Train developers on the real risks in their code — human-written or AI-generated

Adaptive Learning automatically connects software risk to targeted developer learning, so that every minute of learning counts.

book a demo
Provenant de la société de formation au codage sécurisé #1
Le problème de la gouvernance de l'IA

L'IA est intégrée au développement. La supervision ne l'est pas.

Les responsables de la sécurité et de l'ingénierie sont invités à :
  • Quels outils et modèles d'IA sont utilisés ?
  • Dans quelle mesure l'IA influence-t-elle le code ?
  • L'IA augmente-t-elle les vulnérabilités introduites ?
  • Les développeurs valident-ils les résultats de l'IA ?
  • Pouvons-nous prouver la réduction des risques au fil du temps ?

Dans la plupart des organisations, ces réponses reposent sur des hypothèses, et non sur des données. Cet écart crée une exposition à la vitesse de l'IA. Agent de confiance : l'IA fournit la visibilité, la corrélation des risques et les contrôles de gouvernance nécessaires pour répondre à ces questions

What is Adaptive Learning?

Turn software risk into developer improvement — automatically

Developers receive just-in-time learning aligned to their environment and the risks they actually create. The result is stronger developer capability and reduced vulnerabilities before they reach production. Targeted learning is aligned to:

book a demo

The vulnerabilities they introduce

The languages they use

The repositories they contribute to

The AI tools influencing their code

Agent de confiance : l'IA capture les signaux d'utilisation de l'IA et valide les métadonnées, et non le code source ou les instructions, tout en préservant la confidentialité des développeurs tout en permettant une gouvernance à grande échelle. Il rend le développement assisté par l'IA auditable et géré à travers le SDLC sécurisé, gérant ainsi les risques pour les développeurs avant la production.

It makes AI-assisted development visible, auditable, and manageable across the secure SDLC, helping organizations identify and reduce developer risk before code reaches production.

Fonctionnalités de base

Gouvernance de l'IA en temps réel chez Commit

Les outils traditionnels de sécurité des applications détectent les vulnérabilités une fois le code écrit. Trust Agent applique les restrictions des modèles d'IA et les politiques de codage sécurisées lors de la validation, empêchant ainsi l'introduction de vulnérabilités avant leur entrée en production.

Réservez une démo
Corrélation des risques au niveau des engagements

Corrélation des risques au niveau des engagements

Associez le développement de l'IA à un risque mesurable

Corrélez les signaux d'utilisation de l'IA, les métadonnées de validation, le Trust Score® des développeurs et les benchmarks de vulnérabilité pour identifier une exposition élevée avant que le code n'entre en production.

Apprentissage adaptatif basé sur les

Apprentissage adaptatif basé sur les

Combler les lacunes en matière de compétences qui sous-tendent l'engagement

Déclenchez un apprentissage ciblé en fonction du risque de validation, de l'influence de l'IA et du Trust Score® des développeurs, afin de réduire les vulnérabilités récurrentes.

Visibilité des rapports et des audits d'entreprise

Visibilité des rapports et des audits d'entreprise

Assurer une supervision fondée sur des preuves

Fournissez des tableaux de bord prêts à l'emploi avec les tendances d'utilisation de l'IA, la visibilité du MCP et les mesures de vulnérabilité introduites, sans stocker de code source ni d'instructions.

API LLM prises en charge

Agent de confiance : AI soutient les principaux fournisseurs de LLM, notamment :

How Adaptive Learning works

From vulnerability discovery to developer improvement in five steps

1
2
3
4
5
1

Ingest

Collect vulnerability signals and AI usage data from your existing scanner stack and AI coding tools, automatically identifying risk at the commit level.

2

Correlate

Connect developer behavior and repository activity to specific vulnerabilities and the developers introducing them.

3

Assign

Automatically deliver targeted learning to each developer based on the specific risks they are introducing — in the languages they use, across the repositories they contribute to.

