Requirements Ai

Product Introduction

1. Requirements AI is an AI-powered platform that automatically converts unstructured meeting transcripts into structured engineering requirements compliant with INCOSE, Behavior-Driven Development (BDD), and Agile User Story formats. It uses advanced natural language processing to identify key decisions, constraints, and actions from discussions, generating standardized outputs in seconds. The tool is designed for systems engineers, product managers, and development teams working on complex technical projects.
2. The core value of Requirements AI lies in its ability to eliminate manual requirement extraction, reduce errors by up to 80%, and ensure adherence to industry standards like ISO 26262 and ASPICE. By automating the transformation of meeting notes into actionable requirements, it accelerates project timelines and enhances traceability for compliance audits. This enables teams to focus on engineering rather than administrative tasks while maintaining consistency across documentation.

Main Features

1. Requirements AI generates INCOSE-compliant requirements with formal "shall" statements, including rationale, verification methods, and traceability tags aligned with systems engineering best practices. These outputs are automatically formatted to meet INCOSE guidelines, reducing the need for manual editing. The AI contextualizes discussions to ensure technical accuracy and completeness.
2. The platform creates Behavior-Driven Development (BDD) scenarios in Given/When/Then syntax directly from meeting transcripts, enabling testable requirements for software and systems engineering teams. It identifies user actions, system responses, and edge cases to generate scenarios ready for integration into testing frameworks like Cucumber or SpecFlow.
3. Requirements AI extracts Agile User Stories with clear acceptance criteria, personas, and business value statements, formatted for direct inclusion in Jira or similar backlog tools. It prioritizes user-centric requirements by analyzing stakeholder intent and translating discussions into INVEST-compliant stories.

Problems Solved

1. The product addresses the inefficiency of manual requirement extraction from lengthy meeting transcripts, which often leads to missed details, inconsistent formatting, and non-compliance with standards. Traditional methods require hours of manual sorting and lack automated quality checks, increasing project risks.
2. Requirements AI targets systems engineers, automotive engineers, and agile development teams managing complex projects under regulatory frameworks like ASPICE or ISO 26262. It is particularly valuable for organizations transitioning from document-centric to model-based systems engineering (MBSE).
3. Typical use cases include converting design review meetings into traceable INCOSE requirements, transforming sprint planning discussions into BDD scenarios, and generating audit-ready user stories for automotive software projects. It also streamlines compliance reporting for ISO 26262 functional safety assessments.

Unique Advantages

1. Unlike generic text analysis tools, Requirements AI is pre-trained on automotive and systems engineering standards, ensuring domain-specific accuracy for industries like automotive, aerospace, and medical devices. Competitors lack built-in support for ASPICE or INCOSE templates.
2. The platform integrates automated quality scoring that evaluates requirement clarity, testability, and alignment with SMART criteria, providing actionable feedback to users. This feature is absent in most requirement management tools.
3. Competitive advantages include simultaneous multi-standard output (e.g., generating INCOSE and BDD formats from the same transcript), AI-trained context recognition for technical jargon, and one-click CSV/Excel exports compatible with IBM DOORS, Polarion, and JAMA Connect.

Frequently Asked Questions (FAQ)

1. What input formats does Requirements AI support? The tool processes raw text transcripts from meetings, emails, or collaboration tools like Microsoft Teams, with automatic speaker differentiation and action item tagging. Audio file support via third-party transcription services is planned for Q4 2024.
2. How does the tool ensure compliance with automotive standards? Requirements AI’s AI model was trained on 50,000+ ASPICE-certified requirements and ISO 26262 work products, with built-in checklists for functional safety attributes like ASIL levels and hazard analysis links.
3. Can users customize requirement templates? While the base templates adhere to industry standards, enterprise clients can configure custom fields, terminology libraries, and validation rules through an API. Edits made to generated requirements are preserved during re-exports.
4. What security measures protect sensitive project data? All data is encrypted in transit and at rest using AES-256, with optional on-premises deployment for air-gapped environments. The platform is GDPR-compliant and supports role-based access control.
5. Does it integrate with requirement management systems? Requirements AI exports to CSV/Excel for seamless import into IBM DOORS, Jama Connect, and Polarion, with REST API support for real-time synchronization. Native integrations with Jira and Azure DevOps are available in the enterprise tier.