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Industrial AI & production optimization

We accelerate the factory you already own

More good production, lower cost per unit, fewer failures and longer asset life, from the data your plant already produces.

Predictive maintenance

We predict problems before they become failures

Each machine's normal behaviour is learned at every load, so slow drift is caught days before the line stops.

Maximum Profitable Sustainable Production

Find profitable capacity before you buy more

The target is not maximum machine speed. It is the best sustainable economic operating point for every line.

In collaboration with Axcelia

Industrial know-how. Specialist AI.

Smart Acceleration integrates the plant. Axcelia builds the models. Your team keeps every decision.

Pilot package

Give us one line. Let the numbers prove it.

One production line, 10 to 20 critical machines, typically 8 to 12 weeks.

Request a pilot

Our Approach

We start with the factory's business problem, not a pre-selected technology. Every machine is studied, then the line as one system.

Load per machine against sustainable capacity, from the platform

Line Study and Bottlenecks

Design, rated and actual capacity for every machine, then starvation, blocking, buffers and idle time across the line to find what really limits output.

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  • Example: machines at 120, 100, 140 and 115 units per hour. The 100 sets the line, and speeding up the others adds nothing.
  • Design maximum, then recommended continuous capacity, then actual sustainable capacity.
  • The safe operating envelope comes from maker data, testing and live measurement, never assumptions.
An explained alert card: what is wrong, why, when to act

Predictive Maintenance

Gradual deviation is found before the failure stops the line, and every alert explains the decision behind it.

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  • What is wrong, why, what could happen, when to act and the recommended action.
  • Example: pump bearing temperature 6.8 °C above its baseline for this load, vibration rising for 18 days, inspection advised within 72 hours.
  • Detect, diagnose, recommend, work order, repair, verify, learn.
Energy per good unit by consumer, from the platform

Energy and Utilities

Electricity, water, compressed air, cooling, steam and gas, each turned into a comparable cost per good unit.

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  • Example: Machine A makes 100 units per hour on 80 kilowatt-hours; Machine B makes 80 on 90. B uses about 41 % more energy per unit.
  • A machine needing more energy for the same output is often signalling a mechanical, electrical or process problem.
  • Sub-metering is added only where a real data gap exists.
Recommended operating point with its expected weekly margin gain

Verified Savings

Value you can verify, not promises. A saving counts only once it is measured against a baseline both sides agreed.

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  • Before, implement, after, verify, on the same indicators, normalized for conditions.
  • Every opportunity is tracked: identified, approved, implemented, verified.
  • Finance and operations can confirm the value themselves.
Maximum profitMargin and verified savings before raw output
SustainableOutput that holds without speeding up wear
Minimum costTotal conversion cost per good unit
Acceptable riskInside maker, safety and equipment-life limits

The Platform

It connects to the control systems you already run, reads data in one direction only, and never writes to a machine.

Health score over 30 days against the four health bands

Asset Health and Alerts

A health score for every machine and component, learned in context: load, speed, temperature, vibration, ambient conditions and history.

Normal80–100 Attention60–79 Action40–59 Critical<40
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  • Readings are validated, cleaned and put in context before any model is trusted.
  • Remaining useful life is shown as a figure only once enough data exists to validate it.
  • Models are watched for drift and retrained when plant conditions change.
Trade-off between margin and energy per unit for many operating points

Digital Twin and What-if

Test a decision before changing the factory. Raise output by 10 or 15 % and see the new bottleneck, energy, rejects and maintenance risk.

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  • Compare current, optimized and maximum sustainable scenarios side by side.
  • The optimizer proposes the best sustainable operating point and shows its trade-offs.
  • Recommendations only. An operator applies each change after a named approval.
Executive dashboard tiles: output, equipment effectiveness, energy and water per unit

One Dashboard, Every Level

From the boardroom to a single sensor: factory, line, machine, energy, maintenance, quality and finance, in English and Arabic, with six user roles.

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  • Production per day, equipment effectiveness, sustainable target and cost per good unit at the top.
  • Every machine has a profile: maker, age, capacities, history and live condition.
  • Each role sees what it needs; finance figures stay with the people allowed to see them.

With Axcelia

Industrial know-how and specialist AI, with clear responsibilities agreed from day one.

Smart Acceleration

Smart Acceleration Technology

Owns the industrial problem, plant integration and the relationship with you.

