# Arize AI vs Oak

Arize AI records 249,028 monthly visits with +3.2% month-over-month growth and Paid, Contact for Pricing pricing. Oak records 21,112 monthly visits with +36.5% growth and Contact for Pricing pricing.

| Metric | [Arize AI](https://openaitools.app/tool/arize-com) | [Oak](https://openaitools.app/tool/oak) |
| :--- | :--- | :--- |
| Website URL | https://arize.com | https://www.oak.id |
| Categories | Large Language Models (LLMs), AI Agent, AI Monitor, AI Developer Tools | Other |
| Pricing Model | Paid, Contact for Pricing | Contact for Pricing |
| Monthly Visits | 249,028 | 21,112 |
| MoM Growth Rate | +3.2% | +36.5% |
| Primary Market | United States | Israel |
| Direct Visits | 107,838 | 9,157 |
| Review Score | 4.6 | 4.2 |
| Saved Count | 1 | 0 |
| Supported Platforms | Website | Website |

## Arize AI

Arize is an AI engineering platform built for teams that run generative AI in production. It is split into two products: Arize AX, a managed environment for agent observability, evaluation, and experimentation, and Phoenix, an open-source tracing and evaluation library that teams can self-host when they need full data control. Both rely on OpenInference, the open-source semantic convention for generative AI tracing that the Arize team founded and that is built on OpenTelemetry.

The workflow follows three questions. Observe answers what an agent actually did by capturing every span, trace, and session; Evaluate answers whether quality is improving or regressing using span-level, trace-level, and session-level evals; Learn answers whether a proposed change will help by letting teams test prompts and harnesses before rollout. A datastore for GenAI traces (ADB) keeps data in open formats that connect to warehouses such as BigQuery, Databricks, and Snowflake, and an in-app AI engineering agent named Alyx surfaces issues and drafts review-ready fixes.

The platform integrates with dozens of models, frameworks, and tools, including OpenAI, Anthropic, Google, Amazon Bedrock, LangChain, LangGraph, LlamaIndex, CrewAI, and DSPy. Arize publishes compliance certifications including SOC 2 Type II, ISO 27001, PCI DSS, HIPAA, and GDPR, and supports cloud, hybrid, and self-hosted deployment.

**Pricing & Plans:** Arize uses a paid model with a free entry point: teams can start free or book a demo, while enterprise-scale usage, deployment options, and support are quoted through a contact-sales process. The open-source Phoenix project is free to self-host.

- **End-to-end tracing:** Capture spans, traces, and sessions across agents and LLM calls using OpenInference conventions built on OpenTelemetry, so instrumentation stays portable.
- **Scalable evaluation framework:** Run evaluations at span, trace, and session level to grade retrieval quality, tool use, and final answers across large production datasets.
- **Alyx AI engineering agent:** An in-product agent that inspects traces, diagnoses likely root causes, and proposes fixes that engineers can review before shipping.
- **Phoenix open-source toolkit:** Self-host the leading open-source tracing and eval tool when you need to keep trace data inside your own infrastructure.
- **Warehouse-native trace storage:** ADB stores traces in open formats that connect natively to BigQuery, Databricks, or Snowflake for joint analytics with business data.

**Strengths:** Covers the full loop of observe, evaluate, and improve rather than stopping at dashboards; Backed by OpenInference and OpenTelemetry standards, limiting vendor lock-in on trace formats; Strong enterprise posture with SOC 2, ISO 27001, HIPAA, and GDPR coverage plus self-hosting options; Integrates with a very wide set of models, frameworks, and agent SDKs

**Limitations:** Self-serve pricing is not published, so cost requires a sales conversation; The breadth of features can be overwhelming for small teams shipping their first LLM feature; Full value depends on disciplined instrumentation across the whole application

[Profile (Markdown)](https://openaitools.app/tool/arize-com.md)

## Oak

Oak describes itself as an AI-native identity operating system, born complete rather than retrofitted for AI or assembled through acquisitions. Its core argument is that AI has pushed identity to the frontline of cybersecurity: identity data is fragmented across tools, reviews are rule-based and periodic, service accounts and AI agent behavior create blind spots, and teams often can see risks without being able to remediate them. Oak's answer is to own the full stack, from seeing every identity in an environment to controlling what each one can do based on intent and context.

The foundation is an Identity Intelligence Layer that acts as one live source of truth — a single data model and graph for the whole identity security stack. On top of it, Oak governs human identities, machine and service accounts, and AI agents, so autonomous agents can be inventoried with accountable owners, effective permissions, and a record of who they act for. Because Oak is positioned as "connect any," it aims to integrate with whatever environments an organization already runs and adapt as new systems are added.

For enterprises that want hands-on help, Oak offers White Gloves: a dedicated identity services team that builds, migrates, and manages identity programs end to end, including enterprise system integration, rapid deployment, and customized solutions. The company targets enterprise scale, with the Oak Promise offering implementation hours and all connectors to qualified Fortune 500 organizations.

