For logistics, delivery & field service

Service-area geography for delivery and field-service ops

Plan service areas, optimize depot placement, and visualize coverage gaps without standing up a routing stack. Drive-time areas, Voronoi territories, and density analysis on top of your own depot and order data.

What it looks like

A typical workflow for logistics, delivery & field service teams. Each line is one operation; together they take a few minutes and produce a published map plus a downloadable dataset.

# "Show me the gaps in our same-day coverage in the Southeast."

mcp.call("bulk_match_addresses", { records: depots })
  → 14 depots geocoded

const { batch } = await mcp.call("geo_isochrone", {
  points: depots.map(d => [d.lng, d.lat]),  // batch: 14 depots, one call
  minutes: [45], profile: "driving",
});

const { polygon: coverage } = await mcp.call("geo_union", { polygons: batch.map(b => b.contours[0]) });
const { shapes: covered } = await mcp.call("query_shapes_by_intersection", {
  geometry: coverage, collection: "us-zcta", version: "tiger-2024",
});
  → 1,247 ZIP codes covered · 894 ZIP codes in service-level gaps

mcp.call("create_report", {
  slug: "se-coverage-gaps", public: false,
  config: { collection: "us-zcta", version: "tiger-2024",
            datasets: [{ slug: "se-coverage", field: "covered", palette: "diverging" }] },
})
  → /v/se-coverage-gaps   internal review

What you can build

Drive-time service areas around depots — Specify your service-level in minutes, get one polygon per depot. Merge them for total coverage; subtract from a region for gap analysis.
Territory carve-up — Auto-assign every ZIP code to its closest depot. Surface where territories overlap and where they don't reach.
Density-based depot placement — geo_hotspot on order volume tells you where new depots earn their cost. Pair with drive-time areas to validate the service-level holds.
Customer / order overlays — Upload your last-90-days order spreadsheet, geocode, bucket by territory. Render to see where volume actually lives versus where capacity is.
Dispatch-friendly exports — Every territory exports as a standard map file. Drop into your routing engine or telematics system.

The tools you'd actually use

bulk_match_addresses
Depots / customer addresses → latitude/longitude

geo_isochrone
Drive-time polygon per depot, by service-level minutes

geo_union
Merge multiple polygons into one total-coverage polygon

geo_voronoi
Assign every point to its closest depot

geo_hotspot
Where order density justifies a new depot

query_shapes_by_intersection
Every ZIP code or county inside a coverage area

build_geojson
Export territories for downstream routing tools

describe_report
Claude narrates the coverage story

How it differs from the alternative

vs. Onfleet / Routific / a custom open-source routing stack: those plan individual routes. We plan the geography — where to put depots, what the service-level polygon looks like, where the gaps are. The two layers compose; we sit upstream of the routing step.

Pricing for logistics, delivery & field service teams

Mid-size ops teams run on Pro ($50/month) for multi-region sub-workspaces. High-volume planning workflows fit on Enterprise. Full pricing details.

From coverage gap to depot map in one chat.

Free tier covers a real pilot — usually one region.

Get an API key

The same toolkit also covers grassroots organizing platforms & campaign tooling · healthcare & life sciences · civic tech & journalism · real estate & property tech · retail, consumer brands & site selection · insurance & risk modeling · research, academia & think tanks · pollsters & survey research firms — one U.S.-geography surface for any team whose question comes down to where.