AI Requirement AnalysisAI
An AI system that reads technical specifications dozens of pages long and extracts every applicable requirement to assess the technical feasibility of customer requests, with traceability down to the source paragraph.
Dozens of pages of specifications, read methodically
For DMV Tubes, a company in the steel tube industry, we developed an AI system that analyzes customer technical specifications — dozens of pages of standards, tolerances and requirements — and extracts every applicable requirement, removing duplicates and mapping it onto a shared company ontology. The end goal is to assess the technical feasibility of customer requests in a market as technically complex and competitive as special steel tubes: faster response times, fewer errors and assessments that stay consistent over time.
An ontology that grows with use
Recognized requirements are mapped to the concepts of the company ontology; unrecognized ones are not lost, but flagged together with a proposed extension of the ontology itself.
With every analyzed document the knowledge base grows richer: the system becomes more accurate precisely on the cases the company actually encounters.
Traceability down to the paragraph
Every extracted requirement is linked to the exact spot in the document it comes from, visually highlighted on the page.
Reviewers don't have to blindly trust the AI: they can check the origin of every requirement in one click and validate the result in a fraction of the time.
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