Design system and
Custom AI platform for
Atlas Manufacturing
Atlas Manufacturing had two decades of maintenance records nobody could search. We built an internal AI platform that makes that history usable, grounded retrieval over their own documents, plus a design system their team keeps extending.
CLIENT
Atlas Manufacturing
Services
Discovery
Strategy
data preparation
Engineering
UI/UX & Design Systems
Rollout
Web Development
Industry
Manufacturing & Industry
In short
We worked with Atlas Manufacturing across data preparation, retrievaland interface engineering.
The shared goal was a retrieval system engineers would actually use instead of asking the one person who remembers. Through a clean data model, a well-judged retrieval layer and a considered interface, the platform now answers maintenance questions in seconds that used to take hours of archive digging. The hard part was never the model, it was turning twenty years of inconsistent scans into a clean, citable corpus .
Design system
Retrieval, grounded, cited, honest about gaps
The retrieval gives the platform a defensible, auditable footing. Every answer cites its source document and page , and the system says plainly when the archive does not cover a question rather than inventing a plausible answer. That single behaviour is what earned the platform trust on the shop floor within weeks.
Technical, maintainable, modern
A platform their own team can extend
A documented component library combined with a typed API surface gives the whole platform a clear technical shape. Strict module boundaries and a thin ingestion layer across the interface reinforce the character mean Atlas engineers add new document sources themselves.
Built for the people using it
An interface designed around the question being asked
The interface surfaces the maintenance history and technical context engineers need. With search, filters and citations in one view , the aim was to give the team a fast, verifiable answer and get them back to the job rather than into another archive hunt.
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