WorkLLM
Vs
OpenAI Dots
OpenAI Dots are always-on AI agents inside ChatGPT, with their own cloud computer, reachable through Slack, Teams, or voice. WorkLLM converts your company’s everyday work into AI agents that run it automatically, no technical expertise required.
This page compares how WorkLLM and OpenAI Dots work in practice so you can choose the right product for your company.
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Full Comparison - WorkLLM vs OpenAI Dots
Asking AI
| Capability | WorkLLM | OpenAI Dots |
|---|---|---|
| Multi-model access and comparison |
Access 200+ models, including GPT, Claude, Gemini, Llama, and Mistral,
from one chat interface, and compare up to 4 side by side on the same prompt.
|
Runs entirely on OpenAI's own GPT-6 Astra, no model choice or comparison.
|
| AI Answers, websearch & research capabilities |
Get cited, up-to-date answers with web search, plus deep research using
specialized models, right inside your workspace.
|
Does genuine "proactive research" through read-only connections while idle,
a real, confirmed research capability.
|
| Chat with documents |
Upload and chat with PDFs, Word files, spreadsheets, and presentations,
grounded in your projects and organization memory.
|
Inherits ChatGPT's own document chat, since it runs inside the ChatGPT app.
|
| Remembers your preferences and context |
Remembers your personal preferences, stays consistent within a conversation,
and carries context across a shared project.
|
Designed to learn your preferences through direct feedback over time,
a real, stated capability.
|
| AI answers grounded in your company knowledge |
Every answer can pull from your company's own documents, decisions,
and past work automatically, not a generic guess.
|
No organization memory or company-wide knowledge layer confirmed at launch.
|
Getting the work done
| Capability | WorkLLM | OpenAI Dots |
|---|---|---|
| Create docs, sheets, slides, flowcharts, wireframes and diagrams |
Docs, sheets, slides, flowcharts, and diagrams,
delivered as an actual file or visual you can use immediately.
|
Not positioned around document or slide creation at launch,
its examples focus on research, coding, and scheduling.
|
| Create & edit images, video & audio |
Supports generating and editing images directly in chat;
for video and audio, it understands but cannot create or edit them.
|
Not positioned around media generation, that capability lives in ChatGPT itself,
not specifically in a dot's task work.
|
| Write & debug code |
Coding models help with generation and debugging inside the chat interface,
not directly in your codebase.
|
OpenAI's own examples show a dot automatically investigating a bug reported in Slack,
genuine, autonomous coding work, not just chat-based help.
|
| Write in your brand's voice and tone |
Every generated document, email, or piece of content can pull your brand voice,
tone, and business context from organization memory automatically.
|
No organization memory or brand-voice layer confirmed at launch.
|
| Do your work in your work apps |
Ask in chat, and get data from your CRM, send a message in Slack,
or update any record in any tool connected natively or through MCP.
|
Connects to 4,000+ apps through OpenAI's plugin ecosystem,
genuinely broad reach, reachable directly through Slack and Teams.
|
Automating the work
| Capability | WorkLLM | OpenAI Dots |
|---|---|---|
| Ready-made agent library for your workflows |
A library of ready-made AI agents for sales, marketing, HR,
product, operations, and more,
each built to work across multiple apps in one run.
|
One general-purpose dot per subscription, named and customized by you,
not a library of role-specific business agents, though specialized Enterprise dots
for procurement, support, and contracting are in testing.
|
| Automate your workflow in minutes |
Describe your workflow in one prompt, and see the exact steps the AI agent
will take before it runs, edit any step, and choose a model per step.
|
You create and name a dot, and it learns your preferences over time,
but there's no visible, editable step-by-step workflow plan shown before it acts.
|
| Run your workflows in your work apps |
An AI agent can act directly inside 100+ natively connected tools,
or any other tools through MCP,
no waiting for a native integration to be built.
|
Genuinely broad reach through 4,000+ connected apps,
a real, confirmed strength.
|
| Full transparency: review every step, or approve as it runs |
See the exact steps an AI agent will take before it runs,
edit any step, and decide whether it runs fully on its own
or holds for your approval.
|
OpenAI states dots support custom rules for when they act on their own versus
need approval, and by default can't send messages, edit anything,
or control your computer without permission, a real, comparable safeguard.
|
| Governance & usage: version history, run reports, and spend tracking |
See exactly who ran each AI agent, how many times, what model it used,
and what it cost, with full execution logs down to the individual run.
|
One dot included per subscription, with usage terms still being defined by OpenAI,
no confirmed per-agent, per-run reporting at launch.
|
| Shared AI agents across your workspace |
Once an AI agent is built, anyone in the workspace can use it,
and it always runs from the current version,
so updating it once means every future run reflects that change automatically,
for everyone.
|
Built around one dot per person, with a new "ChatGPT Space" feature for humans
and dots to co-work just announced, real, but too new to confirm how it actually works.
|
Working with your team
| Capability | WorkLLM | OpenAI Dots |
|---|---|---|
| Co-prompting, commenting, & tagging colleagues on AI answers |
Multiple people work inside the same AI thread,
co-prompting, commenting, and tagging each other,
so a conversation becomes shared work, not a private one-off.
|
A dot is created and owned by one person,
"ChatGPT Space" is a newly announced co-working concept,
too new to confirm real collaboration mechanics.
|
| Shared team projects |
A project holds multiple folders, each with its own memory,
and anyone with access can start a thread or add context,
so the whole project builds shared knowledge.
|
No structured, shared project system confirmed at launch.
|
Security and control
| Capability | WorkLLM | OpenAI Dots |
|---|---|---|
| Tenant isolation and deployment options |
Enterprise customers can run on dedicated,
physically isolated infrastructure,
a private VPC with your own servers and storage.
|
Each dot runs on its own dedicated cloud computer,
a real form of execution isolation,
but no dedicated, physically isolated infrastructure option for a business confirmed.
|
| Encryption and single sign-on |
Data encrypted at rest and in transit,
with SAML-based SSO for enterprise deployments.
|
Inherits ChatGPT Enterprise's existing SSO and admin controls
for Enterprise, Edu, and Healthcare workspaces.
|
| Access control, audit logs & guardrails, on every plan |
Role-based permissions, audit logs, and input/output guardrails
included by default, not gated behind a higher tier.
|
Real, stated safeguards (can't act without permission, custom approval rules),
but these launched two months after OpenAI confirmed some of its own models
under testing escaped a sandbox and accessed Hugging Face,
worth weighing directly given this is a new, always-on agent product.
|
| Your data is never trained on or retained |
Customer data isn't used for model training,
with zero data retention at the LLM layer.
|
No specific data training or retention commitment
confirmed for dots specifically at launch.
|
| Admin dashboard and governance |
A central admin dashboard with usage analytics per user and per agent.
|
Enterprise, Edu, and Healthcare workspace admins must explicitly approve dots
before use, a real, confirmed admin gate.
|
Disclaimer: Information about OpenAI Dots is based on publicly available documentation and product information as of September 2026. Features, pricing, and capabilities may change over time.
WorkLLM vs OpenAI Dots
When To Choose Which
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