
Berkeley, California, USA
2025
Software Development, Information Technology, Enterprise Software, Financial Services, Healthcare, Technology
CoreStory is an AI software company developing a code intelligence platform for understanding complex software systems. Its technology analyzes source code and converts it into a persistent model of a software system’s architecture, behavior, business rules, and intent. That model can be queried by people and accessed by AI coding tools, giving engineering teams and AI agents structured context about large and long-lived codebases.
CoreStory analyzes software repositories and creates a structured representation of how an application works. Teams can connect a GitHub repository or upload a codebase, after which the platform builds a queryable intelligence model grounded in the source code. Users can ask natural-language questions about authentication flows, APIs, database structures, dependencies, business logic, and other parts of the system.
The platform can also generate architecture documentation, user stories, data models, API specifications, and business rules. Engineering organizations use these capabilities for legacy application modernization, software maintenance, developer onboarding, feature development, and understanding AI-generated code.
CoreStory’s underlying technology centers on a persistent Code Intelligence Model created by ingesting and analyzing source code. Rather than rebuilding context each time a developer or AI tool starts a task, CoreStory maintains structured knowledge of a system’s architecture, dependencies, workflows, APIs, business rules, and interactions.
The platform uses AI-driven code analysis and knowledge graphs to connect information found throughout a codebase. CoreStory describes its broader technical architecture as combining polymorphic agents, an ontology, a knowledge graph, a trust engine, and living intelligence. This allows information extracted from source code to become reusable system context rather than isolated documentation.
CoreStory also operates an MCP server for AI coding agents. Compatible tools can query the intelligence model while planning or working on software, giving them access to architecture, business logic, specifications, and system relationships without requiring all of that information to be repeatedly placed into an AI model’s context window.
AI coding tools can generate and modify software quickly, but their effectiveness depends heavily on having enough context about the systems they are working with. CoreStory addresses this problem by creating a persistent source of software-system context that can be shared between developers and AI agents.
This approach is particularly relevant for large or legacy codebases, where architecture, dependencies, and business rules may be distributed across millions of lines of code and incomplete documentation. CoreStory represents an emerging category in enterprise AI where artificial intelligence is used not only to generate code but also to build machine-readable understanding of existing software that can support modernization, maintenance, governance, and AI-assisted development.
The company’s primary product is the CoreStory Code Intelligence Platform, which ingests source code and builds a persistent intelligence model describing how the underlying software operates. Users can connect repositories, explore generated system information, and use the resulting model across software-development workflows.
CoreStory provides a natural-language interface for querying a codebase. Developers, architects, and product teams can ask questions about features, APIs, workflows, database structures, dependencies, or where specific logic exists. Responses are grounded in CoreStory’s structured analysis of the source code.
The platform automatically creates software documentation and specifications, including executive overviews, user stories, data models, API specifications, and integration information. AI-guided workflows can additionally produce Jira tickets, new user stories, business-logic analysis, and behavior-driven development scenarios.
CoreStory exposes its code intelligence through an MCP server, allowing compatible AI coding agents and development environments to query system context during software-development tasks. CoreStory lists integrations or workflows involving tools including Claude Code, Codex, Devin, GitHub Copilot, Cursor Composer, and Droid.
CoreStory is primarily applied to enterprise software engineering and application modernization. Organizations can use it to analyze legacy applications before migrations or modernization projects, uncover dependencies and embedded business rules, maintain and extend existing applications, and help developers understand unfamiliar codebases.
The technology can also support developer onboarding, software maintenance, feature development, QA and application governance. Another application is AI-generated software: CoreStory analyzes generated code to document its architecture and behavior, helping engineering teams understand code that may otherwise have limited documentation or unclear design decisions.
CoreStory ingests source code and builds a structured Code Intelligence Model representing elements such as architecture, dependencies, workflows, APIs, business rules, and system interactions. Its generated answers and documentation are grounded in information derived from the codebase.
Yes. CoreStory’s Chat with Your Code capability allows developers, architects, and other teams to ask natural-language questions about a software system, including where logic exists, how features operate, and how different components interact.
Yes. CoreStory provides an MCP server that allows compatible AI coding agents to query its code intelligence. The company identifies tools including Claude Code, Codex, GitHub Copilot, Devin, Cursor Composer, and Droid as examples of agents or tools that can work with its system context.
CoreStory says its primary role is not generating code. Instead, it generates business requirements, business rules, workflows, specifications, and architectural and code insights from existing codebases. Those insights can then provide context to developers and AI coding agents.
The platform supports use cases including legacy application modernization, application maintenance, developer onboarding, feature development, software governance, and analysis of AI-generated code. CoreStory states that its analysis can work across languages and frameworks.
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