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SPIDER (SPatial Intelligence & Dynamic Extended Reality) is GridRaster’s spatial mapping and AI platform, built for industrial and defense environments. It creates, processes, understands, and distributes 3D data as a single foundational layer, marrying static technical data with the physical asset in front of you.
SPIDER ingests images, videos, 3D models, point clouds, technical manuals, task orders, labels, and part identifiers, then trains customer-specific models against that data. The result is spatial understanding tuned to your assets and your environment, not a generic model applied to them.
SPIDER is built around three constraints that matter in defense and regulated manufacturing:
Deployment Flexibility: Runs on-premises, in a secure government or private cloud, or fully disconnected at the depot and flight line.
Data Stays Put: XR content is streamed to the device with no local storage, so technical data never rests on the endpoint.
Device Versatility: Works across Apple Vision Pro, iOS, and Android XR devices.
Data Integrity: Syncs with PLM systems, so the model in XR is the model of record.
Third-Party Integration: Connects through standard APIs.
Searchable 3D Database: Powers AI-driven 3D object recognition and real-world overlays.
Streams high-polygon 3D meshes without decimation.
AI-driven 3D model generation at a fraction of traditional time and cost.
On-premises, secure government or private cloud, or fully disconnected.
Works with standard mobile devices and cameras.
PLM systems that house the source of truth are rich, complex data structures and are traditionally challenging to “thread” into operational systems for manufacturing maintenance systems.
Wiring Harness verification and validation is a particularly challenging use case, where the intended design information is challenging to communicate in 2D format, and the possibilities for error in routing are virtually infinite.
SPIDER tackles these challenges by integrating and streaming complex data right to the end user in XR, dramatically reducing the likelihood for errors.
SPIDER streams real-time sensor data onto the asset’s digital twin, changing how industries manage their assets.
At the core is high-resolution sensor data streaming (for example, from 3D capture devices) combined with algorithms that enable localization, mapping, and visualization of practical data and metadata.
A critical use case is defect mapping. By integrating captured sensor data seamlessly into the SPIDER digital twin, users gain unparalleled insight into the real-time condition of their assets along their life cycle. Applications include monitoring infrastructure integrity, optimizing maintenance schedules, or facilitating rapid response to defects.
SPIDER sets a new standard for asset management efficiency and effectiveness.
Traditionally, Product Lifecycle Management (PLM) systems, which store product geometry and metadata, and real-time XR experiences have functioned independently.
This separation limited the potential of XR applications in manufacturing and maintenance, especially for the aerospace, defense, and automotive industries where PLM is the crucial source of product truth.
SPIDER bridges this gap by seamlessly streaming PLM data into XR without extensive de-featuring, allowing users to experience rich product data from PLM systems within their real-time XR workflows.
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