The story
You already know Them.
Every company has one. This is the story of keeping their expertise, and the company we are building around it.
The team
Once upon a time, there was a team full of people who were very good at what they did.
Each had learned things no handbook could teach: what to notice, when to adapt, and how to solve the problems no process had planned for.
The scattering
But their work lived in far too many places.
Conversations were in one tool, documents in another, and every AI assistant worked alone with only a small piece of the story.
The missing thinking
The files were easy to find. The thinking was not.
New teammates could see what the team had done, but still needed the experts to explain why it worked and what to do next.
A bright idea
Then we had a bright idea.
What if people and AI teammates could work from shared context, while keeping the tools they already use? That idea became Them AI.
Multiplayer
Now the agents could work together, too.
They shared context and posted their work into the same room, while people guided the decisions that mattered.
The learning
One project's lessons could help the next.
A reviewed decision could become memory. The method behind it could become a skill. A teammate's training stayed with that teammate until the team reviewed a method for wider use.
The next chapter
Work was always multiplayer. AI finally is.
People brought judgment. AI teammates helped prepare the work. Each reviewed lesson gave the next person or teammate a better place to start.
One memory
Keep the knowledge. Keep the reasons behind it.
People bring their experience. Agents bring their tools. Shared memory keeps the facts and decisions the team approves, with reusable skills alongside it.
Your company
Its processes
how the work runs
the company's own · governed
Them AI
One company memory
citedownedreviewed
ApproveReject
Human review before draft knowledge becomes approved memory
Its skills
reviewed methods to use again
the company's own · reviewable
Its people · past, present and future
AI teammates · built and trained here
External agents · connected through MCP
Claude
CursorIts rooms
a room for each project · people and AI teammates sharing context · organization-wide human access
Its connectors
Supported source connectors · document uploads · public pages · setup varies by source
A room does not restrict access for individual workspace members. Read the current access boundaries.
Each teammate carries its own job, training and reviewed skills.
The company keeps approved knowledge, with processes and skills beside it. People and AI teammates can build on that shared context. When someone leaves, the work your team has agreed to keep can still help.
Governed
The AI drafts it. The human decides it. The memory compounds.
Bring context
Connect a supported source, upload a document, or supply a public page. Start with material your workspace members are authorized to see.
Prepare the knowledge
Turn source material into draft facts and decisions. Keep the supporting references and assign someone to review them.
Assist
Draft from approved context, then check the sources and reasoning. AI can still make mistakes.
Keep what holds up
A person with review permission approves the useful decision as memory. Repeatable methods can be reviewed separately as skills.
A policy says what is allowed. A decision with its evidence explains why the team applied it that way. Keep both, so the next person does not have to start from the file alone.
The road
Three acts, one brain.
What the current beta does, what we are exploring, and the longer-term ambition. Future ideas are not availability commitments. The details live in the FAQ.
An AI team with shared context
Build and train AI teammates, work together in rooms, and review the memory and skills worth keeping. Connect supported sources and give compatible external agents scoped MCP access. Human room and memory access is organization-wide.
Help around the conversation
We are developing Call assist to prepare the brief, surface automatic suggestions during the call, and help with the follow-up. Relevant past cases, policy and useful questions should appear as the conversation unfolds. Room bridges to Slack and Microsoft Teams are planned. Live meeting audio and automatic updates in outside tools are not part of the current beta.
Earned autonomy
The long-term question is where a proven method could safely need less supervision. That would require explicit controls, clear accountability, and evidence it works. It is an ambition, not a current feature or a reason to skip human review in the beta.
Individual expertise in.
Collective intelligence out.
Why we build
More room for judgment and creation.
We build Them AI to help teams reuse what they know, so people spend less time explaining the same work and more time applying their judgment to what comes next.
The promise
The knowledge your people choose to share can keep helping the people who come next.
Them, together.
People move on. Expertise should stay and evolve.
Start with one recurring task, the sources behind it, and the person who knows what a good answer looks like.
Mac-only for now. Free during the beta (invite-only).
Building with us or backing us: hello@usethem.ai