Cradle

The complete workspace built for AI agents.

One app on one shared, local-first database — and the AI agent lives in there too, with the same data, the same permissions and the same write path as a human.

Launching Autumn 2026

Desktop and web · self-hosted or managed cloud

The problem

A team's work is scattered across a dozen tools — and AI bolted on top can't see it.

The one technology that could absorb the fragmentation is the one the fragmentation locks out.

An expensive patchwork

Jira + Confluence + Slack + Zoom sit at the core of a $40–60-per-seat stack, pieced together with weak interoperability.

Integrations compound

Every attempt to tie the tools together hits the same wall: connectors multiply faster than anyone can maintain them.

AI is locked out

AI added on top of that stack sees a lossy, stale slice of one tool at a time — and can't act on any of it.

The product

One app. One shared database. AI built in.

Everything Jira, Confluence, Slack and Zoom do — in one place, synced live to every client, so everything is instant.

One shared, local-first database
  • Issues
  • Docs
  • Chat
  • Meetings
  • Calendar
  • Files
  • Notes
  • Code review
The AI agent lives in here too — same data, same permissions, same write path as a human.

What it feels like

Someone mentions a bug on a call. Cradle files it.

No "file this" click, no form, nothing to hunt for afterwards.

On the call

The meeting is transcribed live. A bug comes up in passing — nobody writes it down.

The agent catches it

When the call ends, the agent files the ticket — assigned, prioritized, in the right project.

Linked to everything

The ticket arrives already connected to the context.

  • The code — the pull request where the bug lives.
  • The docs — the spec that describes the intended behavior.
  • The chat thread — from two weeks ago, that everyone forgot about.

Every agent action leaves a receipt — logged, attributed, and revertible in one click.

Why only Cradle

Owning the substrate — the data, the permissions, the writes — is the moat.

Everyone is bolting AI on. No one owns what the agent needs.

AI layered on top of a stack

  • Lossy, stale context — one connector at a time
  • Permissions stitched fragilely across vendors
  • Read-only — it can summarize, not do
  • One more app on the pile, one more connector layer to maintain

The ceiling of every AI added on top.

AI inside the substrate

  • Live, full-fidelity context across every surface
  • One permission model — the agent sees what you'd let a teammate see
  • One write path shared by humans and agents — actions land atomically across surfaces
  • Every action logged, attributed, revertible

Properties of the data model — not features on top of it.

A chatbot on top doesn't retrofit this. Company brains inherit the fragmentation of the stack they sit on. Point tools each own one surface — their agents see the issues, or the docs, never the meeting, the thread and the PR at once. For the all-in-ones, it means rebuilding the core.

Progress

Built end to end. We run our company on it.

Building since July 2026 — with Claude Code in the loop. Public launch Autumn 2026.

All eight surfaces live

Desktop and web apps running on our infrastructure — issues, docs, chat, meetings, calendar, files, notes, code review.

AI fully operational

Meetings transcribed and summarized, follow-ups filed autonomously, tickets assignable to the agent, code tasks dispatched as pull requests.

Our own ML in production

The calendar's recommendation engine learns each person's own Bayesian model of what to work on next — trained on real outcomes, no LLM in the scoring path. The notebook runs a two-stage pipeline that triages raw notes into tickets, to-dos and docs.

How it's built

Client-side prediction, but for databases.

Multiplayer games stopped waiting for the server decades ago: the client predicts the result, the server confirms it. Cradle is built on Zero (Rocicorp), which does the same for application data — the UI acts on a local replica, and the server reconciles behind it.

Client LOCAL REPLICA

Reads answer from memory. Writes apply here first. 0 MS

zero-cache SYNC ENGINE

Streams only the rows your permissions allow. Pushes every change live — and confirms or rolls back each write.

Postgres SOURCE OF TRUTH

Plain relational data. One write path for humans and agents.

01

Instant by default

No loading states, no round trips — every click lands at memory speed.

02

Live by default

Every change streams to every client — the collaboration Linear and Figma made table stakes, without building it per feature.

03

Cheap by default

Reads are served from the client, so the cloud bill scales with writes, not with every keystroke.

Why now

Agents can finally do real work. Their workspace doesn't exist yet.

01

Capability arrived

Models crossed into real multi-step work — planning and acting, not just chatting. What they still lack is context and a safe write path.

02

Incumbents are retrofitting

Every incumbent is bolting AI chat onto systems built for a pre-agent world — so the retrofit inherits the fragmentation it was meant to fix.

03

The control plane is up for grabs

Claude, ChatGPT and GitHub's Copilot agent already file their work into issue trackers. The workspace is becoming where agents are directed and reviewed — and teams are re-choosing their stack for the AI era, before habits calcify.

Who it's for

"We're a great team with a great idea. What now?"

How do we become professional? How do we ship and operate? Cradle is the answer — the default before the stack is chosen.

Teams of 10–50

Teams that haven't bought into a stack — or whose buy-in is weak and hasn't calcified. Nothing to rip out, everything to gain.

Every product role

Not just engineers — the PMs, designers and leads working beside them share the same workspace and the same agent.

Self-hostable, EU-incorporated

Run it on your own box or on our managed cloud. Natively positioned for organizations that need an EU-based, self-hostable vendor.

The vision

The workspace your agents live in.

Every team is about to work alongside agents — and agents need a workspace built for them as much as people do. We're building it for both.

Launching Autumn 2026

We're looking for early teams to build with — come break it.