Elite AI hackers aren’t born. They’re trained.
Elite AI hackers aren’t born. They’re trained.
Mindfort is a capable platform with a proprietary model and strong remediation, but it launched recently, sells credit-based tiers, skips mobile and AI apps. Novee is proven at enterprise scale, runs continuously, and covers the full app layer.
Mindfort has real capabilities for a young platform, but early-stage and credit-based aren’t built for continuous enterprise coverage.
Very early, not enterprise-ready.
Credit-based, so testing is episodic.
No confirmed independent validation.
Proprietary AI, but unproven in depth.
No mobile or AI app coverage.
Maturity matters: proven at enterprise scale, running continuously without a credit meter, and validated independently, so you can trust exactly what reaches your team.
Proven at enterprise scale.
Continuous, with no credit meter.
Independently validated, not claimed.
Full application-layer coverage.
Flat per-asset pricing.
A demonstrable proprietary model.
| Capability | Novee AI Pentesting | Mindfort |
|---|---|---|
| Production track record | Proven in production at named enterprises, running today at scale with a track record security leaders will speak to. |
Launched April 2026 with $3.5M raised and early-stage customer logos, so the production track record is still limited. |
| Continuous, change-triggered testing | Runs continuously on demand or automatically the moment code ships via CI/CD. |
Sold as credit-based assessments, so testing is episodic, run when you spend credits, not continuous. |
| Validation architecture | Three independent agents, including a blind re-validator, prove every finding, backed by deterministic checks where possible, and each issue arrives with a working exploit, replication steps, and PoC script. |
Claims under one percent false positives, but with no confirmed independent validation, nothing proves those findings actually hold up. |
| Autonomous execution | Fully autonomous from a domain name, it maps, analyzes, plans, hunts, validates, and fixes on its own, chaining exploits across your application with no human configuration or intervention required. |
Describes autonomous scanning, but the claim is unverified and not yet demonstrated. |
| Pricing | Flat per-asset pricing tied to complexity, so continuous testing costs the same whether you run it once a quarter or every time code ships. |
Credit-based monthly tiers; more testing costs more. |
| Coverage | Web apps, APIs, mobile apps, and AI agents/LLMs, the full application layer, mobile and AI included. |
Web, APIs, infrastructure, and network, but no mobile or AI apps. |
| Compounding application context | An Asset Intelligence Model, proven in production, that deepens every cycle so coverage compounds across runs. |
Describes a per-target knowledge graph; maturity across runs unproven. |
| Closed-loop remediation & retesting | Remediation tailored to your WAF, backend, and codebase, not generic OWASP, with automatic retesting that confirms the fix held. |
Genuine strength: automated code patching and re-test through GitHub, Jira, and Linear. |