Dashboards as data.
dvt is an AI-native BI tool. Every dashboard is a versioned JSON spec that humans and AI agents like Claude author the same way. It queries Snowflake, Postgres, or BigQuery, updates live over API or MCP, and renders faithfully down to the last pixel.
The builder runs the spec format in your browser — no signup. Early access puts dvt on your own data; we reach out personally to set it up.
Watch dvt build a dashboard, then verify it.
One Claude Code session turns a live Postgres connection into a working dashboard, then traces a number on it back to the exact SQL, and through it to the table and column that produced it.
What makes dvt different
DADDashboards as Data
Every dashboard, page, and element is a versioned JSON document stored in dvt's database. Update via API, roll it back, or co-author it with Claude — live, no deploy required.
Fully customizable
No locked styles. Every visual property — down to the gap between an axis and its title — is an exposed, storable, spec-controlled parameter.
AI-native from day one
An MCP server lets Claude and other agents create, edit, and audit dashboards as first-class operations. Not a plugin — the architecture.
Documented spec, hosted convenience
The dashboard spec format is documented — plain JSON you can read, diff, and keep in version control. A spec that stays within the Core profile is portable across compliant renderers.
Spec-first tooling
A published JSON Schema will let editors autocomplete it, linters validate it, and AI agents generate and self-correct it programmatically. The spec is a first-class artifact.
Follow the build
dvt is in founding research. Leave your email and we'll reach out when there's something to see — no newsletters, no noise.