Built for network operators and network owners
ConVis turns existing customer data into a network-wide operational 3D twin. Spatial Data Capture creates missing spatial detail from available plans and documentation wherever possible, then captures only the remaining, decision-relevant gaps.
Anonymized first demo · no customer data or system access required.
ConVis + Spatial Data Capture
ConVis starts with existing customer data rather than assuming everything must be captured again. Available records, plans and documentation are turned into an operational 3D context; missing spatial information is created from existing source material where possible and captured only where required.
ConVis platform
Available site, asset, topology, plan and documentation data become a shared spatial workspace for RF review, planning, validation, acceptance and handover.
Spatial Data Capture
Where relevant geometry or site detail is absent, available plans and source material are converted into usable spatial data first. Targeted capture is added only when the intended workflow requires more.
Use what is already available. Convert existing source material into usable spatial data. Capture only the remaining gaps. Keep every validated addition reusable in the shared layer.
Value logic
Network operators often already have useful records. ConVis makes them spatially accessible, exposes gaps and adds precision only where the target workflow requires it. The result is better review quality, scalable reuse and a structured basis for workflows and automations.
Shared context
Records, drawings and evidence become accessible in one shared 3D context so teams evaluate the same spatial situation.
Decision quality
RF coverage, feasibility, validation and handover improve where representation is fit for the target workflow.
Network scale
Existing data, plans and remote methods form the network-wide starting point; new capture focuses on decision-relevant gaps.
Automation
Consistent spatial data supports repeatable QA, validation and customer-specific workflows and automations.
The relevant value mix depends on the operator, data situation, target workflow and rollout stage. Automation often carries the largest long-term potential and compounds as formats, rules and workflows become repeatable.
Implementation flow
Existing network records create the network-wide starting point. A workflow-specific data and confidence check shows what can be used immediately and where uncertainty affects a decision. Only those gaps trigger targeted spatial capture; validated updates return to the shared ConVis twin.
01 · Existing data
Topology, sites, assets, plans, mast documentation and location data form the starting point.
02 · Network-wide base twin
Existing records become a functional 3D context across the network before broad new capture begins.
03 · Data u0026 confidence check
Review what is usable now, what remains uncertain and which gaps affect the decision.
Use the base twin now
Where available detail is sufficient, planning, validation and review can start immediately.
04 · Targeted spatial capture
Use plan conversion, remote digitization, targeted measurement or selective scans.
05 · Validate u0026 return
Validated updates, evidence and agreed outputs return to the shared twin or customer systems.
Build the network-wide base twin
01 · Existing data
Topology, sites, assets, plans, documentation and location data.
02 · Network-wide base twin
Functional 3D context before broad new capture begins.
03 · Data u0026 confidence check
Review what is usable, what is uncertain and what affects the decision.
Enrich only where decisions require it
Usable for the workflow
Review, planning and validation can begin without new capture.
Decision-relevant gap
Plans, remote digitization, measurement or selective scans.
Accepted updates return to the shared twin or customer systems.
ConVis workflows u0026 automations
ConVis already supports workflows and automations for RF review, visibility checks, planning context, fiber routes, acceptance loops, indoor assets and site-specific analysis. Because every operator has its own data structures, rules and operational constraints, ConVis adapts these capabilities to the customer environment.
Supported today
All listed workflows and automations are already supported. The library shows available capabilities, not a future roadmap.
Problem-led workflows u0026 automations
Customers can bring a concrete requirement or an operational problem. Glaucus translates it into practical workflows, checks and automation logic.
Integrated by design
Data structures, technical rules, toolchains and acceptance processes are mapped into the way the workflow is delivered.
Featured workflows u0026 automations
RF coverage
Review antenna position, height, azimuth, obstacles and RF context in 3D before field work. Coverage becomes a spatial workflow, not only a disconnected calculation or map layer.
vLOS
Check line-of-sight, Fresnel clearance, height assumptions and obstacles directly in the 3D model.
