# Arize AI vs Nadi

Arize AI records 249,028 monthly visits with +3.2% month-over-month growth and Paid, Contact for Pricing pricing. Nadi records 60 monthly visits with -74.9% growth and Free Trial, Freemium, Paid pricing.

| Metric | [Arize AI](https://openaitools.app/tool/arize-com) | [Nadi](https://openaitools.app/tool/nadi) |
| :--- | :--- | :--- |
| Website URL | https://arize.com | https://nadi.pro |
| Categories | Large Language Models (LLMs), AI Agent, AI Monitor, AI Developer Tools | AI Monitor, AI Assistant, AI Developer Tools |
| Pricing Model | Paid, Contact for Pricing | Free Trial, Freemium, Paid |
| Monthly Visits | 249,028 | 60 |
| MoM Growth Rate | +3.2% | -74.9% |
| Primary Market | United States | Malaysia |
| Direct Visits | 107,838 | 24 |
| 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)

## Nadi

Nadi installs into a PHP project in three steps: require the package, run the artisan installer, then deploy. From there it collects ten categories of backend issues — exceptions, queries, queue jobs, HTTP requests, notifications, scheduler runs, commands, gates, logs and mail — each with full stack traces, deduplication and the list of affected users. A JavaScript SDK adds the frontend half: Core Web Vitals, session tracking, JS error capture, page loads, memory, network timings and rage-click detection, with source map deobfuscation so browser stack traces stay readable.

Alerting is handled by a rules engine that supports Slack, Microsoft Teams, Telegram, webhooks and plain email, along with acknowledgement, resolution and alert history. Larger teams get organization-level data isolation, role and permission groups, project groupings, invitations and audit logs, which makes the platform viable where compliance or multi-tenant separation matters. The current release is versioned 2.0.0 and advertised as production ready.

Pricing is unusually transparent for a monitoring tool: a free tier for individuals and side projects, a Pro tier aimed at startups, and an Enterprise tier with SSO, SAML and a 99.9% uptime SLA. The company states that 2,000+ developers use it and that everything can be set up in about two minutes, with a 30-day money-back guarantee on paid plans.

**Pricing & Plans:** Free tier at $0 with 3 projects, 10,000 events per month, error tracking, RUM, traces, email notifications and 2 team members. Pro is $12/month (or $10/month billed yearly), with unlimited projects, 100,000 events per month, Slack/Teams/email alerts, 15 team members and priority support. Enterprise is custom-priced with unlimited events and projects, custom integrations, SSO/SAML, unlimited members and a 99.9% SLA. All plans include a 14-day free trial and a 30-day money-back guarantee.

- **Backend error tracking:** Ten issue types tracked with full stack traces, smart deduplication and affected-user tracking, from exceptions and slow queries to queue jobs and scheduler runs.
- **Real user monitoring:** Core Web Vitals, sessions, JS errors, page loads, network timings and rage-click detection, with source map deobfuscation for readable traces.
- **Multi-channel alerting:** A configurable rules engine that pushes alerts to Slack, Microsoft Teams, Telegram, webhooks or email, with acknowledgement and resolution history.
- **Organization and access control:** Data isolation per organization, team roles and permissions, grouped projects, invitations and complete audit trails.
- **Two-minute setup:** A Laravel package installs in three commands via Composer, with a JavaScript RUM SDK for the browser side.

**Strengths:** Free tier is genuinely usable for side projects and solo developers; Backend error tracking and browser RUM live in one platform, avoiding two dashboards; Organization isolation, roles and audit logs are available without an enterprise-only add-on conversation; Straightforward three-step Composer install documented on the site

**Limitations:** Error tracking SDK support is currently focused on Laravel and JavaScript, with Node.js, Python and Go still listed as coming soon; Event-based pricing means busy or spiky applications can outgrow a tier quickly

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

## Frequently Asked Questions

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

Arize AI has 249,028 monthly visits, while Nadi has 60. 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%; Nadi has -74.9%.

### 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. Nadi: Free Trial, Freemium, Paid. Free tier at $0 with 3 projects, 10,000 events per month, error tracking, RUM, traces, email notifications and 2 team members. Pro is $12/month (or $10/month billed yearly), with unlimited projects, 100,000 events per month, Slack/Teams/email alerts, 15 team members and priority support. Enterprise is custom-priced with unlimited events and projects, custom integrations, SSO/SAML, unlimited members and a 99.9% SLA. All plans include a 14-day free trial and a 30-day money-back guarantee.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Datadog](https://openaitools.app/tool/datadog) | 5,175,760 | -4.8% | Freemium, Free Trial, Paid, Contact for Pricing, Free | Unified observability, security and incident response for cloud-scale engineering teams | [.md](https://openaitools.app/tool/datadog.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 | [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) |
| 4 | [Maxim AI](https://openaitools.app/tool/maxim-ai) | 121,351 | +10% | Contact for Pricing, Free Open Source | Evaluate, monitor, and govern your AI applications in production | [.md](https://openaitools.app/tool/maxim-ai.md) |
| 5 | [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) |
| 6 | [Confident AI](https://openaitools.app/tool/confident-ai) | 83,400 | -3.3% | Freemium, Paid, Contact for Pricing | Standardize LLM evaluation, observability, and red teaming across your whole org | [.md](https://openaitools.app/tool/confident-ai.md) |
| 7 | [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) |
| 8 | [Openlayer](https://openaitools.app/tool/openlayer) | 48,415 | -6.4% | Freemium, Contact for Pricing | Stronger focus on compliance enforcement and AI governance, but less specialized for deep developer tracing workflows. | [.md](https://openaitools.app/tool/openlayer.md) |
| 9 | [Latitude](https://openaitools.app/tool/latitude) | 48,210 | -30.6% | Freemium, Open Source, Enterprise | Open-source observability that finds your AI agent's failures — and fixes them | [.md](https://openaitools.app/tool/latitude.md) |
| 10 | [Agenta](https://openaitools.app/tool/agenta) | 45,760 | +29.5% | Freemium | Open-source workspace for building, evaluating and shipping AI agents | [.md](https://openaitools.app/tool/agenta.md) |

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

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