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  • Plant study, criticality and problem definition
  • Data collection, sensors and edge gateways
  • Integration with control, supervision and maintenance systems
  • Implementation, commissioning and local follow-up

Axcelia

Our AI and advanced analytics partner, building and improving the models.

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  • Data analysis and machine learning
  • Anomaly detection and failure prediction
  • Specialized models per equipment type
  • Continuous model improvement and retraining

And your team

Sets the goals and the pilot line, provides data and site access, validates recommendations and approves work orders and investments.

  1. EquipmentMachines and utilities
  2. Existing controlsControllers and meters
  3. Edge gatewayRead-only collection
  4. Data platformSmart Acceleration
  5. AI and analyticsAxcelia
  6. Health and predictionAnomaly and risk
  7. RecommendationAction and urgency
  8. Work orderYour maintenance system
  9. Verify and learnBack to baseline

In the contract from the start: data ownership, use of anonymized data, model and intellectual property ownership, confidentiality, cybersecurity duties and service responsibilities.

Walkthrough of Our Work

From the factory's problem to verified value in fifteen steps. Each stage ends with something you can check.

  1. 1

    Understand

    • 01Agree goals, pilot line and indicators
    • 02Map the process and stoppages
    • 03Assess every machine
  2. 2

    Measure

    • 04Balance the line, find the bottleneck
    • 05Audit energy, water, air and cooling
    • 06Close data gaps only where needed
    • 07Collect the baseline
  3. 3

    Analyze

    • 08Technical and AI analysis
    • 09Classify no-cost, low-cost and capital opportunities
    • 10Simulate current, optimized and maximum
  4. 4

    Decide

    • 11Feasibility, return and payback
    • 12Your approval, then installation
  5. 5

    Verify

    • 13Before-and-after on the same indicators
    • 14Deploy predictive maintenance
    • 15Monitor and report value

Inside the Pilot Platform

Choose a page to see it.

Executive Factory page with eight indicator tiles, a good-units chart, downtime summary, alerts and savings

The first page a manager opens: good units per day, equipment effectiveness, the sustainable production target, cost per good unit, energy and water per unit, fleet health and quality, with verified savings kept apart from expected ones.

Machine Profile page with the capacity ladder, health history, key signals and model monitoring

Every machine has its own profile: identity, the capacity ladder from design down to sustainable, remaining useful life, a 30-day health history and live signals against their learned bands.

Predictive Maintenance page with alerts and the six-field alert card

Each alert explains itself: what is wrong, why, what could happen, when to act, the recommended action and how confident the model is. Approved alerts become work orders.

Energy and Utilities page with energy per good unit by consumer and over 14 days

Energy and water per good unit, broken down by machine and utility, so the consumer using more for the same output stands out.

Optimization and What-if page with sliders, results, a scenario table and a trade-off chart

Move machine speeds and product mix and see output, margin, energy and the bottleneck before anything changes on the floor. The optimizer proposes the best sustainable point.

Screenshots from our working pilot platform, running on a simulated production line.

8machines and utilities
64signals read every 10 seconds
84health models
10model families
6user roles
2languages

Services

A business improvement project, not a maintenance-department project.

Capacity ladder for one machine: design, sustainable, recommended and measured

Pilot on One Production Line

1 line10–20 machines8–12 weeks

Assessment, data review, baseline, predictive opportunities, optimization scenarios and a full business case with capital cost, savings, return and payback.

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  • Deliverables: baseline, line study, opportunity register, an initial dashboard and the complete engineering and financial report.
  • Even if you stop after the pilot, you keep a full engineering and financial study of the line.
A live signal against its expected band

Monitoring and Improvement

After the pilot: continuous monitoring, predictive maintenance across the plant, periodic value reports and new opportunities as conditions change.

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  • Platform, models, dashboard and support as one annual service.
  • Models are checked for drift and retrained as the plant changes.
  • Shared-savings terms are possible where the baseline and calculation are agreed in the contract.

Before you buy more production capacity, do you know the maximum profitable sustainable production of the assets you already own?

Contact us

Contact Us

Start with one conversation about one line. Tell us what you want to improve and we will prepare for the first meeting.

Helpful to have ready

  1. 01Current output compared with design capacity
  2. 02Known bottleneck, downtime and recurring failures
  3. 03Energy and water per unit, and reject rate
  4. 04Annual maintenance spend

We use your details only to reply to this enquiry.