A February 2026 seminar brought together three organizations at the forefront of spatial data and infrastructure technology to tackle one of the industry’s most debated questions: what is a digital twin, and when does it actually work? Moderated by Blaine Horner of Merrick & Company, the session featured Esri’s Andrew Carey challenging the room on terminology and purpose, gNext Labs’ Russ Ellis demonstrating AI-powered defect detection across bridges, airports, and communication towers, and Langan Engineering’s Russell Hall and Brock Saylor walking through their end-to-end indoor mapping workflow. The through-line across all three presentations: the gap between collecting good data and making it actionable is still the hardest problem to solve.
Esri — ArcGIS Reality Engine | Andrew Carey, Sr. Business Development
Redefining the Digital Twin
Andrew Carey opened with a challenge to the geospatial industry. He began by asking the audience to imagine drawing a diagram of the conference center — from a rough pencil sketch to a SLAM-scanned 3D model. None of these, he argued, are digital twins in any meaningful operational sense. They are digital representations of the real world. The distinction matters because it defines what customers actually need their data to do.
A genuine digital twin, in Carey’s framing, is a connected system that can answer specific questions: Where are things? How many are there? What happens if this scenario plays out? How will the environment be affected? These questions require integrating IoT sensors, live camera feeds, utility network data, and 3D spatial context into a single platform accessible to a broad range of users — not just the engineers who built the model.
The System of Systems Framework
Esri approaches this through what Carey called a system of systems: a system of record (where data lives and can be recalled consistently), a system of insight (analytical tools that extract understanding from the data), and a system of engagement (how that data is made accessible to the people who need it). This framework maps directly onto the most common failure mode Carey encounters in client conversations: an organization that paid for a LiDAR scan three years ago but cannot find where the data went or how to access it today.
Case Studies: Nottingham and Raleigh
Carey drew on two compelling city-scale examples. The City of Nottingham, UK deployed a digital twin to address a permitting bottleneck that was actively stifling investment and development. By integrating aerial survey, ground control, and building scans into a single accessible platform — with a public-facing interface for citizen comment on proposed developments — the city fundamentally changed its permitting process. The return on investment: two pounds returned for every one pound spent.
The City of Raleigh, North Carolina partnered with Nvidia and Microsoft to integrate 3D aerial scan data with static CCTV feeds and AI-powered video analytics. The system uses Nvidia’s VSS chipset to identify stalled vehicles, count pedestrians, and analyze traffic patterns in real time — automatically prompting dispatch through the city’s traffic management system. Interoperability through a common location standard is what makes this a digital twin rather than two parallel tools.
Oriented Imagery and Web-Performant Delivery
Oriented imagery workflows within ArcGIS link raw source images directly into processed photogrammetric scenes, surfacing the best available image of any location in the model with a single click. These images typically have higher fidelity than processed outputs and are particularly valuable for inspection and documentation. The ArcGIS Reality Engine continues to advance with photometric rendering, true ortho processing (removing building lean and geometric distortion), and web-performant delivery pipelines that make complex 3D models browser-accessible.
gNext Labs — AI-Enabled Defect Detection | Russ Ellis, President
The Inspection Bottleneck
Russ Ellis, President of gNext Labs, framed the problem directly: the traditional output of an infrastructure inspection is a 144-page PDF that no one reads. His platform replaces that static deliverable with a live, collaborative, AI-annotated system. Every defect detected by drone-based computer vision receives a unique ID, a GIS location, quantified measurements, and a trackable history — enabling comparison across inspection cycles and predictive condition modeling. The platform connects directly to the core question of how to allocate limited maintenance dollars most effectively.
Bridge Inspection
In the bridge inspection demo, Ellis navigated a 3D model of a Scottsdale, Arizona bridge, toggling defect layers on and off — cracks, spalls, patches — with each defect individually geolocated and quantified. Patches are classified as defects in the GeneXT system, enabling inspectors to evaluate whether prior repairs are holding or deteriorating over time. Outputs integrate directly into CAD, GIS layer files, and CSV/Excel formats for existing workflows.
