Pentera proves what’s exploitable across your network and infrastructure. Novee goes deep on the layer attackers use to breach modern products — your applications and API — reasoning like a real attacker, continuously, and closing the loop with a verified fix.
See what Novee finds in your applications that infrastructure validation can’t.
Pentera earned its position in Automated Security Validation, but it was built for infrastructure. On the application and business-logic layer, the gaps show.
Built for infrastructure, not applications.
Human-guided, not fully autonomous.
No compounding application context.
No confirmed proprietary offensive model.
Detection without a closed loop.
Novee is an AI penetration testing platform purpose-built for the layers attackers target most often, combining an AI hacker and an AI defender in one continuous loop. It reasons about how your applications actually work, then finds, proves, and closes real exploitable risk.
Depth on the application layer.
Fully autonomous, at machine speed.
A purpose-trained offensive model.
Context that compounds every cycle.
Zero false positives by design.
Closed-loop remediation.
| Capability | Novee AI Pentesting | Pentera |
|---|---|---|
| Application & business-logic testing | Core strength — reasons about how your apps work to find business logic flaws, authorization gaps, and chained attack paths |
Infrastructure-focused; application and business-logic testing in beta. |
| Compounding context | Living model every cycle — the Asset Intelligence Model expands coverage and sharpens testing over time |
No equivalent; testing does not compound an application-specific model across runs |
| Closed-loop remediation | Finding to verified fix — stack-specific remediation, automatically retested to confirm it held |
Proves exploitability, but no confirmed stack-specific remediation or automatic retest |
| Proprietary offensive model | Purpose-trained — a proprietary offensive reasoning model inside an multi-model Offensive System |
Agentic AI layer on a deterministic engine; no confirmed proprietary offensive model |
| Autonomy | Fully autonomous — agents test continuously with no human approval in the loop |
Automated infrastructure testing, but analysts approve each testing step |
| Developer-workflow integrations | Built for engineering — CI/CD triggered, with Jira and GitHub |
SOC-ecosystem integrations, but no developer-workflow integrations |
| Continuous testing | Continuous by design — triggered on every change through CI/CD |
Runs continuous pentesting across the infrastructure and network surface |
| Coverage | Application surface — web, API, mobile, and AI apps |
Broad infrastructure reach — network, cloud, external surface, and AI attack surface |