Engineers are pulled in after the event
Alarms tell teams that a limit has been crossed. The engineering investigation into why it happened often starts only after performance has already deteriorated.
AI engineering · Continuous-process operations
The AI Engineer for
Continuous-Process Operations
Give every process an engineer that never stops watching. Veldar continuously understands process behaviour, investigates deviations, identifies opportunities and helps your team determine what should happen next.
Live process feed Unit 3 energy intensity 8.1% above physics baseline
Investigation Heat exchanger HX-14 fouling signature developing
Live anomaly Compressor Train B surge margin decreasing
Decision Pump Station 3 setpoint review recommended
Live efficiency Water treatment line operating at 91% of design efficiency
Engineering model Mass and energy balance model updated
Live process feed Unit 3 energy intensity 8.1% above physics baseline
Investigation Heat exchanger HX-14 fouling signature developing
Live anomaly Compressor Train B surge margin decreasing
Decision Pump Station 3 setpoint review recommended
Live efficiency Water treatment line operating at 91% of design efficiency
Engineering model Mass and energy balance model updated
01
Observe
Connect live plant data.
02
Understand
Interpret behaviour through physics.
03
Decide
Evaluate the best next action.
04
Act
Integrate with people and systems.
05
Autonomously Optimise
Improve continuously within safe limits.
The problem
Plants have more software and data than ever.
Engineering insight is still fragmented.
Engineering insight is still fragmented.
Too much data, too little investigation
Historians contain years of process data, but engineering teams rarely have time to investigate every drift, inefficiency or emerging constraint continuously.
Engineering knowledge does not scale
Experienced engineers carry critical process context in their heads. Veldar helps make that reasoning persistent, repeatable and available across the operation.
How the AI engineer works
From plant data to
trusted action.
Veldar works alongside your operations and engineering teams, continuously turning plant data into engineering work: observing the process, building context, investigating what is changing, evaluating options and recommending the next action. It complements the systems already running the plant rather than replacing them.
Plant evidence
Continuously reads SCADA, historians, PLCs, sensors, CMMS, laboratory data and engineering records.
Build context
Understands design intent, operating envelopes, asset relationships, process constraints and current operating state.
Investigate
Uses engineering knowledge, first-principles models and available analytical tools to test hypotheses and explain behaviour.
Recommend
Evaluates causes, constraints, trade-offs and scenarios before recommending the most appropriate next action.
Act & learn
Works through people and existing systems today, then learns from outcomes and progresses toward bounded autonomy where appropriate.
Applications
Start with one decision.
Expand across the plant.
Each deployment begins where the operational value is clearest. The same intelligence layer can then extend across assets, process units and sites.
01 · Reliability
Understand degradation before failure
Identify developing faults from the physical behaviour that causes them—not only from late-stage vibration or temperature symptoms.
OutcomeEarlier action
02 · Energy
Expose hidden energy waste
Compare current operating behaviour with physics-based efficiency baselines to find drift, fouling and poor setpoints.
OutcomeLower cost
03 · Throughput
Find the real bottleneck
Use mass and energy balances to distinguish true capacity constraints from avoidable operating inefficiency.
OutcomeMore output
04 · Scenario analysis
Test changes before committing
Explore changes in feedstock, throughput targets, equipment configuration or operating conditions before applying them in the plant.
OutcomeLower risk
05 · Autonomy
Build toward self-optimising operations
Ground progressively more automated decisions in physics, process constraints and human-defined operating limits.
OutcomeTrusted autonomy
Why Veldar can reason like an engineer
AI that understands the
physical process.
01
Grounded in engineering
Veldar reasons from process relationships, physical laws, design intent and operating evidence—not historical correlation alone.
02
Built to investigate
Like an engineer, Veldar can combine evidence, calculations, models and competing hypotheses to work through why a process is behaving differently.
03
Designed for accountable action
Recommendations can show evidence, assumptions and constraints, while actions remain bounded by engineering limits and human-defined operating envelopes.
Where Veldar works
Built for continuous
process operations.
Veldar is designed for asset-intensive continuous-process environments where engineers must make sense of interconnected physical systems, ageing equipment and fragmented operational data.
Water & Wastewater
Network performance, pumping efficiency, treatment process stability and lifecycle planning.
Fluid systems
Chemicals & Process
Energy balances, debottlenecking, heat transfer, rotating equipment and continuous process optimisation.
Continuous process
Food & Beverage
Throughput, quality consistency, thermal processing, utility use and production-line reliability.
Production systems
Energy & Utilities
Asset integrity, efficiency, remote operations and safe automation across critical infrastructure.
Critical infrastructure
Pulp, Paper & Mining
Comminution, pumping, material flow, energy intensity and equipment lifecycle intelligence.
Asset intensive
Advanced Manufacturing
Process stability, resource efficiency, equipment performance and physics-grounded automation.
Industrial productionDesign partner programme
Help shape the AI engineer for industrial operations.
Veldar is working with a small number of industrial organisations to identify high-value engineering workflows, prove measurable outcomes and define the path from decision support toward trusted autonomy.
Discuss a Design Partnership- Start with one asset, process or line
- Use existing plant data where possible
- Define success before deployment
- Expand only after value is proven
Common questions
FAQ
No. Veldar is designed to sit above existing systems and use the operational data already available through historians, SCADA, PLCs, APIs and engineering records.
Veldar is designed to do more than answer questions or display analytics. It continuously observes the process, maintains engineering context, investigates deviations, evaluates possible causes and actions, and supports the team with evidence-backed recommendations. Underneath, it combines operational data with first-principles physics, engineering models and AI reasoning.
No. Reliability is one task the AI engineer can support. Veldar is designed to perform continuous engineering work across process performance, energy, throughput, asset behaviour, investigation, scenario analysis and, over time, bounded autonomous optimisation.
Yes. A deployment can begin with one asset class, process unit or production line and expand only after the value and data requirements are understood.
Autonomy is a progression, not a starting claim. Veldar moves from observation and understanding to decision support, workflow integration and, where appropriate, bounded autonomous optimisation under human oversight.
Start a conversation
What would you ask another process engineer to solve?
We begin with a focused engineering problem: a process deviation, recurring investigation, optimisation opportunity or decision your team would benefit from understanding continuously.
Email
mal@outreach.veldar.co