AI generates code well but cannot understand large, complex applications. CAST maps the real architecture, dependencies, and structural risks, then feeds that deterministic context to your AI agents so they transform software with fewer blind spots and less rework.
See how CAST grounds AI in verified application facts
Why change
Important relationships span multiple technologies, databases, repositories, and applications. Without a factual map, AI agents guess, and guessing causes rework.
AI without CAST
AI with CAST
Capabilities
CAST analyzes source code across 450+ technologies to produce maps, dashboards, and call graphs that executives, developers, and AI agents can act on.
CAST Imaging reverse engineers an entire application into an interactive visual blueprint of code objects, data structures, dependencies, and call paths.
CAST Highlight governs software portfolios with empirical facts on technical debt, cloud maturity, OSS risks, and AI adoption readiness.
CAST Gatekeeper applies ISO 5055 rules to detect system-level flaws affecting security, resiliency, and efficiency before changes reach production.
The CAST MCP server delivers architectural graphs, dependency maps, and call paths to MCP-compatible AI agents so they understand complex software before making changes.
CAST SBOM Manager provides open-source component analysis and aggregates results into dashboards for risk control and compliance.
Identify the best candidates for cloud migration, surface blockers, and measure cloud maturity across your portfolio.
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Your path
Start fast and see the difference within weeks.
CAST plugs directly into GitHub, BitBucket, and Azure DevOps to access source code across your applications.
CAST deterministically analyzes source code across 450+ technologies, mapping objects, dependencies, transactions, data flows, and architectural relationships.
Dashboards, interactive maps, and call graphs are produced covering technical debt, cloud maturity, structural flaws, quality grades, and AI readiness.
The MCP server delivers this factual architectural context to your AI coding agents, grounding their work in verified software facts.
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Packages
Annual subscriptions include complementary concierge services with dedicated specialists. Each portfolio requires its own subscription.
Free
Software bill of materials management with open-source component analysis.
$20,000/year for 25 applications
Portfolio governance with empirical facts on technical debt, cloud maturity, and OSS risks. Three editions available: Complete Insights, Cloud Insights, and SCA Insights.
Custom
Interactive application blueprints and structural integrity gates with ISO 5055 compliance. Volume discounts available via private offers.
Answers
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 effective at generating code but 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, so the AI agent can ground its work in verified facts.
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.
Common use cases include understanding unfamiliar applications, extracting business rules, performing change-impact analysis, generating documentation and tests, remediating technical debt, removing cloud blockers, identifying microservice candidates, replacing frameworks or databases, and transforming legacy applications.
Move forward
Stop letting AI guess at your architecture. Book a call to see how CAST grounds AI in deterministic software facts.
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