ViSNET AI — True Intelligence

Platform

One intelligence layer under every ViSNET application

ViSNET AI ingests visual data from the sources you already operate, converts it into structured records, and exposes those records to applications and to the systems your teams work in. The applications differ; the pipeline underneath them does not.

  • 01Capture
  • 02Detect
  • 03Structure
  • 04Deliver
Capture to delivery, one pipeline

Architecture

The chain from capture to decision

Each layer is deliberately separable. You can start with one capture source and one application, and add others without re-implementing the layers below.

  1. 01

    Physical world

    Bridges, plants, sites, buildings, workforce and work in progress.

  2. 02

    Visual data capture

    Existing CCTV, drones, mobile devices, sensors and VR/MR spatial capture.

  3. 03

    ViSNET AI intelligence layer

    Computer vision, spatial reconstruction and analytics that turn imagery into structured records.

  4. 04

    Applications

    Infrastructure Intelligence · MRLAYOUT · EHS & Workforce Intelligence.

  5. 05

    Workflows and decisions

    Inspection reports, attendance records, digital twins, forecasts and alerts inside existing operations.

Inputs

Data the platform works from

ViSNET is designed around visual data that most operations already generate, which keeps deployment cost concentrated in software rather than new hardware.

Capture sources

  • Existing CCTV infrastructure on sites and facilities
  • Drone imagery of structures and large assets
  • Mobile device photography from field teams
  • VR and MR spatial capture through MRLAYOUT
  • Sensor inputs alongside visual data

What the platform produces

  • Classified defect records with location and measurement
  • Digital attendance and workforce deployment records
  • 3D models and measurable digital twins
  • Condition and workforce history per asset, site and contractor
  • Automated reports and operational alerts
  • Exports and API access into ERP, CAD, BIM and operational systems

Intelligence layers

Three layers, one data model

These layers are what the applications are assembled from. An application is a workflow surface over one or more layers, not a separate product with its own database.

Infrastructure Intelligence

Turns visual inspections into a maintained record of asset condition.

  • AI-powered defect detection
  • Digital twins and 3D asset models
  • Asset health monitoring
  • Structural condition assessment
  • Predictive maintenance insights
  • Automated inspection reporting

Workforce Intelligence

Digitises labour operations from cameras already installed on site.

  • Automated entry and exit tracking
  • Workforce attendance automation
  • Labour productivity analytics
  • Contractor performance monitoring
  • Workforce utilisation insights
  • Trade-wise workforce visibility

Project Intelligence

Correlates workforce and progress data into schedule signals.

  • Progress monitoring
  • Delay prediction
  • Completion forecasting
  • Resource optimisation
  • Workforce versus progress correlation
  • AI-powered recommendations

AI agents

AI agents for infrastructure inspections

Agents sit on top of the intelligence layer and turn its output into completed workflow steps — without a person writing the record by hand. Select an automation to expand its workflow, indicative impact and the application capabilities it feeds.

Defect classification from drone imagery

Drone capture is routed straight into a classified defect record, so an inspection flight produces a ready-to-review register instead of a folder of images.

Workflow, step by step

01Drone imagery of the structure is ingested after each flight

Drone imagery of the structure is ingested after each flight

02Detection models classify defects

Detection models classify defects — cracks, corrosion, spalling, rebar exposure — with confidence and location

03Each finding is pinned to the asset record and the 3D twin in MRLAYOUT

Each finding is pinned to the asset record and the 3D twin in MRLAYOUT

04A draft inspection report is assembled from the classified findings for review

A draft inspection report is assembled from the classified findings for review

Indicative impact

Example review time per structure
hours, not days
Typical target range for manual triage removed
40–70%
Findings carrying location and severity
every record

Illustrative ranges, not guaranteed outcomes. Actual results depend on capture coverage, asset class and current process.

Capabilities this supports

Infrastructure IntelligenceAI defect detection and condition historyMRLAYOUTDefect pinned to the measurable 3D twin

See these agents run on your own capture

Book a demo and we will walk one automation end to end against an asset class you operate.

Request a demo

FAQ

AI agents for infrastructure inspections — common questions

What are AI agents for infrastructure inspections?

They are automations that sit on top of the ViSNET intelligence layer and complete an inspection workflow step end to end — ingesting drone or CCTV capture, classifying findings, writing them to the asset record and assembling a report draft — instead of leaving a person to do it manually.

Which inspection tasks can ViSNET AI agents automate?

Defect classification from drone imagery, attendance and workforce deployment logs from existing site CCTV, and structured inspection report drafting from capture and detection output.

Do AI agents replace the inspection engineer?

No. Agents prepare the record — classified findings, measurements, location and a report draft. A qualified reviewer validates, edits and signs off before anything is issued.

What data do the agents need to run?

Visual data you already generate: existing CCTV coverage, drone imagery of structures, mobile photography from field teams and MRLAYOUT spatial capture. No new hardware class is required to start.

How do the agents connect to Infrastructure Intelligence, MRLAYOUT and EHS?

All three applications read the same data model. An agent writes once and the output surfaces as a defect record in Infrastructure Intelligence, a pinned finding on the 3D twin in MRLAYOUT, or a workforce record in EHS & Workforce Intelligence.

Spatial layer

MRLAYOUT: where the layers become visible

MRLAYOUT provides the 3D environment the other layers are read in — a defect shown on the structure it belongs to, activity shown in the space it happened in, condition compared across capture dates. Models are browser-accessible and exportable to CAD, BIM, DWG, IFC and GLB.

Where to go next

Applications built on this platform

01

Infrastructure Intelligence

Defect detection, condition history and inspection reporting for critical assets.

Read more02

MRLAYOUT

Spatial capture, measurement and shareable 3D digital twins.

Read more03

EHS & Workforce Intelligence

Safety monitoring, digital labour management and project forecasting from CCTV.

Read more

Talk to an expert about your data sources

Tell us what you already capture — camera coverage, drone imagery, inspection archives — and we will map it against what the platform can produce.

Talk to an expertExplore solutions