ReqSpell is an AI-powered platform for requirement analysis, code understanding, and legacy modernization. It helps teams analyze requirements, understand existing systems, and generate documents such as BRD, FSD/FRD, SRS, and technical documentation directly from requirements and source code. ReqSpell also creates code-linked documentation to improve traceability and collaboration across teams.
The platform supports legacy system understanding, reverse engineering, and modernization acceleration by identifying dependencies, workflows, and system architecture. Its interactive Knowledge Graph visually maps relationships between requirements, code, APIs, repositories, and documents, helping teams easily understand complex systems. With repository integrations, ReqSpell enables automated analysis of applications, documentation generation, and AI-assisted insights to accelerate modernization and overall SDLC efficiency.
ReqSpell is an AI-powered platform designed to help development teams modernize existing systems, maintain current applications efficiently, and build new solutions faster. It supports three types of application initiatives:
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Once you open an application, the top-left corner of the screen displays the following sections: Overview, Sub Systems, Sources, Teams, and Connections.
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Provides high-level information about the application, including its business domain and a brief description.
Contains the subsystems of a project or process. Users can create and manage subsystems within the application to organize and group related project components or processes
Contains all sources related to the project or process, such as source code, documents, and files. Users can upload and manage these sources, which are used during requirement analysis and system understanding. Supported file types include .pdf, .docx, .jpeg, .jpg, .xlsx, .csv, .pptx, .png, and .zip. A maximum of 10 files can be uploaded, with each file up to 10 MB.
Enables users to collaborate with team members during the requirement analysis process. Users can invite team members to join the application. All team members can access shared sources and collaborate on common project data within the application.
Allows the application to be connected to a source code repository, enabling direct integration with the codebase.
Once sources and connections are set up, the system indexes the data. This indexed data powers the knowledge graph, enabling efficient retrieval, contextual understanding, and enhanced relationships between data entities.
The Groom window is the main workspace in ReqSpell. It consists of four key sections:
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The System Overview is a knowledge graph that provides a complete view of the system. It displays all modules and their submodules, along with the interconnections between them. This helps users understand how different parts of the system relate to and interact with each other.
Double-clicking a node expands it to a nested level, allowing users to explore the interrelationships between modules in greater depth.
This section represents the entity relationships within the system. It covers:
It provides a high-level understanding of how business entities are connected across the system.
The Information section displays detailed information about the selected entity or module. It helps users understand the purpose, structure, and dependencies of the selected component.
The Chat feature allows users to interact with an AI agent in the context of a selected entity or module. Users can:
To ask questions about a specific entity or module, select the required item from the System Overview or Business Entity Overview. It will automatically be set as the context in the Chat window, enabling focused and relevant analysis.