Structural Integrity Gates
Apply ISO 5055 standards to detect system-level flaws affecting security, resiliency, and efficiency before changes reach production.
What you get
From structural integrity to open-source risk, CAST gives you the facts to build reliable software.
Apply ISO 5055 standards to detect system-level flaws affecting security, resiliency, and efficiency before changes reach production.
Detect open source security and license risks across your portfolio with detailed software bill of materials management.
Identify the best candidates for cloud migration and spot blockers that delay your transition to the cloud.
Provide AI agents with deterministic application context via MCP server to reduce blind spots and unintended downstream impacts.
Reverse engineer applications into interactive visual blueprints to understand architecture and accelerate modernization.
Identify and prioritize technical debt with empirical facts to improve reliability, security, and efficiency.
How it works
A clear path from first step to measurable outcome.
CAST plugs directly into GitHub, BitBucket, and Azure DevOps to analyze your source code and open-source components.
Semantic analysis maps code objects, data structures, dependencies, and cross-application relationships across 450+ technologies.
Use dashboards, call graphs, and structural integrity gates to block flaws, guide AI agents, and ensure reliable production releases.
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Pricing
Annual subscriptions include access to complementary concierge services.
$20,000/year
Free
Custom
Questions
AI + CAST combines AI coding agents with deterministic software intelligence from CAST. CAST maps the architecture, dependencies, data access, call paths, and structural risks inside an application, then provides that context to AI agents so they can understand and transform complex software more accurately, efficiently, and safely.
AI coding agents are very effective at generating code, but they can struggle to understand large, complex applications from source files alone. Important relationships may span multiple technologies, databases, repositories, and applications. CAST gives the agent a factual map of these relationships, reducing blind spots, incorrect assumptions, and unintended downstream impacts.
It means the information is derived through semantic analysis of the actual software rather than inferred or generated probabilistically by an LLM. CAST identifies the application's real objects, dependencies, transactions, data flows, and architectural relationships. The AI agent can therefore ground its work in verified facts about the software.
No. CAST complements the AI tools an organization has already selected. It supplies deterministic application context to MCP-compatible agents and development tools, allowing customers to improve their existing AI-enabled workflows without introducing another tool.