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4M Analytics website screenshot

4M Analytics

4M Analytics is a utility AI mapping company that builds the "Google Maps of underground infrastructure." Its platform compiles millions of scattered public utility records into a single, validated subsurface map, using an AI conflation engine, satellite imagery, computer-vision object detection, and geospatial experts to identify known and unknown underground utilities before design and construction. Teams use 4M to speed utility record research, reduce excavation risk, and avoid costly conflicts during planning, pre-construction, and design. The platform exposes utility data through the 4M web application (4Map) and a WFS (OGC Web Feature Service) API that streams line and point utility features directly into GIS and CAD tools (ArcGIS, QGIS, AutoCAD, Autodesk, Bentley), with exports to PDF, SHP, KML, GPKG, DWG, DXF, and DGN. Founded in 2019 (Austin, TX and Tel Aviv) and backed by Insight Partners, 4M is added to the API Evangelist network and enriched here.

human only

More than an index entry, but the surface is still mostly links rather than artifacts — the cohort most likely to move a full band from modest, well-targeted work.

Kin Score

API Evangelist profiles 4M Analytics the way a machine reads it — 3 machine-readable artifacts across 1 API, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.

Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — 4M Analytics scores 25.3/100 (emerging), with a separate agent-readiness read of 10/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.

Kin Score

This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 25.3/100 · emerging
Contract Quality 0.0 / 25
Developer Ergonomics 10.4 / 20
Commercial Clarity 6.8 / 20
Operational Transparency 0.0 / 13
Governance 0.0 / 12
Discoverability 8.0 / 10
Agent readiness — 10/100 · human only
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
MCP Server 0 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3

How we profile 4M Analytics

Each block below is one kind of artifact we hold for 4M Analytics. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.

APIs 1

Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.

Individual APIs this provider publishes, each with its own machine-readable definition.

4M WFS API

The 4M WFS API is an OGC Web Feature Service that streams 4M's validated subsurface utility data (line and point features) in real time into GIS platforms such as ArcGIS and QGI...

Security Posture 2

Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.

Authentication, domain security, vulnerability disclosure, and trust-center signals.

4M Analytics Authentication

apiKey · 1 scheme

SECURITY

4M Analytics Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Every other property we hold for 4M Analytics — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.

Documentation 2

Reference material describing how the API behaves

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Access & Security 2

Authentication, authorization, and security posture

Operate 1

Status, limits, changes, and where to get help

Commercial 2

Pricing, plans, and the legal terms of use

Company 2

The organization behind the API

← All providers · Data indexed from github.com/api-evangelist/4m-analytics · machine-readable index on apis.io