Descartes Labs
Descartes Labs was a Santa Fe, New Mexico geospatial intelligence company founded in 2014 as a spin-out from Los Alamos National Laboratory. The company built the Descartes Labs Platform, a cloud-native geospatial data refinery and analytics environment combining a petabyte-scale satellite imagery archive (Landsat, Sentinel-1/2, MODIS, NAIP, PlanetScope, SkySat, commercial radar, NEXRAD weather radar, plus client-uploaded data) with a Python client library, JupyterHub-based workbench, and distributed compute for training and running deep learning and remote-sensing models at scale. Customers in agriculture, mining, energy, defense, insurance, and the U.S. government used the platform to build production geospatial machine learning pipelines covering crop forecasting, mineral exploration, infrastructure monitoring, methane detection, wildfire response, and ESG reporting. The Platform exposed a Catalog (imagery, bands, products, blobs, events), a Compute service (containerised functions, jobs, schedules), a Vector service (tabular and geospatial features), Dynamic Compute (lazy raster algebra and tiling), Auth, and a `descarteslabs` CLI. In October 2024, EarthDaily Analytics — backed by Antarctica Capital — acquired Descartes Labs and the Descartes Labs Government, Inc. subsidiary, folding the team, customers, and platform into the EarthDaily Constellation programme. The product was rebranded EarthOne in 2025; the `descarteslabs` Python package has been formally discontinued in favour of `earthdaily-earthone` (v5.x), the github.com/descarteslabs organisation has been renamed to `dlarchives`, www.descarteslabs.com is now a parked domain, and the docs.descarteslabs.com developer portal has been retired in favour of EarthDaily-hosted EarthOne documentation. This catalog entry preserves the historical Descartes Labs Platform surface as an archive — see the EarthDaily / EarthOne profile for the active product.
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.
API Evangelist profiles Descartes Labs the way a machine reads it — 22 machine-readable artifacts across 6 APIs, 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 — Descartes Labs scores 17.7/100 (emerging), with a separate agent-readiness read of 7/100 (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
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Descartes Labs
Each block below is one kind of artifact we hold for Descartes Labs. 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 6
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.
Descartes Labs Platform (Archived)
The historical Descartes Labs Platform — a managed geospatial data refinery and analytics environment exposing imagery catalog, raster access, vector tables, compute functions, ...
Descartes Labs Catalog API
The Catalog organised all imagery and derived data on the Platform. Products group Bands which group Images; Storage Blobs hold arbitrary file artefacts; Events emit notificatio...
Descartes Labs Compute API
The Compute service ran user-supplied Python code as containerised Functions against the imagery archive at scale. Users defined a `Function` (CPUs, memory, environment, Docker ...
Descartes Labs Vector API
The Vector service hosted tabular and geospatial feature data as Tables of typed columns with `uuid` identifiers and ipyleaflet visualisation. Supported property filtering (incl...
Descartes Labs Dynamic Compute API
Dynamic Compute was the Platform's lazy map-computation engine for interactive raster algebra and tile rendering in notebooks. Expressions over imagery products (band math, mosa...
Descartes Labs Auth API
The Auth module handled token-based authentication against app.descarteslabs.com — OAuth login flow, refresh tokens, and the user namespace claim that served as a global identif...
Features 15
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Scroll within the panel for all 15 ·
Security Posture 1
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.
Resources
Every other property we hold for Descartes Labs — 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.
Get Started 1
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Build 10
SDKs, sample code, and the tooling you integrate with
Scroll within the panel for all 10 ·
Access & Security 1
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Company 1
The organization behind the API
Other 6
Properties that don't map to a standard resource type
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