People and AI teammates.
One multiplayer platform.

Build an AI team around the way your company works. Give teammates a job, bring them into shared rooms, and turn reviewed work into memory and skills. And get work done.

Join the waitlist See a team at work

Mac-only for now. Free during the beta (invite-only).

The Them view of the app, with a shared room and a prepared reply awaiting human approval

Your people and AI teammates, working together in shared rooms. Prepared work stays open for human review.

Multiplayer by design.
Keep what your team learns.

Who is Them?

You already know Them.

Them is who...

sees problems differently from everyone else
has years of judgment your company depends on
knows how things work beyond the process documents
remembers why important decisions were made
has expertise that would take years to replace
knows what to do when there is no playbook

They are the person everyone turns to when the obvious answer is not good enough. People like Them help build companies. Them AI helps their expertise keep building, and pass on to the next employees and the next AI teammates.

The problem

Transferring memory to AI is not enough. Expertise should also follow.

Your company saves the work, but not the thinking behind it.

The presentation survives, but not the reasoning behind it.

The process document explains what usually happens, but not what actually happens.

When a customer asks for an exception or when a complex problem shows up, a decision has to be made without enough information. That is when experience matters.

But experience lives in people. In corrections. In conversations. In hundreds of decisions nobody thought to document. When those people leave, change roles, or simply forget, the company keeps the files but loses judgment.

A prepared reply and a workflow waiting for human approval in Them AI

Support deskReply review

The customer cannot find their receipt. The team prepares a reply, keeps the payment settlement check open, and asks Maya to confirm the next step with billing before anyone sends it.

Riley · support teammateMaya Chen · billing checkReply review · awaiting approval

Files can tell an AI what happened, but Them AI helps it learn how your best people handled it.

The multiplayer workspace

Humans and AI in the same room. One workspace. Many minds.

Create a room for a project and bring in the people who understand it along with AI teammates that can help. Then let them work together with the same context.

Rooms hold conversations and data. AI teammates carry their own training. Shared company memory gives them a common starting point. Explore rooms and access boundaries or find your use case.

People and AI teammates working around one table in a shared studio, with the Them AI heart logo on the wall
01

AI teammates

Give Riley the support job and Jamie the handoff. Choose their models, add instructions, and teach each teammate through reviewed corrections.

Explore AI teammates →
The AI teammates directory in Them AI, with search, status filters and named teammates
02

Workflows

Prepare the handoff, review the draft, then share it in the room. Turn those steps into a workflow with a person at the decision.

Explore workflows →
The Workflows screen in Them AI, with saved workflows and their review steps
03

Company memory

Keep the verified billing decision with its source and owner. The next teammate can use the approved record instead of asking the team to explain it again.

Explore company memory →
Company memory in Them AI, showing source records, owners and review status
04

Skills

Teach the check behind the answer: confirm payment status before promising a refund. Review the method before reusing it.

Explore skills →
Skills and teammate training rules in Them AI with their scope and approval status
05

Rooms

Keep the ticket, policy, conversation and draft in Support desk. Give people and assigned AI teammates a common place to work from.

Explore rooms and data access →
A Them AI room showing a prepared draft waiting for human review
06

External agents

Let a configured Claude or Cursor client use Them AI knowledge through MCP. Give each connection its own key and retrieval scope.

Explore integrations →
External agent connections in Them AI with their key permissions and retrieval scope
07

Call assist

An AI teammate designed to suggest what to ask, check or explain while you are on the call. Company knowledge, right beside the conversation.

Explore Call assist →

The desktop overlay

Keep the call in view.

We are building live suggestions that appear in the overlay as the conversation unfolds. Relevant past cases, policy guidance and the next useful question, without typing every prompt.

Them AI Call assist collapsed to a compact bar with controls to expand or return to the workspace
Riley in the Them AI Call assist overlay, with Support desk selected and notes about a customer's missing payment receipt
08

Room bridges

Planned

One room, several destinations. Planned bridges will connect the same room to multiple Slack or Microsoft Teams conversations.

Explore room bridges →

Them AI room

Support desk

RileyJamieYour team
  • SlackSupport team
  • SlackAccount team
  • Microsoft TeamsCustomer success
One Them AI room. Multiple conversations in the tools your team uses.

A teammate for research. Another for the draft.
Your people make the final call.

Your people guide the thinking. Correct the mistakes. Make the final call.

When one person improves the way a problem is solved, the whole team can benefit from it.

How Them AI learns

The learning loop. Let one project teach the next.

Review what worked, keep the evidence, and write down the method. Learning here means reusable knowledge and instructions, not retraining the underlying AI model.

A prepared reply and a workflow waiting for human approval in Them AI

Every correction should fix more than one answer.
Review the lesson, then use it in the next piece of work.

Different jobs. Shared company knowledge.

Your AI team

Riley prepares the support reply. Jamie handles the handoff. Each teammate has its own job, room and training, with shared company knowledge to work from.

