Measured by survey.
Volumes and distances need a survey crew, so they are checked rarely.
Depth from a single camera.
How far.
How big.
How much is left.
Wherever the work is.
Hosted
Private cloud
On-premise
Edge
Air-gapped
A photo is flat.
The work isn't.
Cameras and drones capture a site every day, but a picture can't tell you how much is in a pile, how close a person is to a moving machine, or whether a load fits under a beam.
Guessed in between.
Between surveys, people estimate from experience and truck counts.
Safety distances assumed.
Clearance and separation rules are written down, but rarely measured while the work happens.
What the AI
can measure.
One image in.
A measurement out.
The model does one hard job: working out how far away each part of the image is. Everything after that is geometry and rules, which is cheap, fast and checkable.
Images inSense
Drone surveys and the fixed cameras you already have.
Depth estimationSpecialized model
Every pixel given a distance.
Surface & scaleRules & code
Ground markers and known sizes fix the scale.
MeasureRules & code
Volumes, distances and clearances computed.
CompareCheck → Operate
Against book stock, limits and design.
Down 1,420 m³.
Sent to the site manager.
Survey SV-0714 · stockpile SP-3. Measured, not assumed. Every volume keeps the surface it came from.
Captured. 1,860 photos from the morning flight at 4 cm ground resolution.
Built. Depth and surface model; scale fixed by six ground markers.
Measured. 12,480 m³, from contours at 0.5 m intervals.
Compared. Book stock is 13,900 m³: a variance of −10.2%.
Illustrative example. Site, survey and figures are fictional.
Built for
the site.
Measurement is only useful if it happens often and can be checked.
-
Uses the cameras you have.
Works from the drone surveys and fixed cameras you already run.
Site Measurement -
Shows its workings.
Every figure comes with the surface it was measured from and the calculation.
How Check works -
Runs on site.
Processing can run on a site server, with results sent when there's a connection.
Deployment options
Where it runs.
The AI goes to where the work is, from hosted to air-gapped.
A managed environment.
Start with a hosted service when speed of adoption and managed operations are priorities. Agree data handling, access and service requirements as part of the engagement.
Discuss hostedIn the cloud you use.
Deploy dedicated instances in your AWS, Azure, Google or Oracle account. Align the architecture with your cloud standards, operational responsibilities and integration requirements.
Discuss public cloudWithin your enterprise network.
Run it inside your own private cloud or VPC, with network access, storage and controls set around your boundary.
Discuss private cloudOn your infrastructure.
Run software, storage and local inference on your own servers. Plan capacity, integration, maintenance and support around the environment your team operates.
Discuss on-premiseClose to the operation.
Place intelligence near industrial sites and operational equipment, where latency and connectivity shape the design. Match the workload to the local compute available.
Discuss edgeWithout constant connectivity.
Operate local workflows without a continuous internet connection. Define how data is transferred, how updates are applied, and what must remain available offline.
Discuss offlineA physically isolated environment.
Plan for an installation with no external network connection. Local models, dependencies, data transfer and maintenance all become part of the deployment design.
Discuss air-gappedThe other capabilities.
Each one is tested on your own work before you rely on it.
Sense
It sees, hears and reads the work as it happens.
Explore Sense →Understand
From piles of paper to records you can use.
Explore Understand →Check
Every line compared. Only the gaps reach you.
Explore Check →Investigate
Follow the evidence across systems. Find out what happened, and why.
Explore Investigate →Anticipate
Know what comes next, and plan for it.
Explore Anticipate →Operate
The next step, taken. The reason, recorded.
Explore Operate →Bring us the work where wrong is expensive.
Start with the operational problem. We’ll work out the data, models and agents it needs, and where it should run.
Talk to us →LondonDiscovery AI Limited · United Kingdom
HyderabadReDscvry Technology Private Limited · India
ChennaiReDscvry Technology Private Limited · India