Do I need Claude Enterprise or ChatGPT Enterprise if I have DeepInspect?

You still need whichever provider tier gives you the model access and the contractual data commitments you require. DeepInspect is not a substitute for the provider contract. DeepInspect is the enforcement layer that operates on the traffic between your users and whichever provider you contracted.

How does DeepInspect handle provider-native features like function calling?

DeepInspect inspects the full request and response, including function-calling tool definitions and tool responses. The policy engine evaluates tool calls the model requests and can block or redact them at the inspection layer before they reach the calling application.

Do both providers publish real-time audit APIs?

OpenAI's Compliance API surfaces conversation records on a schedule that is close to real time but is not synchronous with the conversation. Anthropic's audit log API surfaces admin events in near real time and conversation metadata on a sampled basis. Neither provider offers a synchronous per-request audit hook that fires inside the customer's boundary at decision time.

Does the shared responsibility model shift when I use an independent inspection layer?

The provider's responsibility for the model and the provider's infrastructure remains with the provider. The customer's responsibility for the controls inside the customer's boundary remains with the customer. An independent inspection layer changes which vendor produces the customer-side controls, not which party is responsible for them.

How does the audit record from DeepInspect compare to the Compliance API record from OpenAI?

The OpenAI Compliance API record captures the conversation content and the workspace metadata OpenAI holds. The DeepInspect audit record captures the identity of the natural person at the customer's boundary, the data classification the customer's policy assigned, the policy state at the moment of decision, and the response classification the customer's policy applied on the output. The two records are complementary. Deployments that require both ingest both.

Can I use DeepInspect while migrating from OpenAI to Anthropic (or vice versa)?

Yes. DeepInspect is model-agnostic. Traffic to OpenAI, Anthropic, and any other supported provider flows through the same inspection layer. A migration that reroutes traffic from one provider to another does not change the identity binding, the policy enforcement, or the audit record shape.

Anthropic vs OpenAI Enterprise Controls: Where the Provider Stops and the Enforcement Layer Starts

Anthropic Claude Enterprise and OpenAI ChatGPT Enterprise both publish an enterprise control surface. SSO integration through SAML and OIDC. Audit log APIs. Admin consoles with usage analytics. Data residency options in a handful of regions. The two surfaces look similar at the marketing tier. The differences and, more critically, the overlap in what neither surface covers, are what matter for a Head of Security evaluating a deployment.

I want to walk through the controls each provider publishes, the mapping to enterprise compliance requirements, and the enforcement gap at the AI request layer that neither provider closes because neither sits between the enterprise's users and the model.

TL;DR

Anthropic Claude Enterprise and OpenAI ChatGPT Enterprise publish comparable admin-console controls, SSO integration, and audit log APIs. Both providers expose the AI capability as a service and secure it at the provider boundary. Neither provider sits between your users and the model to enforce identity-bound policy or produce per-decision audit records inside your control boundary. That gap is where an independent inspection layer operates.

Anthropic Claude Enterprise: what it publishes

Anthropic Claude Enterprise ships identity integration through SSO. The enterprise plan lists SAML 2.0 for identity provider integration, SCIM for user provisioning, and a role-based admin console for permission management. The audit log API surfaces admin events (user added, role changed, workspace setting modified) and, on the enterprise tier, sampled conversation metadata.

Data handling. Anthropic Claude Enterprise contracts include the data-use commitment that inputs and outputs are not used for model training. Data residency is limited to the regions Anthropic operates in, which as of mid-2026 include US and EU tiers with region-affinity routing.

Retention. Enterprise deployments can set conversation retention policies (30, 90, 365 days, or custom) at the workspace level. The retention applies to the conversation storage Anthropic manages.

Model access. Enterprise admins configure which models are available to which users. The configuration lives in the Anthropic admin console.

OpenAI ChatGPT Enterprise: what it publishes

OpenAI ChatGPT Enterprise ships identity integration through SSO. The enterprise plan lists SAML 2.0 for identity provider integration, SCIM for user provisioning, and a workspace admin console for permission management. The Compliance API surfaces conversation records for compliance ingestion into third-party archives.

Data handling. OpenAI ChatGPT Enterprise contracts include the commitment that business data is not used for training the models, and data is encrypted in transit and at rest. Data residency is limited to the regions OpenAI operates in.

Retention. Enterprise deployments can set conversation retention at the workspace level. Zero data retention is available for API deployments on request.

Model access. Enterprise admins configure model access per workspace and per user.

