Mining & Metals
Computer Vision for Mining & Metals
Computer Vision for mining & metals, built around the constraint that defines the sector: the environment is hostile to hardware and safety compliance is non-negotiable.
- Regulations in scope
- 3
- Systems we integrate
- 4
- Typical first release
- 6 weeks
What changes when it is mining & metals
Orqent Labs builds computer vision for manufacturing, safety and retail operations, reported honestly per class rather than as a single flattering accuracy number.
In mining & metals, the environment is hostile to hardware and safety compliance is non-negotiable. That single fact reshapes how computer vision has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.
The workload we are most often asked to take on first is environmental compliance reporting, usually integrated against SCADA. Integration comes before intelligence. A model that cannot reach your systems of record is a demo with good manners.
Deployed across regulated and unregulated sectors, with audit trails where the regulator expects them. You own the code, the models where they are open-weight, and the documentation to run it without us.
The sector constraints we design around
- Defining constraint
- the environment is hostile to hardware and safety compliance is non-negotiable
- Regulations in scope
- DGMS safety regulations · environmental clearances · mineral concession rules
- Systems of record
- fleet management · SCADA · ERP · geological modelling software
- Where we usually start
- PPE and safety compliance monitoring
Computer Vision workloads in mining & metals
- PPE and safety compliance monitoring
- haul fleet optimisation
- equipment failure prediction
- ore grade estimation
- environmental compliance reporting
What is included
- Data collection protocol and labelling workflow
- Model training against your real conditions and lighting
- Edge deployment with offline tolerance
- Precision and recall reported per defect class
- Integration with MES, PLC or alerting systems
- Retraining pipeline as conditions drift
Questions from this sector
Will cameras survive site conditions?
With appropriate industrial housings, yes. Hardware selection matters more than model selection in mining deployments.
Can it improve safety compliance?
PPE and exclusion-zone monitoring provide consistent, documented observation that manual supervision cannot match across a full shift.
How much training data do we need?
It depends on defect variability, but a few hundred well-labelled examples per class is a realistic starting point. We design the collection protocol first so the data you gather is actually usable.
Does it run without internet?
Yes. We deploy at the edge with offline tolerance, syncing results when connectivity returns, essential in most plant environments.
What accuracy can we expect?
We report precision and recall per defect class against a held-out set from your line, rather than a single headline number. The honest figure varies by class and we show which ones are hard.
Other capabilities for mining & metals
- AI Agent Development for Mining & Metals
- Agentic Workflow Automation for Mining & Metals
- LLM Application Development for Mining & Metals
- RAG & Knowledge Retrieval for Mining & Metals
- Chatbot Development for Mining & Metals
- AI Copilot Development for Mining & Metals
- Data Engineering for Mining & Metals
- Enterprise AI Platform for Mining & Metals
- Workflow & Integration Automation for Mining & Metals
- AI Readiness Assessment for Mining & Metals
Computer Vision for mining & metals, worth a conversation?
Tell us the workload and the regulation it sits under. We will tell you what is realistic.
Or email bd@dtrasglobal.com · call +91 74118 77878