DevTools · AI-klaar · Open source
Een framework-onafhankelijke grafiekengine met eersteklas DevTools, een AI-leesbare ChartContext op elke grafiek, en één TypeScript-API voor SVG, Canvas en WebGPU - voor React, Vue, Svelte, Angular of gewone web components.
Een echt DevTools-paneel: live status, lay-out, rendering en hit-testing, verschillen tussen renders, profilering en toegankelijkheidsaudits.
Elke grafiek levert een gestructureerde ChartContext - een samenvatting in gewone taal die een AI-agent kan lezen en via MCP kan aansturen.
Diezelfde context is een echt tekstalternatief voor schermlezers. Ingebouwd, niet achteraf toegevoegd.
Voorspelling, anomaliedetectie en narratie draaien in de browser. Geen server, geen upload. MIT-licentie.
Every block below is a real michi-vz chart (a line, a scatter, a radar, an area), fed data until it turned into Michi, our cat in Geneva. The serious reasons start right below.
Seventeen chart types, from stacked bars to gap charts to the fountain, drawn by one engine. Here are the six ideas michi-vz cares about most, each one a live chart, not a screenshot.
The sentence beside this chart was written by the chart itself. Every michi-vz chart emits a structured ChartContext that an AI agent can query, a screen reader can speak, and a test can assert on. Pixels for people, structure for everything else.
How machines read these charts →Ontwikkelaarservaring als kern
Bouw grafieken in minuten, inspecteer ze in seconden en schaal van prototype naar productie met dezelfde API. Kies een grafiek op basis van je vraag - elke kaart is een live component op echte data.
Trends over time across one or many series. The dashed run is a gap in the data (detectGaps).
A forecast fan: history, a dashed forecast median, and nested confidence bands that widen with the horizon.
Part to whole over time: how each component's share of a stacked total shifts.
The relationship between two numeric variables; bubble size encodes a third.
Min to max bands per series: forecasts, confidence intervals, or observed ranges.
Stacked columns per period, linked by ribbons that trace each category over time.
Compare several entities across a shared set of axes at a glance.
Stacked vertical bars per category, with an explicit missing-data guard.
Two overlaid horizontal sub-bars per label: a based vs compared value.
Two full-bandwidth overlapping columns per category, with a change arrow above each pair - the vertical sibling of Comparable Bar.
Diverging bars from a centre line: population pyramids and tornado charts.
Cumulative horizontal segments per row with end-cap circles at each step.
Two values per label joined by a gap bar that emphasises the difference.
Hierarchical tiles sized by value; each splits into two parts (e.g. realized vs untapped). Falls back to a stack on narrow screens.
Slices sized by share of a whole; set innerRadiusRatio for a donut. Per-slice % labels and an optional legend.
Circles sized by value, pulled into a cluster by gravity; each can split into a realized core inside a lighter untapped ring.
Flows between nodes laid out in columns; each band's thickness is the flow value. Built on d3-sankey.
A Jet d'Eau: apex height is the value, the blooming plume is the uncertainty. Categorical x = snapshot/comparison, temporal x = trend.
A world/region choropleth: your own GeoJSON, shaded by a threshold colour scale or an explicit category map. 13 d3-geo/d3-geo-projection projections.
A force-de-overlapped bubble map: you supply lng/lat per item, a one-shot simulation pulls overlapping circles apart. An optional muted backdrop landmass is available; dot-only by default.
A radial cluster()/dendrogram: leaves sit equidistant from the centre, with circles sized at both the group and leaf level. Labels adapt (abbreviate, rotate, or hide) as leaf density grows.
