# Donely vs Mindgard

Donely records 10,995 monthly visits with -0.9% month-over-month growth and Freemium, Free Trial pricing. Mindgard records 153,455 monthly visits with +1.3% growth and Contact for Pricing pricing.

| Metric | [Donely](https://openaitools.app/tool/donely) | [Mindgard](https://openaitools.app/tool/mindgard) |
| :--- | :--- | :--- |
| Website URL | https://donely.ai | https://mindgard.ai |
| Categories | AI Agent, No-Code&Low-Code, AI Assistant, AI Productivity Tools | AI Testing, Large Language Models (LLMs), AI Developer Tools |
| Pricing Model | Freemium, Free Trial | Contact for Pricing |
| Monthly Visits | 10,995 | 153,455 |
| MoM Growth Rate | -0.9% | +1.3% |
| Primary Market | United States | United States |
| Direct Visits | 4,554 | 21,556 |
| Review Score | 4.2 | 4.3 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## 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)

## Mindgard

Mindgard is an AI security platform that approaches protecting AI systems the way an attacker would. Instead of starting with a checklist of prompts, it begins with agent-native reconnaissance: profiling the models, agents, tools, instructions, permissions and behaviours that make up an AI system, so it can identify the attack paths most likely to cause real damage. That reconnaissance is fed by vulnerability intelligence drawn from the company's own published disclosures.

The platform spans the full security loop. Recon surfaces what an AI deployment can actually do; red teaming continuously tests agents and systems against evolving attacks; assessment validates which weaknesses are genuinely exploitable and quantifies their impact; runtime protection and remediation guidance help teams close gaps and verify that defences hold as the system changes. This matters because AI behaviour shifts with every model update, prompt change or new tool integration, which makes one-off testing insufficient.

Mindgard originated from more than a decade of AI security research at Lancaster University and says its technology has been behind 175+ publicly disclosed vulnerabilities in prominent AI systems. It is designed to slot into existing engineering workflows through APIs, CI/CD pipelines and Burp Suite integration, so AI security assessment can run before deployment and continuously in production rather than as a periodic external exercise.

**Pricing & Plans:** Mindgard does not publish public pricing. Plans are quoted based on scope, deployment model and enterprise requirements. Contact the team for a demo and custom quote.

- **Attacker-style AI reconnaissance:** Agent-native reconnaissance maps models, agents, tools, instructions, permissions and behaviours the way an attacker would before launching attacks.
- **Continuous AI red teaming:** Continuous, adaptive testing of AI agents and systems against evolving attack techniques, rather than one-off audits.
- **Proprietary vulnerability intelligence:** Findings are backed by a knowledge base built from more than 175 publicly disclosed AI vulnerabilities across major AI systems.
- **Remediation and runtime protection:** Runtime protections and remediation guidance help close defensive gaps and verify that fixes actually hold.
- **Governance and compliance support:** Risk reduction, evidence and reporting aligned to AI policies and governance requirements, keeping AI compliant as it changes.

**Strengths:** Attacker-led methodology focuses on provably exploitable risk rather than generic prompt noise; Backed by a decade of Lancaster University AI security research and 175+ disclosures; Covers recon, red teaming, assessment, remediation and runtime protection in one platform; Integrates with CI/CD, APIs and Burp Suite for continuous assurance

**Limitations:** Requires a sales conversation; no transparent public pricing; Some capabilities overlap with other AI security vendors, so evaluation takes care; Fully realising value assumes integration into CI/CD and security workflows

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

## Frequently Asked Questions

### How do Donely and Mindgard compare in monthly traffic?

Donely has 10,995 monthly visits, while Mindgard has 153,455. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Donely has a month-over-month growth rate of -0.9%; Mindgard has +1.3%.

### How does pricing compare?

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. Mindgard: Contact for Pricing. Mindgard does not publish public pricing. Plans are quoted based on scope, deployment model and enterprise requirements. Contact the team for a demo and custom quote.

## 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 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Agent observability, evaluation, and continuous improvement for production AI | [.md](https://openaitools.app/tool/arize-com.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 | [Hacktron](https://openaitools.app/tool/hacktron) | 125,526 | -40.9% | Freemium, Paid, Contact for Pricing | Automates continuous red teaming and security reviews, but lacks Mindgard's dedicated machine learning vulnerability scanning suite. | [.md](https://openaitools.app/tool/hacktron.md) |
| 6 | [Future AGI](https://openaitools.app/tool/future-agi) | 121,741 | -7.8% | Freemium, Usage-based | Provides open-source LLM simulation and guardrails, but requires more manual setup for enterprise security testing than Mindgard. | [.md](https://openaitools.app/tool/future-agi.md) |
| 7 | [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) |
| 8 | [Lakera Guard](https://openaitools.app/tool/lakera-guard) | 88,435 | -24% | Contact for Pricing | Specializes in real-time runtime security against prompt injections, but lacks comprehensive offline model vulnerability scanning. | [.md](https://openaitools.app/tool/lakera-guard.md) |
| 9 | [Confident AI](https://openaitools.app/tool/confident-ai) | 83,400 | -3.3% | Freemium, Paid, Contact for Pricing | Offers robust LLM testing and red teaming tools, but is tailored more toward developer evaluation than enterprise security auditing. | [.md](https://openaitools.app/tool/confident-ai.md) |
| 10 | [Openlayer](https://openaitools.app/tool/openlayer) | 48,415 | -6.4% | Freemium, Contact for Pricing | Focuses broadly on AI governance and compliance monitoring, but offers less specialized autonomous model red teaming. | [.md](https://openaitools.app/tool/openlayer.md) |

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Source: https://openaitools.app/compare/donely-vs-mindgard

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