notification terms before you sign.
Confirm with your procurement and security teams which of these items your contract covers in writing.
With a self-hosted Open WebUI stack, your team or its implementation partner owns every upgrade, patch and restore. Open WebUI installs with Docker and Docker Compose, Kubernetes with Helm, or pip, and the install method determines how you pull, pin and roll back a version. As a reference point, v0.12.3 was published on the project's GitHub releases page on October 16, 2026, after v0.12.0 on October 10 and v0.11.0 in July. Each release is a change you must review, test and schedule.
- Release review: Read the release notes and compare them with your configuration, connected models and any functions or plugins you have added.
- Staging first: Apply the new version to a copy of production data, then check login, SSO, model connections and knowledge retrieval before promoting it.
- Backup before change: Snapshot the PostgreSQL database and file volumes so a failed upgrade can be reversed.
- Pinned versions: Pin the image tag, Helm chart version or pip version so that no node upgrades on its own.
- Host and dependencies: Patch the operating system, container runtime, Redis, PostgreSQL and reverse proxy on a cycle you document.
Confirm with your partner who owns each runbook step, how a rollback is performed and where upgrade records are kept for your change management evidence.
A single Open WebUI instance can run with default local storage, but the scaling guide changes the design once you run more than one replica. The guide requires PostgreSQL in place of SQLite for multi-instance deployments, because SQLite does not handle concurrent writes from multiple processes well. Replicas also need shared state and shared files, so the availability of every replica depends on those services.
- PostgreSQL: Provision, back up and restore-test the database on its own patching schedule, whether you run it yourself or use a managed service.
- Redis: Redis holds sessions, websocket connections and application state, so a Redis outage affects every replica at the same time.
- Shared file storage: Uploads and knowledge must be reachable from every replica, so choose a storage backend with its own redundancy, access controls and backup.
- Ingress behavior: Session and websocket handling depends on how your load balancer routes traffic, so test it with the settings you will run in production.
- Failure testing: Simulate the loss of one replica, the Redis service and the storage backend before users depend on the setup.
Confirm with your platform team who operates Redis and storage, their recovery targets and where logs from each component are collected.
Open WebUI connects to model runtimes, and Ollama is a common choice for local models. Ollama is MIT licensed and binds to 127.0.0.1 on port 11434 by default. Its local API does not require authentication, so any process or user that can reach that port can send requests. Changing the bind address with OLLAMA_HOST, or placing a proxy such as Nginx in front of it, makes the API reachable from other hosts, which means authentication and network rules must be part of your design.
- Default bind: The loopback address keeps the API off the network until someone changes OLLAMA_HOST, so record every change in your build documentation.
- Proxy authentication: Add authentication, TLS and network restrictions at the reverse proxy or service mesh before the endpoint is exposed to any other host.
- Cloud features: Set OLLAMA_NO_CLOUD=1 or the equivalent server configuration when you need local-only inference, then verify the setting on each running host. Direct calls to Ollama's cloud endpoints require an API key sent as a Bearer token, so store and rotate those keys like other secrets.
- Model storage and concurrency: Models live in a default directory unless OLLAMA_MODELS moves them, and OLLAMA_NUM_PARALLEL defaults to one request per model, so size hosts for the concurrency you expect.
- Version tracking: Ollama published v0.40.5 on 14 October 2026 and v0.40.6 as a pre-release on 16 October 2026, so record which version each host runs.
Confirm the bind address, proxy rules, cloud settings and version on every model host during your access review.
What each stack costs and what drives the bill
This table sets each cost component of a ChatGPT Enterprise workspace beside the components of a self-hosted Open WebUI stack, with who is paid, whether the cost is one-time or recurring, and what moves it. Use it to build a quote request, not to estimate a total, because the largest lines depend on your seat count, model choice and hardware.
