What we do

Professional services for real industrial problems.

We have proven experience helping organisations overcome production, quality and operational challenges through data-centric solutions, independent of any specific software and aligned with their objectives.

Asset-intensive experience

Deep experience in mining, manufacturing, energy and process industries - not generalist IT.

Operations & data fluency

Strong understanding of industrial data, control systems and operations – bridging engineering, operations and data teams.

Industrial analytics & AI

Predictive and diagnostic analytics, ML for quality and maintenance, process optimisation, decision support and context-driven analysis across systems.
Our Process

From discovery to validated outcome, in four stages.

Our independent integration services help you make progress while keeping risk manageable. We provide consistency by adopting a formal structure each time – so you know what’s coming, what’s expected of you and what will be delivery at the end.

01
Discovery

Understand the problem

Stakeholder interviews and a review of your current systems, data and processes to identify high-value opportunities. Output: agreed problem statement, success criteria and target metrics.
02
Agree scope

Define the engagement

Select focus area and data sources, define timeline, roles and deliverables, and finalise commercial terms. Output: a signed PoV agreement with clearly defined scope, use case and success metrics.
03
Implement

Demonstrate measurable value

Configure the solution against your data, execute the agreed workflows, dashboards or analytics, with regular check-ins to review progress. Output: a working model, dashboard or system aligned to the agreed criteria.
04
Review

Validate & further improvements

Present findings to business and technical stakeholders and discuss additional value opportunities. Output: customer-validated success and opportunities for further improvement.
Example outcome · Root cause detection

Finding hidden causes in interconnected systems.

A manufacturer had a recurring, unexplained loss of temperature control across their gas-fired ovens - no obvious trigger and no warning. Optrix used ARDI's Timeline addon to scan for statistically significant events around each loss-of-control. The common thread sat on the other side of the facility: a cleaning tank purge was leaving its burner valve fully open onto an empty tank, briefly starving the rest of the line of gas. There were no gas pressure sensors and only one site-wide flowmeter, so the cause was invisible on conventional trends.

ARDI Timeline root-cause diagram showing cleaning tank, shared gas supply, four ovens, and the 5-minute lead time between purge event and loss of control.
5 min

hidden lead time between purge and loss of control

Remote

investigated by an analyst who had never been on site

Procedural

resolved without hardware change; control quality and gas efficiency both improved

The engagement followed the four stages above - Discovery through to Review - with the root-cause hypothesis validated against historical events before any process change was made.

More from the field

Different industries, same engagement model.

Each engagement starts with a problem statement and ends with validated outcomes. Across steelmaking, renewable energy, mining and manufacturing, the same four-stage process has applied - adapted to whatever the customer's data, equipment and operational priorities required.

Coke oven battery management · Steelmaking

50 coke ovens with data dispersed across a historian, an Oracle database and Excel files at varied recording intervals. Optrix synchronised around 3,600 values across mismatched time cycles into a 3D visualisation - surfacing hidden setpoint inconsistencies, push-torque variations and data issues that existing SCADA and reports were missing.

Field access at hydro power plants · Renewable energy

Field personnel were losing time on trips back to the control room or waiting on operators for HMIs, drawings and work instructions. ARDI's digital twin plus AR on existing mobile devices put real-time data and documentation in the field - no new hardware, faster decisions, and remote out-of-hours support for on-site staff.

Maintenance compliance · Manufacturing

Routine maintenance was thorough but hard to verify, and harder to prove for regulators. ARDI's Checklist and Checkmate addons turned routine checks into guided, web-based checksheets with live equipment data - auditable records of who did the check, when, and what the equipment was actually doing at the time.

Remote longwall operations · Underground coal mining

A longwall mine face stretching hundreds of metres underground, with information scattered across multiple systems. ARDI's 3D visualisation consolidated roof support heights, pressures, angles and positions into a single live view - supporting remote operations, surfacing faulty sensors, and enabling incident replay for compliance reporting.

Virtual sensor for in-tank temperature · Process manufacturing

A heating element inside a sealed liquid container relied on a failure-prone internal probe. An ARDI-trained LSTM model estimates the internal temperature from external sensors only - typically within 2°F of the actual reading at 1200°F - with discrepancy alerts that flag when the physical probe drifts or freezes, so operators can keep control and schedule a replacement.
 
Get started

Start with a simple conversation.

We usually begin with a short discussion to understand your environment, your priorities and where better data or analytics could make the biggest impact - and what a focused PoV could prove.
Talk to Optrix Try ARDI →