Feature comparison

The two enterprise plans overlap substantially at the admin-surface layer. The table below reflects the state at July 2026 and will drift as both providers ship updates.

| Control | Anthropic Claude Enterprise | OpenAI ChatGPT Enterprise | |---|---|---| | SSO (SAML 2.0) | Yes | Yes | | SCIM provisioning | Yes | Yes | | Admin console | Yes | Yes | | Audit log API (admin events) | Yes | Yes | | Conversation-level audit API | Sampled metadata | Full via Compliance API | | Data used for training | No | No | | Data residency (US) | Yes | Yes | | Data residency (EU) | Yes | Yes | | Retention configuration | Yes | Yes | | Zero retention option | On request | On request | | Model access controls | Per workspace, per user | Per workspace, per user | | Fine-tuning available | Not on enterprise (July 2026) | Yes for select models | | Sub-processor list published | Yes | Yes | | SOC 2 Type II | Yes | Yes | | ISO 27001 | Yes | Yes | | HIPAA BAA available | Yes | Yes | | Custom identity binding per request | No | No | | Per-decision policy enforcement inside customer boundary | No | No | | Prompt-content classification with customer-controlled taxonomy | No | No | | Output redaction with customer policy | No | No |

The last four rows are the gap that both providers share. Neither provider sits inside the customer's enforcement boundary. Both providers operate at the model boundary, where the customer's identity context and data classifications are not natively available.

The provider boundary

Both Anthropic and OpenAI enforce controls at the boundary where the enterprise's users hit the provider's service. The controls operate on the identity the enterprise's SSO passes to the provider. The provider enforces the workspace-level configuration the admin console holds.

The provider does not see the enterprise's data classifications, does not run the enterprise's DLP policy, and does not attach the enterprise's per-record identity to the audit record inside the enterprise's control boundary. The provider's audit log lives on the provider's storage and requires an API call to retrieve. The retrieval is subject to the provider's retention policy and API availability.

The provider does not enforce policy on tool calls the AI agent makes to other systems inside the enterprise. The provider's control ends at the model boundary. Everything the model produces flows through the provider's response path and into the enterprise's application layer. The application layer is where the enterprise's control resumes.

Pick Anthropic Claude Enterprise if...

You already run Anthropic as your primary model provider and prefer the operational simplicity of one provider surface. You value the Constitutional AI approach to model-level safety training and are aligned to the Anthropic Usage Policy. Your compliance obligations are satisfied by the admin-surface controls plus the sampled conversation metadata the audit API surfaces.

Pick OpenAI ChatGPT Enterprise if...

You already run OpenAI as your primary model provider and prefer the operational simplicity of one provider surface. You need the Compliance API's full conversation record for third-party archive ingestion. Your compliance obligations require conversation-level audit at the provider tier.

Pick an independent inspection layer if...

You run multiple providers. Your compliance obligations require per-decision audit records inside your control boundary, keyed to your natural-person identity, with your data classifications attached. You need policy enforcement that is model-agnostic and survives provider migration. You are subject to EU AI Act Article 12, ISO 42001, or SOC 2 requirements that expect the enforcement point to sit inside your boundary.

Pricing approach

Anthropic Claude Enterprise pricing is contract-negotiated and includes a base workspace fee plus usage-based charges on tokens. Public information does not include per-seat pricing.

OpenAI ChatGPT Enterprise pricing is contract-negotiated with a per-seat annual commitment (150+ seats typically required). Public information includes an approximate starting price around $60 per seat per month for 12-month commitments.

Both providers offer sample pricing on request. Neither provider publishes a fully transparent price sheet, and both encourage a sales conversation for the enterprise plan.

An independent inspection layer is priced by the volume of AI requests that flow through it, not by the provider count or the seat count. The pricing scales with the deployment's actual AI usage.

Compliance posture side by side

The compliance posture of each provider is anchored in the provider's certifications and the customer's use of the provider's controls. Both Anthropic and OpenAI hold SOC 2 Type II and ISO 27001. Both offer HIPAA Business Associate Agreements. Both maintain sub-processor lists and update them regularly.

The customer's compliance posture is not the provider's compliance posture. The customer inherits the provider's certifications through the shared responsibility model. The customer is responsible for the controls that operate inside the customer's boundary. Those controls include the identity binding at the request, the data classification, the policy state at the moment of decision, and the audit record. The provider's certifications do not carry those controls.

DeepInspect

This is where DeepInspect sits. DeepInspect is an independent inspection layer between your users or agents and the LLM APIs, and it works with both Anthropic and OpenAI (and Bedrock, Vertex, and self-hosted models) simultaneously. The identity binding, the policy enforcement, and the audit record are produced inside your control boundary and do not depend on which provider the request eventually reaches.

The provider surface remains the provider surface. Anthropic and OpenAI continue to publish the admin console, the SSO integration, and the audit APIs they publish today. DeepInspect adds the enforcement layer that sits between your users and the provider, and produces the per-decision audit record your compliance obligations expect inside your boundary.

If you are facing the August 2, 2026 EU AI Act deadline, let's talk.