Leveraging Distributed Development Knowledge Across the Organization

In automotive software development, a wide range of information—such as specifications, design documents, and defect handling records – is often managed in a fragmented manner across different teams and tools.
As a result, engineers may spend significant time simply searching for the information they need, and valuable past knowledge is not always fully utilized.
This feature organizes existing document assets as searchable resources and enables cross‑domain information access, allowing teams to reference development knowledge more effectively across departments and tools.

Supporting Evidence‑Based Answer Generation

The RAG‑based Conversational AI for Knowledge Utilization generates answers in an interactive manner by referring to pre‑accumulated internal documents and development assets.
– Searching for and extracting relevant reference materials
– Generating answers grounded in existing information
– Reusing past assets and similar cases
As a result, it becomes easier to confirm information with a consistent factual basis without relying on individual memory or experience, supporting more reliable and efficient decision‑making in automotive software development.

Supporting More Efficient Development and Design Activities

This feature is intended for use in scenarios such as design reviews, specification checks, and referencing past cases during development and discussion.
By reducing the need to manually search through individual documents, it helps decrease indirect effort associated with development and analysis activities.
As a result, it supports more effective use of accumulated knowledge and helps improve decision‑making speed in automotive software development.