Industrial & Aviation
AI that recovers revenue and keeps the line running
Contract pricing unlocked, downtime cut, forecasts sharpened and paperwork automated. Built for industrial, manufacturing and aviation operators on the systems you already run.
Free diagnostic, three minutes. No follow-up unless you ask.
What AI for manufacturing means
AI for manufacturing means using machine learning and generative AI on the data a plant, a supply chain or an aviation operation already produces: sensor readings, orders, contracts, invoices and sales history. The aim is practical. Keep the line running, put contract pricing where negotiators can use it, forecast demand well enough to hold less stock, and take manual keying out of order entry.
Industrial and aviation operators ask us for results they can see in the P&L. Predictive maintenance on existing sensor data cut unplanned downtime by 65 per cent at a UK industrial manufacturer that had been losing £4m a year to it. A generative AI pipeline reads emailed PDF orders and posts them into SAP, automating half of one manufacturer's orders end to end. A machine-learning model cut a medical-device supplier's sales-forecast error by about 31 per cent and extended its forecasting horizon to 18 months.
In aviation the problem is often contracts. We used AI to extract contract pricing into a queryable database for a global aviation operator, giving it clear visibility to support pricing negotiations.
Not every operational problem needs AI. Some need a cleaner data feed, a better report or a rule a spreadsheet can run. The AiRE Diagnostic exists to make that call before you spend on a build: it returns a short list of AI bets ranked by value, feasibility and risk across your plants, depots or fleet, and an honest read on whether to roll out, build, buy or wait.
Built around the operator's P&L
The four places industrial and aviation businesses ask us to start, each drawn from work we have already delivered.
Contract and pricing intelligence
Generative AI that reads scattered contracts and puts the pricing where negotiators can use it. For a global aviation operator we extracted contract pricing into a queryable database, giving it clear visibility to support pricing negotiations.
Predictive maintenance and operations
Predictive maintenance on the sensor data you already collect, with operations dashboards plant managers actually use. One heavy industrial manufacturer, losing £4m a year to unplanned downtime, cut downtime by 65 per cent.
Demand forecasting and inventory
Seasonality-aware machine-learning forecasts that optimise stock across markets. A medical-device supplier cut absolute sales-forecast error by 31 per cent and extended its forecasting horizon to 18 months.
Document and order automation
Generative-AI pipelines that read scattered contracts and emailed orders and put the numbers where teams can use them. One European manufacturer now automates half its customer orders end to end, from inbox to ERP.
What we have built for industrial and aviation operators
Specific engagements, specific results. Anonymised by agreement where the client asked for it.
Predictive maintenance and ops dashboards for a UK industrial manufacturer
UK industrial manufacturer (£800m turnover)
A heavy industrial manufacturer was losing £4m a year to unplanned downtime. We deployed predictive maintenance models on their existing sensor data and built operations dashboards their plant managers actually use.
Automating order entry from inbox to ERP
A private-equity-backed European manufacturer of engineered wood products
A private-equity-backed European manufacturer of engineered wood products relied on a dedicated team to interpret and rekey emailed PDF orders into SAP by hand. QuantSpark built a generative AI pipeline that automates half of customer orders end to end.
Building an AI-powered pricing database for a global aviation operator
A global travel logistics operator
QuantSpark used AI to extract pricing terms buried in scattered contracts and built a queryable pricing database, giving commercial teams clear visibility across customers and stations to support negotiations.
Predictive churn model helps a plastics manufacturer prioritise sales engagement
A multinational plastics packaging manufacturer
A multinational plastics packaging manufacturer needed to anticipate customer churn so its sales team could act before mid-tier accounts drifted away. A bespoke, explainable churn model gave sales a real-time view of which customers were most at risk.
Machine learning improves a medical-device supplier's sales forecasting
A private-equity-backed orthopaedics and medical-device supplier
A seasonality-based machine-learning model cut sales-forecast error by around a third and extended forecasting to 18 months, optimising stock across international markets.
How we work with operators
We are an AI consultancy of around 70 strategists, data scientists and engineers, building AI and analytics systems since 2016. Our industrial work follows three rules.
Start with the data you already collect
We start with the sensors, ERP records and documents you already hold, and prove value on them before anyone buys new hardware. The downtime result above came from sensor data the manufacturer was already capturing.
Build for the people who use it
A model that sits unopened changes nothing. We build operations dashboards plant managers use, and explainable models sales teams trust: a productionised churn model gave a plastics packaging manufacturer's sales team a real-time view of at-risk mid-tier customers.
Automate the documents
Orders, contracts and invoices arrive as email and PDF. Generative AI reads them, extracts the fields that matter and puts them into the systems of record. That is how one manufacturer now automates half its customer orders from inbox to ERP, and how an aviation operator turned scattered contracts into a pricing database.
Proof, not promises
Less unplanned downtime for a UK industrial manufacturer, from predictive maintenance on its existing sensor data
Figures are drawn from completed QuantSpark engagements. Clients are anonymised by agreement; on a call we will walk you through how each number was measured and, where the client has agreed, put you in touch with a reference.
One ladder, each step earned
Every engagement starts small and earns the next step. Book a discovery call and we will tell you where to start, honestly.
Readiness Diagnostic
Free. Ten questions, a scored readiness band and an honest diagnosis. No follow-up unless you ask.
- Scored readiness band
- Plain-English diagnosis
- Recommended next step
AiRE Diagnostic
A short list of AI bets ranked by value, feasibility and risk, a recommended roadmap, and an honest read: roll out, build, buy, or wait.
- Ranked AI bets
- Value and feasibility scoring
- Recommended roadmap
- Honest build / buy / wait call
First Agent
A production-candidate agent, live on your own stack in five weeks, built with your team so you leave owning both the agent and the ability to build the next one.
- One core workflow mapped (week 1)
- One production-candidate agent on your stack
- Your people building alongside us
- Runbook, eval harness, code and IP, all yours
AiRE Rollout
Fractional AI implementation across your existing stack. From AI experiments to AI operations.
- Tool deployment on your stack
- Team enablement
- Governance and guardrails
- Monthly reviews and Slack support
Labs Discovery
A working prototype on your data, in your workflow. Not a slide deck. Validated value and a scale roadmap.
- Process and data mapping
- Working prototype
- Validated value case
- Scale roadmap
Labs Build
An enterprise-grade system embedded in your operating model. You own the code and the IP.
- Production build
- Integration and embedding
- Team handover
- 12 months support
Every project is scoped individually. Book a discovery call and we will provide a detailed proposal within 48 hours.
Manufacturing and aviation AI questions, answered
How is AI used in manufacturing?
Can predictive maintenance reduce unplanned downtime?
Can generative AI automate order entry into our ERP?
Can AI make sense of aviation contracts?
How much can machine learning improve a demand forecast?
How do we start?
Talk to an AI consultancy for manufacturing, industrial and aviation that has done this before.
Start with the honest read
Three minutes, ten questions, no follow-up unless you ask. Or talk to a human first.