4

Improve

Developers complete focused learning that strengthens secure coding capability aligned to their real-world risks.

5

Measure

Track reduced vulnerabilities and stronger developer performance at the commit level over time.

Outcomes & Impact

Adaptive Learning helps organizations stay ahead

AI-assisted development is accelerating code delivery — and the volume of vulnerabilities entering production. Organizations relying on generic training and reactive remediation are falling further behind.

image 15
image 16
image 17
image 18
*Prochainement
Reduction in introduced vulnerabilities
53%+
Faster mean time
to remediate
82+%
AI model
traceability
100%
MCP model
traceability
100%
Who it’s for

Purpose-built for security and engineering teams

Book a demo

For AI governance leaders

Operationalize AI governance at commit with model traceability, benchmark-informed policy enforcement, and risk visibility.

For CISOs

Demonstrate measurable reduction in developer-introduced vulnerabilities and connect security training investment directly to risk outcomes.

For AppSec leaders

Connect scanner findings to targeted developer improvement — reducing recurring vulnerabilities at the source without manual assignment or triage.

For engineering leaders

Improve team security skills without slowing delivery. Targeted learning reduces rework and builds capability as AI-assisted development scales.

Turn software risk into developer improvement

See how Adaptive Learning automatically connects vulnerability data and AI-generated code risk to targeted developer learning — at any scale.

schedule a demo
trust score
Adaptive Learning FAQ

Reduce recurring vulnerabilities through targeted developer improvement

Learn how Adaptive Learning automatically connects vulnerability data to targeted developer improvement — reducing recurring vulnerabilities at the source.

What problem does Adaptive Learning solve?

Most developer security training is generic, manually assigned, and disconnected from real development activity. Developers often repeat the same vulnerability patterns because learning is not tied to the risks they actually create.

Adaptive Learning closes that gap by automatically delivering relevant learning based on real vulnerability data and AI-assisted development behavior.

How is Adaptive Learning different from traditional security training?

Traditional security training is typically generic, static, and assigned manually. Adaptive Learning automatically aligns learning to real developer activity and actual software risk.

Instead of assigning broad catalogs of content, Adaptive Learning delivers focused learning tied to:

  • Real vulnerabilities
  • Active repositories
  • AI-assisted development activity
  • Individual developer behavior

This helps organizations reduce recurring vulnerabilities instead of simply tracking training completion.

How does Adaptive Learning help reduce vulnerabilities?

Adaptive Learning helps reduce vulnerabilities by identifying recurring risk patterns and assigning targeted learning before insecure behaviors become repeated development habits.

By connecting vulnerability findings directly to developer improvement, organizations can reduce recurring vulnerabilities at the source instead of relying only on downstream remediation.

What is the relationship between Adaptive Learning and Trust Agent: AI?

Trust Agent: AI provides visibility into AI-assisted development activity. Adaptive Learning builds on that foundation by connecting AI-generated code risk and developer behavior to targeted learning.

Together, they help organizations move from AI visibility and governance to measurable risk reduction and developer improvement.

Which vulnerability scanners are supported?

Adaptive Learning currently supports integrations with:

  • Snyk
  • GitHub Advanced Security
  • Aikido
  • Fortify
  • Polaris

Support levels vary by integration and deployment mode.

Can administrators control what training gets assigned?

Yes. Administrators remain in control of the content, structure, timing, and settings through Secure Code Warrior Quests. Adaptive Learning determines who receives training based on risk signals, while admins define the learning experience itself.

Does Adaptive Learning assign training automatically?

Yes. Adaptive Learning automatically identifies which developers should receive learning assignments based on real developer activity, AI usage, vulnerability data, and repository contribution patterns. This removes the manual overhead traditionally required to manage large-scale developer security learning programs.

Vous avez encore des questions ?

Informations d'assistance pour capter les clients qui pourraient être réticents.

Contacter