Decommissioning work usually begins with multiple site visits, third party videos, images, scattered schematics, survey notes, and manual checklists that are hard to align once execution starts. Teams end up spending too much time validating what the asset is before they can decide what to do next.
SupplyDome unified that process by classifying each asset record with machine learning assisted diagram interpretation, then linking safety guidance, onboarding, collaboration, and execution steps in one connected flow.
Asset intelligence from schematics and surveys
SupplyDome ingested schematic and survey-based diagrams and used machine learning to identify asset categories, models, assemblies, sub-assemblies, and parts. That gave engineering and field teams a clean structure from day one, eliminating repeated manual interpretation before each work package.
Safety recommendations grounded in standards
Using geographical and historical operating data, SupplyDome recommended job safety guidelines aligned to American Petroleum Institute standards, OSHA guidance, ISO requirements, and other applicable controls. Teams received context-specific safety direction earlier, which reduced rework during permit and pre-job reviews.
Onboarding and collaboration without blind spots
Every role received job onboarding through selected procedures and videos tied to the task at hand, while real-time collaboration feeds kept customers and internal teams aligned on updates, blockers, and completions. The platform then produced simplified, action-oriented task lists that reduced redundant steps and replaced fragmented paper trails with clear digital execution history.