Siesta AI vs ChatGPT Enterprise

Native connectors across your enterprise stack — Microsoft 365, Google, Slack, Notion, Confluence, Jira, Salesforce, HubSpot, GitHub, Zendesk, Box, Dropbox and more.

Growing set of integrations and custom GPTs. Most enterprise knowledge still needs to be uploaded manually or connected via API.

Mirrors source-system ACLs in real time; users only see what they are entitled to across every connected app.

Workspace-level sharing controls. Source-system permission enforcement on connected data is not natively available.

Persistent structured memory objects shared across users, agents and departments — organisational context is never lost.

Knowledge lives in uploaded files or per-GPT context. No persistent company-wide memory layer with structured objects.

Role-based access control, department scoping and granular data-source permissions managed from a single admin panel.

Workspace-level admin roles and SSO. Granular per-source access control within the product is limited.

GPT-4/5, Claude, Gemini, Mistral, Llama or your own private LLM — switch per agent or per workflow.

OpenAI models only. Running Claude, Gemini or private models is not part of the ChatGPT product.

Every answer is cited with source documents and respects the asking user's permissions across all connected systems.

Answers grounded in uploaded files or web browsing results. No live access to internal systems with ACL enforcement.

Web app, browser extension, Slack, Teams, mobile and embedded SDK — plus public and internal widgets.

Web app, desktop and mobile chat. Native Slack, Teams and browser-extension presence is not available.

Reusable skills that agents and assistants can invoke — structured, composable capabilities that go beyond prompt templates.

Custom GPTs can encode instructions and knowledge. A reusable skill abstraction across agents is not a native concept.

Visual, no-code builder for prompts, tools, knowledge and approvals — included in every plan.

Custom GPTs provide a basic builder. Production agents with tool orchestration require the Assistants API and your own code.

Schedule, webhook, email and event triggers; governed actions across every connected app.

Scheduled runs and event triggers are not native to the ChatGPT product. Actions require building your own integrations.

20+ pre-built agent templates for sales follow-ups, deadline reminders, RFPs, onboarding, IT triage and more.

GPT Store hosts community GPTs. Enterprise-grade agent templates with governed workflows are not available.

AI-generated task queues with assignment, review flows and status tracking — turning agent output into managed work.

ChatGPT generates text output. Managed task queues with assignment and review flows are not part of the product.

Visual workflows chaining retrieval, generation, approvals and actions across any connected tool.

Not natively available in the ChatGPT product. Requires custom code via the API or external automation tooling.

Built-in approval steps, audit trail and rollback for sensitive actions.

Must be implemented by your engineering team if you build on the API.

Every agent run is logged with inputs, outputs, latency, cost and tool actions — exportable to your BI stack.

Workspace-level usage analytics. Per-run audit trails with cost attribution are not available out of the box.

Agents execute actions in Jira, Gmail, Salesforce and CRM with role-based permissions, approval gates and full audit trail.

Tool use is available via plugins and function calling. Governed execution with approval gates is not a native ChatGPT feature.

SaaS, EU-hosted, hybrid or fully private customer infrastructure.

SaaS on OpenAI / Azure infrastructure. Private-cloud or customer-managed deployment is not available for the ChatGPT product.

Pin all data and inference to EU regions; no training on customer data, ever.

Some EU data zones available. Full customer-controlled residency end-to-end is limited.

ISO 27001, GDPR — full DPA with sub-processor list.

SOC 2 Type II; enterprise DPA available. Compliance posture is maturing.

Control which models each department or workflow can use — enforce policies centrally across all agents.

Model selection is not configurable per department. All users share the same OpenAI model tier.