BlogOpenAI Dots for Law Firms

OpenAI Dots for Law Firms

OpenAI's dots can sign into your apps and work around the clock. Here is where they help a law firm, and what to check before they touch client work.

By Jason AlafganiOctober 1, 2026 ·

OpenAI's dots are a capable always-on assistant for a person's own work at a law firm: research, inbox and calendar, follow-ups, and one-off tasks the person checks. For repeated client work like matter intake, conflicts, filing, and billing, they plan each run fresh and keep records per user, so most law firms will want a verifiable agent for that work and keep dots for the rest.

This fall, three AI companies shipped the same idea within weeks: an agent with its own computer that works for you around the clock. xAI launched Grok Bot in August, Meta launched Muse in September, and OpenAI answered with dots at the end of the month. Operations teams at law firms are already asking whether one of them can take work off their plate.

This guide is for that question. It covers what OpenAI's dots are, where they fit at a law firm, and the five things the firm has to answer before an always-on agent touches repeated client work. Every product fact comes from OpenAI's own pages as of October 1, 2026, and these products are changing fast.

What is OpenAI Dots?

dots are OpenAI's always-on agents, announced at DevDay on September 29, 2026. Each dot runs on GPT-6 Astra with its own cloud computer and browser, connects to over 4,000 apps through ChatGPT, and works toward your goals in the background. You can reach your dot in ChatGPT, Slack, and Microsoft Teams.

dots learn from feedback over time, can delegate to other agents, and OpenAI says it envisions teams of dots. Specialist dots with their own identity are in an enterprise pilot.

dots are good at the open-ended work of a busy professional: following up on threads, researching ahead of a meeting, drafting an update, and keeping track of loose ends across thousands of apps.

Plans. Your first dot is included with ChatGPT Pro (from $100 a month, not yet in the EEA, Switzerland, or the UK) and Business Premium. Enterprise, Edu, and Healthcare get a beta an admin has to turn on.
Model. GPT-6 Astra.
Custom Rules. Each rule is set to take action without asking, take action if pre-approved, ask before acting, or hand off to you.
Auto-review. A separate system checks planned actions, like emails and file changes, against your instructions and rules before they run.
Hard stops. Deleting data and granting security-sensitive access always need confirmation. Password changes and transfers between financial accounts are handed back to you.
Records. Activity View shows tasks in progress, scheduled, and completed. Business, Enterprise, and Edu content is not used for training by default.

Product details as of October 1, 2026, from the vendor's own announcement, help, and security pages.

Where law firms want to use dots

Nobody at a law firm needs an agent to do the professional judgment. They want back the hours their teams spend on repeated, system-to-system work:

Matter intake and conflicts. Reading the intake form, running the conflict search in Intapp, and opening the matter.
Document filing. Profiling and filing email and documents into iManage or NetDocuments by the firm's conventions.
Time and prebill review. Chasing missing time, applying outside counsel guidelines, and preparing prebills in Aderant or Elite 3E.
Docketing. Pulling dates out of orders and emails and getting them onto the right calendars.
Inbox triage. Sorting shared mailboxes into new matters, client questions, and court notices, and routing each one.

Picture a legal operations manager setting up a dot to keep matters moving: watch the shared intake mailbox, chase missing engagement letters, and post a daily summary in Teams. Custom Rules let them say follow-ups can go out if pre-approved and anything else asks first, and Auto-review checks each email against those rules before it is sent.

That is a good set of controls for one person's work. For intake at a firm, the dot still decides how to handle each new email on that run, and the record is that user's Activity View. dots are also new: Enterprise access is a beta an admin turns on, and OpenAI's materials do not describe an exportable audit log the firm could hand to a general counsel or a client.

Five questions before dots touch client work

None of these are reasons to avoid dots. They are the questions any law firm has to answer for any agent that acts on a client's behalf.

Will dots do the work the same way every time?

You give a dot a goal and define what it can do on its own; it works out what needs to happen next. Scheduled tasks and Custom Rules shape that, but OpenAI does not describe a saved, step-by-step workflow, and its help center notes that a dot "can make mistakes, including when following your rules."

For matter intake, conflicts, filing, and billing, that matters. You cannot test a procedure on last month's cases and rely on the result if the next run is planned again from scratch.

Who supervises dots at a law firm?

OpenAI's controls are layered: Custom Rules per action type, an Auto-review system that sits outside the dot's environment, hard stops for destructive and security-sensitive actions, and stricter recipient checks as data gets more sensitive. Those are real safeguards. Like the others, they decide which individual actions need a person, not whether the overall procedure is right.

ABA Model Rule 5.3 requires lawyers with supervisory authority to make reasonable efforts to ensure that nonlawyer assistance is compatible with their professional obligations, and ABA Formal Opinion 512 (July 2024) applies the supervision rules to generative AI tools. A supervising partner needs something to supervise: a procedure they can review and a record of how it ran.

Can the firm show what dots did?

Activity View shows each user what their dot is doing, has scheduled, and has finished. OpenAI's dots materials do not describe an exportable audit log or an admin-level log of dot activity.

