RevoAI GmbH automates the extraction, classification, and evaluation of requirements from unstructured sources using artificial intelligence, enabling engineers to streamline their product development processes. This technology enhances productivity by providing traceable results and actionable insights, significantly reducing the time spent on requirement management.
Funding
Funding not disclosed
Founders
Product
Problem
Engineers often struggle with the time-consuming and complex task of manually extracting, classifying, and evaluating requirements from unstructured documents like PDF specifications and standards. This process can be error-prone and hinder productivity during product development.
Solution
Complyze, by RevoAI GmbH, leverages artificial intelligence to automate the extraction, classification, and evaluation of requirements from unstructured sources. The platform automatically extracts requirement lists, assesses and annotates requirements based on user-defined specifications, and provides traceable results with user-friendly preview features. This enables engineers to streamline product development, improve productivity, and reduce the time spent on requirement management. The extracted requirements can be exported into common exchange formats.
Target Audience
The primary users are engineers, quality management professionals, and technical sales teams seeking to improve productivity and efficiency in requirement management processes.
Features
- Automated extraction of requirement lists from unstructured sources such as PDF documents and standards.
- Automated assessment and annotation of requirements based on user-defined specifications and documentation.
- Traceability features to ensure the origin and context of each requirement are maintained.
- User-friendly preview functions for easy review and validation of extracted requirements.
- Export functionality to common exchange formats for seamless integration with existing engineering tools.
- AI-powered suggestions based on similar requirements evaluated in the past.
- Out-of-the-box functionality requiring no data adaptation.