Figure Eight
Figure Eight (formerly CrowdFlower, and originally Dolores Labs) was a human-in-the-loop machine learning and artificial intelligence company founded in San Francisco in 2007 by Lukas Biewald and Chris Van Pelt. Its platform turned unlabeled text, image, audio, and video into high-quality AI training data by combining automation with a distributed contributor workforce. The company exposed a RESTful, key-authenticated JSON API for programmatically creating, configuring, launching, and monitoring annotation jobs and multi-step workflows, and for downloading aggregated judgments and reports. Figure Eight was acquired by Appen in March 2019 for up to $300M; by 2020 its assets were fully integrated into Appen and the API is now served as the Appen Platform API at api.appen.com. This profile captures that surviving API surface. figure-eight.com now redirects to appen.com.
Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.
API Evangelist profiles Figure Eight the way a machine reads it — 17 machine-readable artifacts across 13 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 — Figure Eight scores 33.9/100 (thin), with a separate agent-readiness read of 56/100 (agent ready). 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 Figure Eight
Each block below is one kind of artifact we hold for Figure Eight. 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 13
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.
Figure Eight Account Info API
Manage account info.
Figure Eight Job Create/Update API
Create and update jobs.
Figure Eight Job Ontology API
Read and Update the Ontology for a job
Figure Eight Job Results API
Request rows, judgments, and reports.
Figure Eight Job Status API
Control job status.
Figure Eight Manage Job Data API
Load data to jobs and work with that data.
Figure Eight Manage Job Settings API
Manage various job settings.
Figure Eight Monitor Contributors API
Monitor contributor status and settings.
Figure Eight Workflow Data Upload/Download API
Upload data to run through a Workflow. Download reports.
Figure Eight Workflow Filter Rules API
Rules for routing data
Figure Eight Workflow Step Routes API
Manage Workflow Step Routes
Figure Eight Workflow Steps API
Manage Workflow Steps
Figure Eight Workflows API
Copy, launch, pause and resume workflows, check status and configuration values
Scroll within the panel for all 13 ·
MCP Servers 1
Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.
Model Context Protocol servers that expose these APIs to AI agents.
figure-eight-mcp.yml
MCP SERVEREvent Specifications 1
Not every API is request/response. AsyncAPI describes the event-driven and streaming side — the webhooks and channels — so the asynchronous half of the interface is documented the same way the synchronous half is.
AsyncAPI definitions for this provider's event-driven and streaming APIs.
Figure Eight Webhooks
ASYNCAPISecurity 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.
Resources
Every other property we hold for Figure Eight — 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 3
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 5
Pagination, idempotency, versioning, errors, and events
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
← All providers · Data indexed from github.com/api-evangelist/figure-eight · machine-readable index on apis.io