Manufacturing
The data is centralised. The decisions are still made on partial information.
Manufacturers have invested in modern production, supply chain and quality platforms, expecting faster, more coordinated decisions. What hasn’t kept pace is turning that data into a decision at the moment it’s needed, on the shop floor, in planning, or in software your operation depends on.
What makes Panintelligence different
You built the infrastructure.
The gap moved somewhere else.
The problem: maintenance, planning and quality decisions run on data that is centralised but not coherent, so issues are found after they have already cost something.
The fix: one governed layer with self service dashboards delivered in the context of production, deployed in weeks.
The number: Denmaur moved Panintelligence from a finance reporting tool into a platform delivering real time insight across teams, saving over 432 hours a year in manual reporting effort.
Built for the people actually making this decision
Chief Operating Officer
What is keeping them up at night
Maintenance, planning and operations teams each run their own version of the truth, and reconciling them consumes real capacity.
How Panintelligence helps
A single governed layer so every team works from the same definition of the same metric.
Supply Chain Director
What is keeping them up at night
By the time a supply or demand plan is agreed, the conditions behind it have already shifted.
How Panintelligence helps
Real time, self service visibility into demand, inventory and supplier risk in one view.
Head of Product, industrial technology
What is keeping them up at night
Customers using your platform want governed reporting built in, and it keeps losing to roadmap priorities that ship revenue faster.
How Panintelligence helps
White label, embedded dashboards that ship as part of the product, not a separate engineering project.
Quality Director
What is keeping them up at night
Quality issues are often found during inspection or downstream, after rework and scrap have already been incurred.
How Panintelligence helps
Contextual, real time visibility across process, machine and material data, so issues surface during production, not after it.
You built the infrastructure.
The gap moved somewhere else.
Manufacturers have centralised production, supply chain and quality data into modern platforms, and the investment case was sound. What hasn’t kept pace is turning that data into a decision at the point it’s needed, rather than a report reviewed after the fact.
Maintenance decisions are made with partial context. Planning decisions are already out of date by the time they’re agreed. Quality issues are often identified after production has been affected, not during it.
This isn’t a data availability problem. It’s a translation problem, between what the systems hold and what an operator, a planner or a quality engineer needs in the moment a decision has to be made.
Where this shows up, across the operation
Ready to see it with your data?
A 14-day no-cost Proof of Concept connects to your actual data environment.
- The first dashboard is live on day one.
- No sample data.
- No hypotheticals.
- Real validation before you commit.
What changes with a single governed layer
Panintelligence sits across your existing MES, ERP and quality systems and builds one governed semantic layer on top, delivered in the context of production rather than as a separate reporting tool.
PiDashboard is self service, so a plant manager or a quality engineer can build and explore their own view without submitting a request to an analyst or a central BI team.
PiReport automates the recurring operational and supply chain reporting that currently consumes real planning capacity.
PiPredict brings explainable, human in the loop AI to early maintenance and quality signals, running on a bring your own LLM model so operational data never leaves your environment.
Built to sit inside the systems you already run
- MES and ERP platforms, and the quality and asset management systems that sit alongside them
- Data warehouses already in place: Snowflake, Databricks, BigQuery, Postgres and SQL Servee
- Single sign on and role based access control that inherits from your existing identity and permissions setup
- White label embedding into your own customer facing industrial or supply chain platform, with no separate login and no third party branding visible
Built for the standard regulated firms are actually held to
Data sovereignty
Zero data movement. Panintelligence queries your data in place, in your own infrastructure or in PiSaaS. Nothing is duplicated into a separate warehouse.
Explainable AI
Predicts runs on a bring your own LLM model, inside your own governance boundary. Every output is interrogatable, not a black box.
Auditability
Every figure in every dashboard and report traces back to source through the same governed semantic layer, with a full permissions and access audit trail.
Purpose-Built for Regulated Finance
Before Panintelligence, our reporting relied heavily on static PDFs and spreadsheets, often out of date by the time they were reviewed. The process was manual, time-consuming, and inconsistent
Matthew Groom, CFO, Denmaur
Skip the generic workarounds. Get fast, governed, embeddable analytics designed explicitly for the unique compliance, speed, and deployment standards that regulated firms are actually held to.
UK support
UK based implementation and support teams, in your timezone, with GDPR native data handling as standard rather than an add on.
What this looks like in practice
If you are running this inside your organisation
Predictive maintenance and asset performance
Challenge
Maintenance decisions are made with partial context, so intervention happens too early or too late.
How Panintelligence helps
Early indicators of performance degradation are surfaced in real time, in the context of production and load.
Outcome
Unplanned downtime is reduced and asset utilisation improves without increasing risk.
Supply chain and demand planning
Challenge
Demand, inventory and supplier data live in different systems, so plans are agreed on data that is already out of date.
How Panintelligence helps
A single, governed view of demand, inventory and supplier risk, updated in real time.
Outcome
Orders at risk of delay are identified earlier, and reactive, expedited logistics are reduced.
Embedded supply chain risk and performance analytics
Challenge
Customers using your platform want governed analytics on their own supply chain or asset data, and building it in house diverts engineering from the core roadmap.
How Panintelligence helps
White label, embedded dashboards ship as part of your platform, on the same governed data foundation as your internal reporting.
Outcome
Analytics becomes part of the product and the sales pitch, rather than a recurring support request.
If you are embedding this in your product
Embedded analytics for lending and wealth platforms
Challenge
Customers and intermediaries want better in app reporting, and building it in house means diverting engineering from the core roadmap.
How Panintelligence helps
White label, embedded dashboards ship as part of your platform, on the same governed data foundation as your internal reporting.
Outcome
Analytics becomes part of the product and the sales pitch, rather than a recurring support request.
White label reporting for insurance MGAs, brokers and claims platforms
Challenge
Insurers and brokers using your platform need their own governed reporting, but a generic export does not feel like part of your product.
How Panintelligence helps
Multi tenant, white label dashboards give each customer their own isolated view, carrying your brand rather than a third party analytics tool’s.
Outcome
Analytics stops being a recurring support request and becomes a reason customers renew.
One platform. Start where you need value most.
| Lever | Evidence | How it is calculated |
|---|---|---|
| Downtime and machine life | McKinsey found predictive maintenance typically reduces downtime by 30 to 50 percent and increases machine life by 20 to 40 percent | Industry benchmark, presented as sector context, not a guaranteed customer outcome. |
| Time saved | Denmaur released over 432 hours a year previously spent on manual reporting. | Hours saved multiplied by loaded hourly cost. Customer specific outcome, not a sector wide guarantee. |
| Time to value | Typical deployments go live in weeks, not the months a broader BI platform rollout usually takes. | Time from contract to first live, governed dashboard on your own data. |
| Commercial differentiation | Embedded supply chain and performance analytics becomes part of the product for industrial platforms, not a support cost. | Customer adoption of embedded reporting, and its role in retention and sales conversations. |
Questions worth asking before you buy anything
Why Panintelligence is different
Most analytics vendors are built for enterprises with large BI teams and long implementation timelines. Panintelligence is built for organisations that need analytics to work quickly, transparently, and without the overhead, whichever way they choose to deploy it.