When a client, an auditor, or opposing counsel asks how a document was filed or why a matter opened without a flagged conflict, the firm needs an answer tied to the specific transaction, not a reconstruction from an agent's chat history.

What happens to client data?

Business, Enterprise, and Edu content is not used for training by default; on personal plans it depends on the Improve the model setting, which can include actions your dot takes. Disconnecting an app does not delete what your dot already pulled from it; removing that data means resetting the dot.

Rule 1.6(c) asks lawyers to make reasonable efforts to prevent unauthorized disclosure of client information. An agent with a user's email, files, and app logins is inside that duty.

OpenAI says plainly: "Dots can still make mistakes, so always review consequential work."

Do dots reach the systems law firms run on?

Over 4,000 apps through the ChatGPT ecosystem, plus Slack and Teams as places to talk to your dot. OpenAI's dots materials do not single out specific practice-management, document-management, or CRM connectors.

Most law firm operations run through Intapp, iManage or NetDocuments, Aderant or Elite 3E, and Outlook, often with portals and desktop software that do not have friendly APIs. Reaching a system is only half of it; the other half is doing the same thing in it every time.

	OpenAI Dots	Caddi
How the work is defined	A goal plus Custom Rules	Tested code you can read and change
Same input, same path?	Not claimed by the vendor	Yes, for the coded steps
Role of AI in a run	Plans and performs each step	Named judgment steps, scoped and logged
Human control	Custom Rules, Auto-review, and hard stops	Review the procedure; exceptions go to a named person
Record of each run	Per-user Activity View; no stated audit export	Every run logged, tied to its source documents
Built for	A person's own varied work	Law firms' repeated back-office workflows

OpenAI Dots vs. Caddi on what a law firm has to answer before an agent runs client work. OpenAI Dots details as of October 1, 2026.

What a verifiable agent does differently

The fix is not a better prompt or a stricter approval setting. It is moving the procedure out of the model. A hybrid agent runs the workflow as code, which can be read, tested, and versioned, and calls AI only for the steps that need judgment, each one scoped and logged.

For matter intake, that means the code reads the intake email, runs the conflict search, opens the matter, and files the engagement letter the same way every time, while AI handles the judgment inside it: is this email a new matter, which party name on the form is the client, does this hit look like a real conflict. Uncertain calls go to the intake team, logged.

That split is what makes an agent verifiable: a reviewer can read the procedure before it runs, every judgment call is on the record, and changes are made on purpose.

More on the idea in what are verifiable AI agents and what are hybrid agents.

Connect Intapp to Caddi
Allow
1Sign in to your tools
One click each for Intapp, iManage and Microsoft Outlook. No API keys.
Automate matter intake.
ScreenshareType it
2Show or tell it
Screenshare the job, or type it in chat. Change it any time.
Running
14 done1 for review
3Watch it run
Caddi does the work and flags anything unsure for review.

Show Caddi the workflow on a call or describe it in chat. It runs as tested code across your tools, with the judgment steps scoped and logged.

How law firms can use both

OpenAI's dots and a verifiable agent are not competing for the same job. Let people use dots for the work around them, where every task is different and the person who asked checks the result.

Put the repeated client work, matter intake, conflicts, filing, and billing, on an agent the firm can verify. That is what Caddi builds: an ops person shows Caddi the workflow on a screen share or describes it in chat, Caddi runs it as code across the firm's tools with the judgment steps logged, and the team changes it in plain English as the work changes. Across Caddi customers, 99% of agent runs complete successfully.

OpenAI's dots show how much an agent can now do inside your apps. For law firms, the next question is whether you can check what it did. Keep dots for personal work, and run client work on a procedure you can review, with a record for every run.

Keep reading

Caddi

See how Caddi AI Agents can run your firm's back office the same way every time and log every run for review

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Frequently asked questions

Is OpenAI Dots safe for law firms?

OpenAI's dots have real safeguards: custom Rules, Auto-review, and hard stops. For a person's own work, those are sensible. For repeated client work, a law firm also has to answer for supervision, records, and confidentiality, and dots plan each run fresh with records kept per user. Most firms will keep it for personal work and use a verifiable agent for client workflows.

Can OpenAI Dots run matter intake, conflicts, filing, and billing unattended?

They can attempt it: dots work in the background and can reach many apps. But each dot decides how to handle each case on that run, and the vendor does not claim repeatable runs, so the firm cannot test the procedure once and rely on it. For unattended client work, a verifiable agent that runs the steps as code is the safer fit.

Does OpenAI Dots keep an audit trail?

Activity View shows each user what their dot is doing, has scheduled, and has finished. OpenAI's dots materials do not describe an exportable audit log or an admin-level log of dot activity. For law firms, check whether that record can be exported, retained, and reviewed at the firm level before relying on it.

Does OpenAI Dots train on our data?

What should a law firm use for repeated client work?

A verifiable agent: one whose procedure you can read, whose judgment steps are logged, and whose every run leaves a record. Caddi builds these for law firms. Your team shows the workflow on a screen share or describes it in chat, and Caddi runs it as code across your tools, with exceptions routed to a named person.