Airport Runway and FAA Vegetation Clearance
The runway surface inspection demo showed crack and patch relationships visualized from altitude to ground level, supporting budget allocation decisions across the full pavement surface. The FAA vegetation clearance module maps growth against mandated approach angle thresholds, color-codes areas by severity, and generates reports with precise GPS locations, parcel boundaries, and property ownership data — providing the specific information needed to initiate contact and remediation.
Communication Tower Inventory
GeneXT’s tower inspection module uses AI to parse drone imagery and build a structured equipment database: height, equipment type, manufacturer, and antenna azimuth for every component on the structure. The platform supports ad hoc design work within the same environment, enabling pre-work modeling of new equipment placement or antenna reorientation.
Langan Engineering — Indoor Mapping with Mobile LiDAR | Russell Hall & Brock Saylor
SLAM Scanning and Scanner Selection
Langan Engineering’s indoor mapping practice centers on two Leica SLAM systems: the Arc Backpack (true 360-degree imagery) and the BLK2GO (approximately 270-degree, compact and flexible). SLAM — Simultaneous Localization and Mapping — builds precise point clouds as the operator walks through a space without requiring static setup or GPS. Hall stressed that the most important variable in scanner selection is vendor inventory and support response time. Leica’s support infrastructure has been available at 1:00 AM on difficult access jobs.
Leica Pinpoint Registration
Hall demonstrated Langan’s registration workflow using Leica Pinpoint, which imports multiple scans, colorizes them, and provides a cross-section/slice view for alignment. Scans are aligned sequentially, snapping together when proximity thresholds are met, with overlap statistics and error readouts confirming quality. The registered cloud flows into TopoDot for extraction, AutoCAD for Indoor GML formatting, and Esri or other viewers for delivery. Langan uses four viewer platforms depending on client preference: Esri, TrueView, Bentley iTwin Orbit, and TopoShare.
Regulatory Context and K–12 Demand
Approximately 20 states now require indoor mapping for K–12 school facilities, with some explicitly mandating GIS-based delivery. California, Texas, Arizona, Utah, and Colorado are among the most advanced. The typical mandate covers accurate floor plans and documented locations of life-safety equipment. Saylor described a recurring pattern where critical institutional knowledge lives only in one employee — at Chapman University, a retiring facilities manager carried essentially all campus infrastructure knowledge in memory. The project converted that knowledge into a GIS-based system of record accessible to the full facilities team.
Platform Architecture and Application Tiers
Saylor described three application layers within the indoor GIS ecosystem: a status monitoring dashboard for facilities managers and leadership; a general explorer application for public or campus-wide navigation; and a mobile update application for field maintenance staff to update asset records without desktop GIS skills. A live demonstration showed the near-complete City and County of Broomfield, Colorado deployment, with full building floor plans, oriented imagery at every scan position, and clickable room views tied to BLK2GO captures throughout the facility.
The Bigger Picture: What This Session Tells Us
The digital twin definition debate is not semantic — it’s strategic. Organizations investing in 3D modeling and spatial data infrastructure will get fundamentally different returns depending on whether they build a digital representation or a connected system that answers operational questions. Practitioners who start from the customer’s problem and work backward to the data architecture will build the more valuable systems.
AI is shifting infrastructure inspection from documentation to prediction. When every defect has a unique ID, a GIS coordinate, and a measurement history across multiple inspection cycles, the dataset becomes a condition trajectory — not a snapshot. GeneXT’s platform is an early example of what predictive maintenance looks like when the underlying data infrastructure supports it.
Indoor mapping is moving from a specialized service to a regulatory requirement. The K–12 legislative mandate Langan described is a leading indicator. As requirements expand into healthcare, higher education, and corporate campuses, the organizations with established indoor mapping workflows will be positioned to absorb substantial demand.
Data accessibility is the last mile problem. All three presenters returned to the same challenge: collection and processing are solved problems. Making the outputs accessible, maintainable, and useful to non-technical stakeholders — and keeping them current over time — is where the real work remains.
Interoperability is the prerequisite for everything else. Every effective system in this session was built on interoperability as a design principle: common location standards, native integration with CAD and GIS workflows, and delivery pipelines designed for browsers rather than engineering workstations.
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