Incedo GenAI Threat Modeling for Enterprises

Reinvent Threat Modeling with GenAI

Traditional threat modeling is often manual, time-consuming, and dependent on scarce security expertise. As organizations adopt cloud-native platforms, APIs, microservices, DevSecOps pipelines, and connected operational environments, the scale and complexity of security design reviews continue to grow.

Incedo GenAI Threat Modeling for Enterprises helps teams modernize this process with AI-driven security intelligence. By combining Retrieval Augmented Generation (RAG) with architecture and design documentation, the platform rapidly creates actionable threat models, uncovers attack scenarios, and highlights priority risks before they become incidents.

Why Legacy Threat Modeling Falls Behind

Conventional approaches typically rely on workshops, static templates, and manual documentation reviews. These methods can be slow, inconsistent, and difficult to scale across multiple products, releases, and distributed teams. Important risks may be missed, while remediation planning is delayed until late in the delivery cycle.

This creates higher security exposure, slower releases, and greater dependency on specialist resources.

How the Platform Creates Value

The solution ingests architecture diagrams, product design documents, technical specifications, and system context to build a security-aware knowledge base. Using GenAI and RAG, it interprets system components, trust boundaries, data flows, integrations, and dependencies to generate comprehensive threat models automatically.

The platform can simulate attack paths, identify vulnerable design patterns, and surface prioritized recommendations through an interactive risk dashboard. Security and engineering teams gain faster insight while maintaining human oversight and governance.

Designed for Modern Environments

The platform supports use cases across cloud-native applications, microservices ecosystems, API security programs, DevSecOps pipelines, enterprise platforms, and ICS/OT environments where security and operational continuity are critical.

Built Using AWS Services

The solution is built on AWS and can leverage Amazon Bedrock for generative AI reasoning, Amazon OpenSearch Service for vector search and RAG retrieval, Amazon SageMaker for custom risk models, Amazon S3 for secure document storage, AWS Lambda for workflow automation, Amazon ECS or Amazon EKS for containerized deployment, Amazon Redshift for analytics, Amazon QuickSight for dashboards, and AWS IAM for secure access control.

Business Benefits

Organizations gain faster threat modeling, broader security coverage, earlier risk visibility, automated attack path analysis, prioritized remediation insight, stronger DevSecOps integration, and reduced dependence on manual review cycles.

Business Impact

With GenAI-powered threat modeling in place, teams can accelerate secure delivery, improve architecture resilience, strengthen compliance readiness, reduce security design gaps, and scale security governance across complex digital ecosystems.