Reachability
Review access, mounting positions, maintainability and site constraints before a team goes on site.
Explore more workflows u0026 automations
Filter the library or scroll horizontally. Every card represents a supported capability.
Reachability
Review access, mounting positions, maintainability and site constraints before a team goes on site.
Planning
Use visual context, vLOS and reachability to plan more efficiently and structure rules for customer-specific planning automation.
Network data
Represent fiber routes precisely from available network data, keeping physical paths and network relationships reviewable in the shared 3D context.
Routing
Visualize routing, link relationships and network logic directly in the shared 3D context.
Indoor u0026 assets
Map technical rooms, cabinets, racks and asset-to-location relationships where they affect rollout or validation.
Site context
Review wind turbines, cranes and other national or project-specific obstacle layers in the same spatial workflow.
VR · Live showcase
Use immersive ConVis review for planning, training or stakeholder alignment — demonstrated live in the InnovationArea in Munich.
Solar
Assess solar potential and shadow context in a dedicated site-analysis workflow where relevant.
Swipe to explore more workflows
Spatial Data Capture
The capture model is built for efficient rollout: reuse existing records, plans and source material first, digitize remotely where possible and capture precise spatial data only where reality changes the decision. Selective scans remain available for complex cases, but they are not the default starting point.
Existing records and plans
Remote digitization where possible
Targeted reality where required
Accepted updates return
Scale u0026 remote preparation
Scalable base
Existing network data can create the network-wide ConVis twin first. Topology, sites, assets, plans and location data form the starting layer before new capture work is scoped.
Efficient remote methods
Approved 2D plans, drawings, rooms, racks and position indications are converted into structured spatial data that can be reviewed and reused inside ConVis.
Efficient remote methods
Where source quality is sufficient, essential mast elements are digitized remotely into fit-for-purpose 3D models for efficient rollout cases.
Increase precision where needed
Swipe through remote and decision-critical capture methods.
Decision-critical precision u0026 accepted state
Decision-critical
When reality changes the decision, teams capture only relevant elements: azimuth, height, coordinates, offsets, photos or completion evidence.
Decision-critical
Scans remain available for complex sites, customer requirements or cases where dense geometry is truly valuable — but they are not the default rollout method.
Update loop
Planned targets, installer evidence and measured reality are compared. Accepted as-built updates return to ConVis or agreed customer systems.
Capture automation path
ConVis spatial data capture is designed to deliver usable output today from existing customer material. Based on customer needs, Glaucus has specialized in PDF-based digitization, while CAD and other structured source formats can also be supported where available. The current delivery model is partly automated and expert-guided; automation reduces repetitive work, supports checks and prepares outputs while customer-specific material remains controlled.
Deliver now
Existing customer material such as PDFs, CAD files, plans and structured records can become usable spatial data without starting every case with full field capture.
Automation, checks and workflow tooling reduce repetitive work so expert effort focuses where source ambiguity or customer-specific judgment matters.
Increase automation continuously
Customer formats, naming conventions, acceptance criteria and output requirements are translated into repeatable delivery logic.
Where inputs and rules become stable, conversion, QA and output preparation can be automated further for faster and more scalable delivery.
Automation increases where formats, rules and acceptance criteria repeat.
Proof of Value
A ConVis Proof of Value starts with a representative area, available customer material or an operational network problem. It demonstrates the approach in a realistic customer context, exposes assumptions early and creates the evidence needed to decide whether — and how — the rollout should continue.
Scope the sample
Define the representative area, source material, target use case and acceptance questions the PoV should answer.
Build the sample twin
Transform available material into a ConVis sample twin and make gaps and assumptions visible.
Validate the approach
Review the relevant workflows, data assumptions and acceptance criteria on the sample.
Decide the next step
Compare demonstrated value, remaining assumptions and implementation effort before committing to a broader rollout.