Arize AI
Arize AI is an AI engineering and observability platform for LLM applications, agents, and traditional ML systems. The commercial Arize AX platform (with Generative and ML & CV variants) provides tracing, evaluation, experiments, prompt management, and the Alyx AI engineering agent, built on the OpenInference OpenTelemetry conventions. Phoenix is the open-source counterpart used by tens of thousands of developers for local tracing, evaluation, and prompt iteration. Arize is vendor- and framework-agnostic with 30+ instrumentation providers and an OTLP-native ingestion path.
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles Arize AI the way a machine reads it — 38 machine-readable artifacts across 5 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 — Arize AI scores 45.5/100 (developing), with a separate agent-readiness read of 31/100 (agent aware). 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 2026-08-17 · rubric v0.11.0
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How we profile Arize AI
Each block below is one kind of artifact we hold for Arize AI. 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 5
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.
Arize AX
Arize AX is the commercial AI engineering platform covering tracing, evaluation, experiments, prompt management, annotations, and dashboards for LLM applications and agents. Bui...
Phoenix
Phoenix is Arize's open-source LLM observability platform offering local tracing, evaluation, experiments, and prompt iteration. Distributed as a Python package with a local UI,...
OpenInference
OpenInference is Arize's open-source set of OpenTelemetry conventions and instrumentation libraries for LLM applications, agents, RAG pipelines, and frameworks. Provides Python ...
Alyx
Alyx is Arize's AI engineering agent that helps developers debug traces, create evaluators, build dashboards, and compare experiments inside the Arize AX platform.
Arize AI Traces API
OTLP trace ingestion
Open Collections 3
Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
API Collection
OPEN COLLECTIONArize AX OTLP Ingestion Traces API
OPEN COLLECTIONArize AX OTLP Ingestion API
OPEN COLLECTIONPricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Arize Ai Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Arize Ai Finops
FINOPSFeatures 8
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.
LLM Tracing
Capture spans for LLM calls, retrieval steps, tool invocations, and agent loops via OpenInference OTel.
LLM Evaluation
Run built-in and custom evaluators on production traces, experiments, and datasets.
Experiments
Compare prompt and model variants over curated datasets with structured logging.
Prompt Management
Playground, hub, builder, and versioning for prompts used across applications.
Annotations
Capture human feedback on traces and outputs for evaluator development and dataset curation.
Alyx AI Engineer
AI assistant for debugging, evaluator authoring, dashboarding, and experiment comparison.
ML Monitoring
Drift, data quality, and performance monitoring for traditional ML and computer vision models.
Phoenix OSS
Open-source local tracing and evaluation tool runnable in notebooks or self-hosted.
Scroll within the panel for all 8 ·
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.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 5
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
LLM Application Observability
Monitor production LLM applications with traces, evaluators, and alerting.
Agent Debugging
Inspect multi-step agent runs across tool calls and intermediate reasoning.
RAG Quality Monitoring
Evaluate retrieval and generation quality over time in RAG systems.
ML Monitoring
Detect drift and degradation in classical ML and CV models.
Local Development
Iterate on prompts and evals locally with Phoenix before shipping to Arize AX.
Integrations 11
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
OpenAI
OpenInference instrumentation for OpenAI Chat Completions, Assistants, and Responses APIs.
Anthropic
Instrumentation for Anthropic Claude models.
LangChain
Instrumentation and evaluators for LangChain chains and agents.
LangGraph
Trace and evaluate LangGraph stateful agents.
LlamaIndex
Instrumentation for LlamaIndex RAG pipelines.
CrewAI
Trace CrewAI multi-agent crews.
DSPy
Trace and evaluate DSPy programs.
Vercel AI SDK
Instrumentation for Vercel AI SDK applications.
OpenTelemetry
OTLP-native ingestion compatible with any OTel collector or backend.
Bedrock
Instrumentation for AWS Bedrock model invocations.
Vertex AI
Instrumentation for Google Vertex AI and Gemini.
Scroll within the panel for all 11 ·
Resources
Every other property we hold for Arize AI — 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 3
Reference material describing how the API behaves
Agent Surfaces 2
MCP servers, agent skills, and machine-readable catalogs
Build 4
SDKs, sample code, and the tooling you integrate with
Access & Security 3
Authentication, authorization, and security posture
Operate 3
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 3
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/arize-ai · machine-readable index on apis.io
This is an independent, third-party profile of Arize AI, published by API Evangelist. We do not operate, host, resell, or support these APIs, and we are not affiliated with or endorsed by the company unless stated above. Everything here is built from publicly available information — the company's own site, developer portal, documentation, public repositories, and the specifications it publishes for public use. Nothing is obtained by breaching a system, defeating an access control, or using credentials.
The Kin Score and Agent Readiness rating are independently calculated assessments of a company's public API artifacts, scored against a published rubric. They are not certifications, endorsements, security assessments, or audits.
Corrections, re-scores, and removal are free — no partnership or purchase required, and you do not need to justify the request. A removed company is recorded as unrated, never scored zero for having asked. Acknowledgement within one business day; removal within two.
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