**Pricing & Plans:** Contact for pricing. Oak does not publish public self-serve tiers; pricing is quoted to qualified organizations. The company advertises an Oak Promise (up to 500 free human hours of White Gloves work and all connectors included) available to qualified Fortune 500 enterprises.

- **Identity Intelligence Layer:** A centrally owned identity platform where every identity is discovered, seen, and governed from one live graph rather than scattered tool-specific lists.
- **Agentic identity governance:** Inventory and govern autonomous AI agents and MCP servers as identities, with owners, scoped permissions, and records of who they act for.
- **Connect-any integrations:** Connect to the identity, security, and enterprise systems you already run, aiming for one data model instead of a patchwork of acquired tools.
- **White Gloves managed services:** A dedicated services team that builds, migrates, and manages identity programs end to end, from discovery through ongoing management.
- **Context-aware, continuous governance:** Go beyond quarterly, rule-based reviews with a live source of truth that reflects what is happening across the environment now.

**Strengths:** One live identity graph as a single source of truth instead of fragmented tools; Covers human, machine, and AI agent identities in one platform; White Gloves services team handles implementation, migration, and management; Connect-any integrations aim to fit existing enterprise environments

**Limitations:** Pricing requires contacting sales rather than self-serve checkout; Designed for enterprises, so smaller teams may find the scope heavy; Value depends on connecting Oak to your existing identity and security stack; Newer category, so buyers should validate fit through a demo

[Profile (Markdown)](https://openaitools.app/tool/oak.md)

## Frequently Asked Questions

### How do Arize AI and Oak compare in monthly traffic?

Arize AI has 249,028 monthly visits, while Oak has 21,112. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Arize AI has a month-over-month growth rate of +3.2%; Oak has +36.5%.

### How does pricing compare?

Arize AI: Paid, Contact for Pricing. Arize uses a paid model with a free entry point: teams can start free or book a demo, while enterprise-scale usage, deployment options, and support are quoted through a contact-sales process. The open-source Phoenix project is free to self-host. Oak: Contact for Pricing. Contact for pricing. Oak does not publish public self-serve tiers; pricing is quoted to qualified organizations. The company advertises an Oak Promise (up to 500 free human hours of White Gloves work and all connectors included) available to qualified Fortune 500 enterprises.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Duck.ai](https://openaitools.app/tool/duck-ai) | 26,431,539 | +10.7% | Free | Private AI chat from the makers of DuckDuckGo | [.md](https://openaitools.app/tool/duck-ai.md) |
| 2 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Excels at experiment tracking and model registry workflows, but is less purpose-built for real-time LLM production observability. | [.md](https://openaitools.app/tool/prompts.md) |
| 3 | [Dex — Personal CRM & LinkedIn Assistant](https://openaitools.app/tool/linkedin-gpt-assistant-by-dex) | 156,354 | +1.6% | Paid | The personal CRM that keeps your network warm — with your LinkedIn graph baked in | [.md](https://openaitools.app/tool/linkedin-gpt-assistant-by-dex.md) |
| 4 | [Defined.ai](https://openaitools.app/tool/definedcrowd-com) | 146,251 | -21% | Contact for Pricing | Enterprise AI training data, annotation and evaluation services | [.md](https://openaitools.app/tool/definedcrowd-com.md) |
| 5 | [Future AGI](https://openaitools.app/tool/future-agi) | 121,741 | -7.8% | Freemium, Usage-based | Includes integrated guardrails and simulation tools, but is less mature for large-scale enterprise production telemetry monitoring. | [.md](https://openaitools.app/tool/future-agi.md) |
| 6 | [Maxim AI](https://openaitools.app/tool/maxim-ai) | 121,351 | +10% | Contact for Pricing, Free Open Source | Features strong testing and prompt evaluation tools, though its monitoring interface is less oriented towards massive telemetry streams. | [.md](https://openaitools.app/tool/maxim-ai.md) |
| 7 | [PromptLayer](https://openaitools.app/tool/promptlayer) | 85,899 | -4.6% | Free Trial, Contact for Pricing | Focuses heavily on prompt management and versioning control, whereas Arize prioritizes end-to-end tracing and ML observability. | [.md](https://openaitools.app/tool/promptlayer.md) |
| 8 | [Invoxia](https://openaitools.app/tool/invoxia-com) | 85,204 | -32.5% | Paid | GPS trackers and pet health devices that watch over what matters | [.md](https://openaitools.app/tool/invoxia-com.md) |
| 9 | [Confident AI](https://openaitools.app/tool/confident-ai) | 83,400 | -3.3% | Freemium, Paid, Contact for Pricing | Offers comprehensive LLM evaluation and unit testing via DeepEval, but lacks Arize's deep production monitoring infrastructure. | [.md](https://openaitools.app/tool/confident-ai.md) |
| 10 | [LangWatch](https://openaitools.app/tool/langwatch) | 52,098 | +73% | Contact for Pricing | Agent observability, evals and governance for AI platform teams | [.md](https://openaitools.app/tool/langwatch.md) |

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Source: https://openaitools.app/compare/arize-com-vs-oak

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