The answer is already in your systems. We make it reachable in minutes

AI for Manufacturing. We connect your machines, MES, ERP, quality and maintenance data into one operational context.

See how it works (3 min)

Trusted by industrial leaders

Philip Morris International
Lufthansa Technik
Gentherm
Schaeffler
Oerlikon
SEG Automotive
ESAB
Haarslev
FCA
OCME
Solaris
Lacroix
Vestas

Data-rich, but context poor

The answer to most production questions already exists across your systems. The hard part is pulling it together fast enough to act on, which is where our Digital Manufacturing stack does the heavy lifting. Pick a question on the left and watch the evidence line up. The same approach answers a question on the line and a question across every site.

No dashboard to read, no five people to chase. The system queried SCADA, MES, ERP, maintenance and four other sources, compared them, and returned a decision with its reasoning. That is the difference between data you can see and context you can act on.
Illustrative scenario. Response time reflects a connected i3X and Unified Namespace deployment.
Choose a question

Head of manufacturing

Across sites / Strategic

Plant manager

On one line / Operational

Which sites are underperforming against their own baseline, and why?

Today this takes days, across several teams
MES · all sites
Awaiting query
Historian
Awaiting query
Planning
Awaiting query
Quality
Awaiting query
Maintenance
Awaiting query
Get the answer

Where AI actually earns its keep

Five moments on the shop floor where connected data and AI change what your team can do, and how fast.

Line just stopped?

Find why it stopped, which order is at risk, and what to do, across SCADA, MES, ERP and maintenance in one query.

Line stoppage
Bottlenecks
Downtime root cause
Process drift
Hours to minutes

Delivery at risk?

See which orders a disruption is affecting, prioritise the critical ones, and reallocate production before customers feel it.

Affected orders
SLA risk
Fault diagnosis
Maintenance history
Schedule changes
Protect delivery commitments

Maintenance blocking output?

Diagnose faults, find spare parts, and see what worked last time, without chasing five different systems.

Fault diagnosis
Maintenance history
Spare parts
Repair recommendation
Planned downtime
Fewer surprises, more uptime

Defect back on the line?

Root-cause a quality issue across batch history, similar cases and process signals, so you fix the source, not the symptom.

Defect root cause
Batch genealogy
Similar historical cases
CAPA support
Stop repeat defects at source

Room to run better?

Optimise energy, throughput and process settings before problems appear, using patterns your data already contains.

Energy
Predictive maintenance
Throughput
Process settings
Yield improvement
Close the gap between planned and actual

Your case not here?

Talk to the expert

Jakub Kaczyński
Jakub Kaczyński
Industrial Portfolio Director
Talk with Jakub

See the advisor running on real data

This is the advisor running on a real data landscape, not a mock-up. It queries the actual ERP, MES, SCADA and stock systems across sites, compares throughput against baseline, reasons through what drove the numbers, and recommends where action pays off most. Built for the people running production across sites.

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Why most AI projects in manufacturing stall

Every new question ends up requiring the same integrations built from scratch. Data sits in silos, each system speaks a different language, and the AI can only see part of the picture. We solve this once.

Connected data layer

Every machine and system feeds into a single, organised data layer. So OT and IT data is available in one place, in real time.

Data that carries meaning

Raw signals are turned into contextualised, modelled data before AI ever sees them. No guesswork, no hallucination on bad inputs.

AI connects on demand

AI reaches any system without a new integration project for every question. When you ask, the answer comes from all sources, straight away.
The result: when you ask a question, the AI has everything it needs to answer it across all your systems, straight away.
Technologies behind this:

What connected data and AI change in practice

Not marketing metaphors. Typical shifts our customers see when machine, enterprise and quality data start working together.

-35%

time to root cause

+15%

OEE improvement

10

days to first working results

-25%

unplanned downtime

Illustrative benchmarks from connected i3X and Unified Namespace deployments. Actual results depend on plant maturity, integration scope and the specific use case in production.

From shop-floor signal to decision

Four layers turn connected data into decisions teams can act on. Each one builds on the layer below it.

1
Trusted production data

Connected machines and systems

Connect machines, lines and OT systems so shop-floor data becomes available, structured and ready for analytics and AI.
2
Business-aware operational data

Business context

Combine production signals with ERP, MES, quality, maintenance and supply chain so teams understand what happened and what it affects.
3
Faster insight and reasoning

AI and analytics

Apply ML, analytics, pattern detection, evidence comparison and root-cause reasoning to detect patterns, identify likely causes or risks and recommend actions.
4
Actionable decisions

Decisions and workflows

Provide factory copilots, AI investigations, root-cause support, order-risk assessment and recommended actions so teams respond faster and more consistently.

Use the right AI for the question

Predictive AI forecasts what may happen. Generative AI (GenAI) and agents help teams understand what is happening, why it matters and what to do next. Each fits different problems, and both matter.

FMCG
100+ instances

Predicts what may happen

  • Predictive maintenance
  • Predictive quality
  • Anomaly detection
  • Process parameter optimisation
  • Energy consumption optimisation
  • Forecasting and planning
  • Computer-vision quality inspection
Generative and agentic AI

Explains what is happening and what to do

  • Factory copilots
  • Talk to your factory and enterprise data
  • Worker decision support
  • Automated investigations and workflows
  • Answers grounded in operational context
  • Human approval and audatibility

The right tool for the question

Sometimes it's predictive, sometimes GenAI, sometimes both. We match the approach to the problem, not the other way round.
We also handle model monitoring and MLOps in our support & maintenance services, so performance does not degrade after go-live.

Why manufacturers work with us

Vendor-neutral by design

You get the technology that fits your plant and budget, not the stack a single supplier needs to sell you.

We build on what you have

Your existing systems stay in place and start working together, so you protect past investment instead of ripping it out.

One partner across OT, IT and AI

A single team connects the shop floor, enterprise systems and AI, so no gap is left for others to own.

AI that runs in production

You move past pilots to workflows that people use every day, so the investment shows up in real operational results.

AI is only as good as the data behind it. We fix both

TT PSC are advisors first. We can start at any level, so wherever you are today there is a sensible first step.

No connected machines yet?

We start with industrial connectivity and OT/IT integration.

No trusted data?

We build the data foundation and a manufacturing data platform.

AI stuck in a pilot?

We fix the missing context and grounding, and get it into production.
What that includes:
Data foundation
Enterprise system integration
Manufacturing data platforms
Operational context
ML models & AI assistants
Multi-agent workflows
Model monitoring
Advisory and rollout

Start with your most pressing question

A 60-minute diagnostic workshop turns your biggest operational question into a clear view of where to start.

Book a free diagnostic
1

Book and align

30-minute intro call to agree on your biggest question and who should be in the room.
2

60-min diagnostic

Working session with your team. We map your systems, data and the question you want answered.
3

Roadmap

Within one week: a concrete plan with sequence, effort and estimated first results.
4

Your decision

Continue with a paid pilot, adjust scope, or walk away. No pressure, no commitment.

Common questions

AI for Manufacturing brings analytics, machine learning, generative AI and multi-agent workflows to production data. It helps teams answer operational questions faster by reasoning across data that sits in machines, MES, ERP, quality and maintenance systems. Rather than a single product, it is a category of applications: factory copilots, predictive maintenance, anomaly detection, root-cause investigations, and cross-site comparisons. See our take on Predictive AI vs GenAI in manufacturing for a deeper split of the two approaches.

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