MappingSpace ALM

The platform applies large language models across the research process. Engineers generate requirements, architecture and test cases inside MappingSpace and push them straight into tracked tasks. The AI supplement feature completes existing documents, AI drawing turns architecture descriptions into editable static and dynamic diagrams, and AI code generates a code framework from the detailed design. The point is to cut the document hours that ASPICE normally costs.

Requirements connect product definition to the development flow. Work item tracking and version control sit alongside them, so each requirement keeps its links to design and tests. Documents are organized as mind maps rather than flat hierarchies, which makes large requirement trees easier to read and keeps traceability intact as the tree grows.

Test management covers the whole cycle: create a test plan, execute cases, and generate reports. Each test ties back to the requirement it covers, so coverage gaps surface before a release gate rather than during an audit. Test cases can be generated by AI and then edited like any other document.

Baseline management brings order to version iteration. When a requirement changes, the system pulls a copy and triggers a review flow, so the change is controlled rather than silent. The full change history is recorded, from the reason it was raised to the final decision, which is what ASPICE traceability asks for.

The chain ends in a standardized release process. A verified baseline moves through defined gates, and the platform keeps the record of what shipped and what it was built on. Teams that do not follow ASPICE end to end can trim the flow and still keep the parts they need.

Private deployment is supported, and the vendor offers a lifetime free private deployment edition. AI features can run against models the customer hosts, so sensitive research documents stay on internal infrastructure. This matters for automotive work, where documents often cannot leave the company network.

GitLab connects for code repositories, and API testing runs inside the platform. The toolchain is built for automotive specifically, with add-on solutions for avionics and medical devices. Reference customers include parts and systems suppliers like Tuopu and Fulda, and the vendor publishes white papers on automotive basic software and research process management.