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PredictionIO

Apache PredictionIO is an open source machine learning server that lets developers and data scientists build, deploy, and serve predictive engines as web services. Originally the commercial product prediction.io from TappingStone, it was acquired by Salesforce in 2016, donated to the Apache Software Foundation, and graduated as a top-level Apache project before being retired to the Apache Attic. It exposes a REST-based Event Server for collecting event data and an Engine Query API for real-time predictions, built on Apache Spark, MLlib, HBase, Elasticsearch, and Akka HTTP, with official SDKs for Python, Ruby, PHP, and Scala/Java. This profile enriches the original portfolio-lead stub.

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 PredictionIO the way a machine reads it — 3 machine-readable artifacts across 2 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 — PredictionIO scores 18.4/100 (emerging), with a separate agent-readiness read of 14/100 (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 — 18.4/100 · emerging
Contract Quality 0.0 / 25
Developer Ergonomics 8.7 / 20
Commercial Clarity 0.0 / 20
Operational Transparency 1.7 / 13
Governance 0.0 / 12
Discoverability 8.0 / 10
Agent readiness — 14/100 · 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 4 / 4
Consent & Bot Identity 0 / 3

How we profile PredictionIO

Each block below is one kind of artifact we hold for PredictionIO. 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 2

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.

PredictionIO Event Server API

REST API for importing and querying event data used to train prediction engines. Authenticated with a per-app access key passed as the accessKey query parameter; JSON request/re...

PredictionIO Engine Query API

REST API exposed by a deployed prediction engine that responds to prediction queries in real time (POST /queries.json). Unauthenticated by default.

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.

Predictionio Authentication

2 schemes

SECURITY

Resources

Every other property we hold for PredictionIO — 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 2

Reference material describing how the API behaves

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 2

Pagination, idempotency, versioning, errors, and events

Build 3

SDKs, sample code, and the tooling you integrate with

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

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