# Arize AI vs Donely

Arize AI records 249,028 monthly visits with +3.2% month-over-month growth and Paid, Contact for Pricing pricing. Donely records 10,995 monthly visits with -0.9% growth and Freemium, Free Trial pricing.

| Metric | [Arize AI](https://openaitools.app/tool/arize-com) | [Donely](https://openaitools.app/tool/donely) |
| :--- | :--- | :--- |
| Website URL | https://arize.com | https://donely.ai |
| Categories | Large Language Models (LLMs), AI Agent, AI Monitor, AI Developer Tools | AI Agent, No-Code&Low-Code, AI Assistant, AI Productivity Tools |
| Pricing Model | Paid, Contact for Pricing | Freemium, Free Trial |
| Monthly Visits | 249,028 | 10,995 |
| MoM Growth Rate | +3.2% | -0.9% |
| Primary Market | United States | United States |
| Direct Visits | 107,838 | 4,554 |
| 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)

## Donely

Donely provides managed infrastructure for autonomous AI employees, with a strong current focus on security. Its headline agent, Sentinel, acts as an always-on adversary: a persistent coordinator maps your attack surface across domains, repositories or API specs, then directs thousands of short-lived agents in parallel, each pursuing one narrow objective such as SQL injection, SSRF, IDOR, auth bypass or business-logic abuse. Deterministic validators then attempt to reproduce each result before it is surfaced.

The distinguishing claim is proof over probability. Findings are only reported after a controlled, production-safe challenge has reproduced them, so each one arrives with a reproducible proof of concept, request and response detail, blast radius and a suggested patch. Results flow into GitHub, GitLab, Jira, Linear, Slack, Notion, Discord and data platforms, and the system advertises continuous re-testing on every deploy for compliance evidence such as SOC 2, ISO 27001 and PCI.

The platform emphasises safety and control while running against production: non-destructive read-only validation, full logging and replay of agent actions, per-target least-privilege credentials, rate limits, blast-radius caps and an instant kill switch. Deployment options range from SaaS to a dedicated tenant, in-VPC and air-gapped builds. The site also points to a rebrand toward HOG 3 for the security line, and to hosted OpenClaw/NemoClaw agent offerings elsewhere on the platform.

**Pricing & Plans:** Freemium and enterprise tiers; the site advertises a free trial path and contact-based enterprise pricing, including dedicated, in-VPC and air-gapped deployments.

- **Exploit-validated findings:** Every reported issue comes with a reproducible proof of concept, request and response detail and a blast-radius assessment.
- **Parallel agent swarm:** Thousands of short-lived agents each pursue one focused attack objective under a persistent coordinator.
- **Real offensive tooling:** A steerable headless browser plus Burp, ZAP, Nuclei, sqlmap, Semgrep and custom payloads.
- **Continuous re-testing:** Trigger from CI on every merge, or run continuously against staging and production to keep pace with releases.
- **Guardrails and audit evidence:** Least-privilege keys, rate limits, full action logging and an instant kill switch, with exportable signed traces.

**Strengths:** Only surfaces findings it can actually reproduce, cutting false-positive triage; Runs continuously rather than in annual windows; Broad delivery integrations covering issue trackers, chat and data platforms; Strong safety framing for production testing, with logged, reversible actions

**Limitations:** Enterprise-oriented engagement and pricing, not a self-serve tool for individuals; Product positioning has shifted over time, so older descriptions may not match today's offering; Validated continuous testing is not a substitute for human judgement on business-logic threat modelling

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

## Frequently Asked Questions

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

Arize AI has 249,028 monthly visits, while Donely has 10,995. 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%; Donely has -0.9%.

### 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. Donely: Freemium, Free Trial. Freemium and enterprise tiers; the site advertises a free trial path and contact-based enterprise pricing, including dedicated, in-VPC and air-gapped deployments.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [KaneAI](https://openaitools.app/tool/kaneai) | 901,340 | +13.2% | Freemium, Paid, Contact for Pricing | GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language | [.md](https://openaitools.app/tool/kaneai.md) |
| 2 | [Aikido Security](https://openaitools.app/tool/aikido-security) | 757,491 | +9.6% | Freemium | All-in-one AppSec platform that finds and auto-fixes vulnerabilities | [.md](https://openaitools.app/tool/aikido-security.md) |
| 3 | [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) |
| 4 | [ProjectDiscovery Neo](https://openaitools.app/tool/projectdiscovery-neo) | 158,530 | +22.5% | Paid, Contact for Pricing | AI security platform that finds exposures, proves they're exploitable, and ships the fix | [.md](https://openaitools.app/tool/projectdiscovery-neo.md) |
| 5 | [Mindgard](https://openaitools.app/tool/mindgard) | 153,455 | +1.3% | Contact for Pricing | Attack-led AI security testing and red teaming | [.md](https://openaitools.app/tool/mindgard.md) |
| 6 | [Hacktron](https://openaitools.app/tool/hacktron) | 125,526 | -40.9% | Freemium, Paid, Contact for Pricing | AI-native offensive security: continuous red teaming, white-box pentests, and PR review | [.md](https://openaitools.app/tool/hacktron.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [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) |
| 10 | [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) |

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

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