Mining & Metals

Enterprise AI Platform for Mining & Metals

Enterprise AI Platform 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

Shadow AI is already happening in your organisation. A platform does not stop it by policy, it stops it by being easier to use than a personal API key.

In mining & metals, the environment is hostile to hardware and safety compliance is non-negotiable. That single fact reshapes how enterprise ai platform 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 PPE and safety compliance monitoring, usually integrated against ERP. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.

Multi-model by default, so a provider outage is a routing decision rather than an incident. 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

Enterprise AI Platform workloads in mining & metals

  • PPE and safety compliance monitoring
  • haul fleet optimisation
  • equipment failure prediction
  • ore grade estimation
  • environmental compliance reporting

What is included

  • Model gateway across providers with failover
  • Central prompt and template registry with versioning
  • Per-team quotas, budgets and cost allocation
  • Policy enforcement, PII handling, allowed models, data residency
  • Full audit log of every prompt and response
  • Self-service onboarding for product teams

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.

Why not let teams call the APIs directly?

Because you lose cost visibility, audit trail and policy enforcement, and you end up with keys in a dozen repositories. A gateway gives teams the same speed with none of that exposure.

Does it lock us to one model provider?

The opposite, the gateway is what makes providers swappable, with failover when one has an outage.

How long does a platform take?

A usable first version with gateway, logging and quotas typically lands in six to eight weeks; governance depth grows from there.

Enterprise AI Platform 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