| Cost component | Who is paid or who carries it | One-time or recurring, and what drives it |
|---|---|---|
| Seat subscription | OpenAI, under an Enterprise agreement; no price is stated here | Recurring per user. Drivers are seat count, contract term and any negotiated terms you request in writing. |
| Model inference | OpenAI inside the subscription, or a model API vendor, or your own GPUs for local models | Recurring. Hosted use is bundled with the seat. Self-hosted use depends on GPU capacity or API token volume and on how many users query at once. |
| Local model runtime (Ollama) | No license fee for running models on your own hardware; Ollama's pricing page says this use is unlimited | Recurring hardware and power cost. Ollama's paid cloud plans apply only if you use its hosted cloud models, which you can switch off with OLLAMA_NO_CLOUD=1. |
| Open WebUI software | No subscription for the open source edition; enterprise licensing is quoted by Open WebUI after contact with an expected seat count | One-time or recurring depending on whether you need white-labeling, which the branding clause requires above 50 users in a rolling 30-day period unless you hold a license. |
| Hosting and compute | Your cloud account, data center or hardware budget | Recurring for application containers and any replicas. Replicas are needed for multi-instance deployments, which add to the bill. |
| PostgreSQL | Your database team or managed database service, if you use one | Recurring for storage, backups and high availability. Required instead of SQLite for multi-instance deployments according to the Open WebUI scaling guide. |
| Redis and shared storage | Your platform team or managed service | Recurring. Needed for multi-replica sessions, websockets and shared uploads and knowledge files, so cost grows with replica count and stored documents. |
| SSO and identity integration | Your identity team, or DeployOpen if scoped as implementation work | One-time for OIDC, LDAP or SCIM setup and testing, then recurring for directory maintenance. ChatGPT Enterprise SAML SSO is included in the subscription but its setup still needs internal time. |
| Upgrades, patching and support | Your team, a managed support retainer, or a fixed-scope engagement | Recurring. Open WebUI releases are frequent (v0.12.3 was published on October 16, 2026), so upgrade testing repeats. In ChatGPT Enterprise, OpenAI operates the service. |
How a move from ChatGPT Enterprise to Open WebUI proceeds
The sequence moves a ChatGPT Enterprise workspace into a self-hosted Open WebUI stack that you run, with history, identity, models and retention settled before users switch over. Each step ends with a check that tells you it can close.
Inventory workspace data and retention obligations
The workspace owner and compliance lead list what the ChatGPT Enterprise workspace holds, which users and GPTs are active, and which retention duties apply to conversations. Admins can view, export and delete end user conversations, and the audit log of conversations and GPTs is retrieved through the Enterprise Compliance API. Confirm with OpenAI exactly what the export covers and leaves out before promising history to anyone. The step is done when you have a written list of data sets, owners and legal holds.
Export and retain conversation history
Using the Enterprise Compliance API, the admin pulls conversation and GPT records into a store you control, such as an encrypted object store or database with access logging. Whether those records can be imported into Open WebUI depends on the export format, so test the import on a sample before relying on it. The output is a retained archive with a checksum record and a named custodian. Keep it separate from the live Open WebUI database so retention can be applied independently.
Define groups and map SSO and provisioning
The identity team connects Open WebUI to the corporate identity provider using OIDC or LDAP and enables SCIM 2.0 user and group provisioning where your identity platform supports it. Groups are mapped to Open WebUI roles, and per-resource permissions are set so that knowledge collections and models are visible only to the right teams. Compare this with the SAML SSO and admin roles you use in ChatGPT Enterprise, since the mapping is not one to one. The step closes when a test user from each group signs in and sees only the expected models and collections.
Choose and connect model backends
The architecture team selects where inference runs: a self-hosted runtime such as Ollama, an OpenAI-compatible API, or another provider Open WebUI supports. Each backend is recorded with its data handling terms, regional location and access method, and API keys are stored under your secrets process. Ollama's local API does not require authentication, so it must sit behind your own network controls and proxy. The step is done when each model appears in Open WebUI, responds to a test prompt, and has a documented owner.
Deploy and harden the stack
The platform team deploys Open WebUI with Docker Compose, Helm on Kubernetes or pip, following the scaling guidance if more than one replica is needed. For multiple instances, PostgreSQL replaces SQLite, and Redis and shared file storage keep sessions and uploads reachable from every replica. Hardening covers TLS, backups of the database and files, logging, patch cadence for Open WebUI and its dependencies, and MFA for administrators. The check is a restore test from backup and a documented patch and upgrade procedure.
Pilot with a limited user group
A small group of business users works in the new interface for a defined period agreed internally, using real but non-sensitive tasks. The pilot team records login issues, missing models, permission gaps and prompt behavior differences, and reviews the Open WebUI License branding clause for the planned user count. Pilot results feed fixes to group mapping and model choices. The step closes with a signed pilot report and a list of resolved or accepted issues.
Cut over with a retention plan
The organization announces the switch, sets a date for the ChatGPT Enterprise workspace to stop being used for new work, and confirms the retention schedule for both the archive and the new Open WebUI database. Admins apply deletion or retention rules in the new stack and document who can export or delete conversations. Any remaining obligations in the ChatGPT Enterprise workspace are handled under the retention terms OpenAI documents, which should be confirmed with OpenAI. The step is done when retention policies are active, access reviews are scheduled, and the cutover is recorded.
Questions buyers ask before choosing Open WebUI
Is running Open WebUI cheaper than a ChatGPT Enterprise seat license?
It depends on which costs you count, and the answer moves with usage. ChatGPT Enterprise is a per-seat subscription paid to OpenAI, which covers the hosted service, its controls and the model. Open WebUI's software is free to download, but you pay for the servers, the model inference (either GPUs you run or API calls to a provider), PostgreSQL and Redis if you scale out, storage, SSO integration, monitoring, upgrades and support. Inference is the line most likely to swing the total, since it grows with heavy use and with the size of models you run. Ask any partner for a quote that lists each component separately, with the assumed user count, usage pattern and hardware, so you can compare it with your current OpenAI invoice line by line.
