Plant and production leaders
See every line as it runs.
Capability
Smart Factory & Industry 4.0
Connect the plant floor to the data layer, then make it decide faster.
Overall equipment effectivenessUnplanned downtimeScrap and rework rateEnergy per unit produced
The service at a glance
The problem, our work, your result
- Business problem
Machines, lines and plants each speak their own language.
Production data stays inside equipment and spreadsheets, so downtime, waste and quality drift are discovered after the fact.
- What we do
We connect machines and lines into one data platform, then layer live monitoring, quality analytics and AI on top, step by step, without stopping production.
- What you receive
- Connected machine data platform
- Live production monitoring
- Quality and waste analytics
- A practical Industry 4.0 path
Who it is for
Built for the people who own the decision
Quality managers
Defects caught at the source.
CFO and finance
Less downtime, waste and scrap.
CDO, CIO and CTO
One industrial data foundation.
The goal: an AI-ready organisation
Where this service moves you
Data readyThis service
Connected, clean, governed and allowed for AI use.
KPIs ready
Agreed measures, one definition each, a named owner.
Organisation readyThis service
Roles, decision rights and skills to adopt AI safely.
=AI that reaches production and creates value
Approach
How we work with you
- 01
Connect
Link priority machines and lines.
- 02
See
Live dashboards for production.
- 03
Analyse
Find downtime and waste drivers.
- 04
Optimise
Add prediction and AI where it pays.
Engagement options
Start where you are
One line pilot
Connect and monitor a single line.
Plant platform
All lines on one data platform.
Multi-site programme
Standard platform across plants.
Scope
What is in, what is not
Included
- Industrial data platform
- Machine connectivity
- Monitoring and analytics
- AI use cases
Handled separately
- Machine procurement
- OT security hardware
Bilytica frameworks behind this service
Our own methods, not a generic playbook
DFF
All Bilytica frameworksData Foundation Framework
The layers that turn scattered systems into data an AI system is allowed to use.
See the frameworkDELIVERAI Delivery Framework
A gated path from idea to live service, with evidence at every step.
See the frameworkIn short
What this actually is
OT/IT integration, unified namespace, an industrial data platform and the analytics on top: OEE, throughput bottlenecks, energy per unit, quality genealogy and a digital twin of the line. Built on standard industrial protocols so it works with the machines you have, including the ones nobody wants to touch.
Key points
What matters before you buy
- 01
The blocker is connectivity, not modelling
Most plants can reach OEE and bottleneck analysis with clean machine data alone, before any AI.
- 02
One namespace ends the tag chaos
A consistent model of site, line, machine and signal is what lets a second plant onboard faster than a from-scratch build.
- 03
Safety and uptime constrain everything
Read-only from control systems first; anything that writes back passes the plant's change-control process.
- 04
Energy is now a first-class KPI
Energy and emissions per unit sit next to throughput, because both are now reported to buyers and regulators.
Delivery
How we build it
Foundation check
Before any buildWe inspect the systems, the data behind them and the quality of the records this capability will depend on, then write down what has to be fixed before anything is built.
Narrow first release
First releaseOne workflow, one team, real traffic, measured against the baseline we captured before we started.
Controls and evaluation
Runs in parallelGuardrails, approval gates, evaluation sets, logging and the evidence pack your auditor and your regulator will ask for.
Scale and hand over
After sign-offAdditional workflows, sites or languages, then runbooks and training so your team can operate it without us.
Data foundation
What has to be true in your data first
Great AI cannot hide bad data. These are the conditions this capability depends on, we fix them as part of delivery, not after go-live.
- Machine connectivity via OPC UA, MQTT or historian export.
- An asset hierarchy that matches the physical plant.
- Production orders and quality results tied to the same time base.
- A segmented OT network with an agreed data diode or DMZ pattern.
Controls
Guardrails we put around it
Every action is logged and replayable
Inputs, retrieved context, model version, output and the human decision are written to an immutable log, so an auditor can reconstruct any single interaction months later.
Data stays where your regulator requires
In-country, in-region or on-premise deployment, with the model portfolio right-sized to the workload instead of routing everything to a frontier endpoint abroad.
Accuracy is monitored, not assumed
A held-out evaluation set runs on every model or prompt change, with drift alerts and a documented rollback path when quality moves.
A human owns every consequential decision
Agents draft, route and execute reversible steps. Anything that moves money, changes a record of consequence or affects a person's rights stops at a named human approver with the reasoning attached.
Fit
Systems it plugs into, and what it moves
Integrations
OPC UAMQTT / SparkplugOSIsoft PI / AVEVASiemens MindSphereRockwell FactoryTalkSAP S/4HANAIgnition
KPIs it moves
- • Overall equipment effectiveness
- • Unplanned downtime
- • Scrap and rework rate
- • Energy per unit produced
- • Throughput against takt
By industry