Roadmap
Boost.space is the synced data layer where humans and AI agents run a business together. Everything below serves one arc: your business data becoming something an agent can understand, act on, and be trusted with.
In development
An automation that starts when something outside Boost.space posts to it.
An agent changing a whole selection of records in one pass instead of one call at a time.
Decide which modules an API token or an AI connection is allowed to reach.
More of the system it can operate, and more work it finishes end to end.
Agents learn what a field means, not only what it contains.
The whole app revisited — the same product, easier to look at and to move around in.
The four-language family completes, from the same generated pipeline.
Next up
The shape of your whole system — and what an agent sees when it looks at it.
An agent as a member of your space, with its own permissions and audit trail.
Find the record you meant, not the one that happened to match a keyword.
Fewer concepts to learn, less to configure, a shorter path to a system that works.
Exploring
Say what must stay true — never oversell, one clean record per customer — and get proof it stayed true.
Small writes flow; big or irreversible ones wait with a dry-run diff and their blast radius.
A proven schema with its automations and views, fitted by an agent to the data you already have.
The dashboard you asked for, wired to your data and living inside your permissions.
Answer a question about your data once, and it becomes a rule you are never asked about again.
Shipped recently
| Feature | What it does |
|---|---|
| Code automations | Your own Python as an automation step, in a sandbox — written by you, or by an agent that tests it against your data before it ships |
| More capable MCP tools | Connected agents now build structure too — modules, spaces, field groups, fields — put files on records, and ask for a secret through a form instead of the conversation |
| Agent Chat | The built-in agent: ask, act, and build automations in plain language |
| Rollup, Formula and button fields | A value aggregated across a record's linked records, one computed from the fields beside it, and an action button on the record |
| Vector database | Spaces embedded for meaning, so retrieval works by intent — on selected systems |
| Build a module with AI | Describe what you want to track; AI generates the module and its typed fields |
| TypeScript and Python SDKs | Typed clients generated from the REST API spec |
| Docs built for agents | Raw markdown per page, an llms.txt index, and a docs MCP endpoint |
The full record lives in the release notes for what shipped in the product, the API changelog for every public API change, the MCP changelog for the server agents connect to, and the SDK changelog for client releases.
Direction, not delivery dates — priorities follow what customers ask for. Waiting on something above? Tell us.