How long does a self-hosted Open WebUI deployment take?
The timeline depends on scope, not on the software installing. A single-instance Docker or pip install can be running quickly, but a production rollout also covers SSO and SCIM mapping, group and role design, PostgreSQL and Redis for multiple replicas, shared file storage, model hosting, backups, logging and testing. Those tasks depend on your identity provider, your data sources and how many approval steps your change process requires. Treat any duration you hear as a guess until it appears in a written, fixed scope with deliverables and milestones. DeployOpen agrees scope, deliverables and timelines in writing before work starts.
Can our own team run Open WebUI without outside help?
A team with container and identity experience can usually stand up a proof of concept alone, using the official Docker Compose, Helm or pip install paths. Production is harder because it needs a database that handles concurrent writes, shared state for replicas, correct OIDC or LDAP settings, backup and restore tests, and a plan for upgrades. Open WebUI releases are frequent, so someone must own the update cycle and check each release before it reaches users. Decide early whether your staff will own this work, whether you need a retainer for ongoing support, or whether you want a fixed-scope build first and then move it to internal ownership.
What skills and staff time does a self-hosted assistant need?
Expect to staff at least three roles: someone who runs the container platform or Kubernetes cluster, someone who owns identity and access (SSO, SCIM, groups and roles), and someone who owns model hosting and capacity, whether that is Ollama, vLLM or an API gateway. Security or compliance staff also need time to review logging, retention and access settings. The recurring workload is patching, upgrades, monitoring, backup testing and answering user access requests. Ask any implementation partner to name which of these tasks it will perform, which ones it will hand over, and what your staff must do each month once the system is live.
Does the Open WebUI branding clause apply to our organization?
It applies once a deployment exceeds 50 users in any rolling 30-day period, and only if you want to remove or alter the Open WebUI branding. Since v0.6.6, released on April 19, 2025, Open WebUI code is under the Open WebUI License, which adds that clause; code through v0.6.5 remains BSD-3-Clause. Below the threshold, or with the copyright holder's written permission, you can change branding freely. Above it, you can buy an enterprise license, which also allows white-labeling and includes dedicated support, but pricing is quoted after contacting enterprise sales with an expected seat count. Have your legal team read the license text and the license history file before you commit.
Can Open WebUI run offline or in EU data residency?
Yes, both are possible because you choose where every component runs. Open WebUI can run entirely offline and works with Ollama and OpenAI-compatible APIs, so models and the interface can sit on local hardware in a network with no internet access. For EU residency, the conversation database, uploaded files, retrieval index and model endpoints all sit in infrastructure you select and control. Confirm three things with your vendor or partner: that every model endpoint and telemetry setting stays inside the approved boundary, that backups are stored in the same region, and that any external provider you call is covered by your contract and data processing terms. The air-gapped design also needs an offline process for model and container distribution.
What does SOC 2 mean for a self-hosted Open WebUI stack?
SOC 2 is an attestation issued by an independent CPA firm about a service organization's controls. OpenAI documents SOC 2 Type 2 audits for ChatGPT Enterprise, which is a report on OpenAI's own hosted service. A self-hosted stack has no vendor report that covers your deployment, so the report you need is one about your own environment, if your customers or regulators require it. DeployOpen prepares systems, controls and evidence for compliance assessments, but it does not issue audit reports, attestations or certifications. Independent auditors do that work. Ask your auditor early which control evidence they will request, such as access reviews, logging, change records and backup tests.
How DeployOpen helps evaluate, implement and run Open WebUI
DeployOpen is a Chainscore Labs company that plans, implements, integrates, hardens, backs up, upgrades and documents self-hosted open-source platforms inside your own infrastructure. For ChatGPT Enterprise vs Open WebUI, we start with the governance questions that decide the choice: where conversations are stored, who sets retention, which models are allowed and who patches each layer.
How we scope
- We confirm which teams, data sources and models the assistant must cover before any build work starts.
- The written scope lists the identity, retention, residency and logging requirements we will meet and document.
- Engagements are fixed-scope, with deliverables and timelines agreed in writing before work begins.
How we build
- We deploy Open WebUI with the database, shared state and file storage your user count requires.
- We connect SSO, group provisioning and role-based access controls to your existing identity provider.
- We test model routing, access rules and retention settings, and document the results for your reviewers.
How we hand over
- You receive architecture, configuration and runbook documentation covering backups, upgrades and the license terms in force.
- We walk your platform and security teams through administration, user onboarding and export procedures.
- We prepare the controls and evidence your compliance assessors will ask for, while auditors issue any formal opinion.
How we support
- Ongoing support, upgrades and continuous testing are available as a retainer after handover.
- A retainer can cover tracking Open WebUI releases, testing upgrades in staging and applying them under agreed change control.
- Ask any provider to confirm in writing who patches the application, the database, the model runtime and the host.