Five illustrated Them AI teammates working together: Riley checks notes, Jamie shares a folder, Parker writes, Morgan plans a story and Sage reads with a bird perched on its head

Explore a team

Different jobs. One piece of work.

Your people direct the teammates and make the final call.

Support deskRoom

A billing question needs more than a quick reply.

Start withTicket notes + billing records + approved policy

  1. RileyCustomer support

    Prepare the reply. Flag the payment check.

    Gemini
  2. SageTeam knowledge

    Find the policy and the reason behind it.

    Claude
  3. JamieCustomer handoffs

    Prepare a handoff for the billing team.

    OpenAI

Shared company memoryApproved knowledge in common. A model and reviewed training for each teammate.

Support lead decides

Check the current payment record, review the draft, and send the answer from your support tool.

See the support workflow
What would you teach a teammate?

“Confirm payment settlement before promising a receipt or refund.”

Explain the correction to a teammate. Review its proposed training rule before reuse. See how teaching works →

Proposal deskRoom

Turn the discovery call into a proposal you can stand behind.

Start withDiscovery notes + approved offer + relevant past decisions

  1. ParkerProposals

    Draft the scope around the buyer’s needs.

    Claude
  2. SageTeam knowledge

    Find the approved terms and earlier decisions.

    Gemini
  3. JamieCustomer handoffs

    Give the account team a clear next step.

    OpenAI

Shared company memoryApproved knowledge in common. A model and reviewed training for each teammate.

Account lead decides

Confirm scope, pricing and commitments. Share the reviewed proposal and update the CRM.

See the sales workflow
What would you teach a teammate?

“Separate an approved offer from a customer request that still needs agreement.”

Explain the correction to a teammate. Review its proposed training rule before reuse. See how teaching works →

Client engagementRoom

Use the firm’s experience without losing the client’s context.

Start withClient brief + assigned room records + shared company methods

  1. SageTeam knowledge

    Find earlier reasoning and check its relevance.

    Gemini
  2. ParkerProposals

    Turn the brief into a proposed work plan.

    Claude
  3. MorganMarketing

    Build the client narrative around evidence.

    OpenAI

Shared company memoryApproved knowledge in common. A model and reviewed training for each teammate.

Engagement lead decides

Check what applies to this client. Review the evidence, recommendation and final deliverable.

See the consulting workflow
What would you teach a teammate?

“Explain where a past approach fits this client, and where it does not.”

Explain the correction to a teammate. Review its proposed training rule before reuse. See how teaching works →

Customer careRoom

Resolve the order question. Keep the promise realistic.

Start withOrder notes + return policy + product information

  1. RileyCustomer support

    Prepare a reply grounded in the return policy.

    Gemini
  2. JamieCustomer handoffs

    List what fulfilment needs to confirm.

    OpenAI
  3. MorganMarketing

    Draft a clearer explanation for shoppers.

    Claude

Shared company memoryApproved knowledge in common. A model and reviewed training for each teammate.

Customer care lead decides

Verify the current order and stock details. Decide on the remedy and make the update in your store tools.

See the ecommerce workflow
What would you teach a teammate?

“Check order eligibility and stock before offering a replacement.”

Explain the correction to a teammate. Review its proposed training rule before reuse. See how teaching works →

One customer question. A team behind the answer.

Know what happened.
Decide what happens next.

A customer changed plans. The workspace updated, but the invoice did not. Your support rep brings the question into a room and puts the right teammates to work.

The question

“My plan changed, but the invoice still shows the old one. Was I charged twice?”
ZendeskStripe

Bring the ticket and billing records as notes or an export. Add the reviewed billing policy to the room.

Explore the support workflow →
  1. 01 · Ask Riley

    Separate facts from open checks.

    Riley uses the policy to prepare a reply. A plan change is not proof of a second charge, so payment status stays an open check.

  2. 02 · Ask Jamie

    Give billing a useful handoff.

    The rep asks Jamie to turn those checked facts into a handoff: the issue, the evidence, and what billing needs to confirm.

  3. 03 · Maya makes the call

    Check the record. Send the answer.

    Maya verifies the current invoice and payment record, reviews the draft, and sends the reply from the support tool.

Human control

You decide what it learns.

Review the lesson

A draft is not company guidance. A reviewer decides what becomes approved memory or a reusable skill.

How skills are reviewed →

Know what is shared

People in a workspace can read its rooms. AI teammates use shared approved company memory plus their assigned room context.

Understand room access →

Scope outside agents

MCP connections have their own keys and permissions. External tools control their own actions and approval steps.

Connect an external agent →

Start with one team.
One real piece of work.

Bring a support question, a sales handoff, or a client brief. Start with the sources and the person who knows what a good answer looks like.

Mac-only for now. Free during the beta (invite-only). Want to shape a workflow with us? Plan a pilot.

People move on. Expertise should stay and evolve.