Discrete manufacturers
Assemble products from parts and components: automotive, electrical, equipment and metal products.
Where we help
- OEE by line, machine and shift
- Standard versus actual cost
- Supplier delivery and quality
AI for manufacturing, end to end.
Every order. Every plant. Every margin. Connected.
From quote to cash, Data Semantics gives manufacturers one view of orders, plants, quality, supply chain and finance, and AI agents that act on it: processing orders, answering technicians, collecting cash and paying suppliers, inside the systems you run.
For discrete and process manufacturers, engineer-to-order and project manufacturers, and multi-plant manufacturing groups.
Ask your businessIllustrative
Why did gross margin fall at two of our plants this quarter?
ERPProcurementInventoryQualityCRM
Material prices rose with two key suppliers, slow-moving stock built up at one plant, and three large orders were quoted on last year's material costs.
−3.1pts gross margin▼ vs plan
44days of inventory▲ 6 days
12supplier price increases▲ this quarter
- Hold price increases from 2 suppliers pending contract checkAwaiting approval
- Rebalance slow-moving stock between plantsDrafted
- Update the quote cost model with current material pricesSent to sales
14+years
400+professionals
200+enterprises served
In short
Data Semantics provides analytics, automation and AI agents for discrete, process and project manufacturers. We connect quoting, orders, planning, production, quality, maintenance, supply chain, people and finance into one view, so plant, commercial and finance teams work from the same numbers. AI agents then enter customer orders into the ERP, answer technicians from manuals and past job cards, follow up receivables and process supplier invoices. Start with one problem, prove the value and scale from there.
The manufacturing value chain
Value is created across six stages. Most manufacturers see them one at a time.
Some manufacturers make to stock, some make to order, and some engineer to order for each project. The emphasis changes. The six stages are the same.
Quote & Order
Inquiries, quotes and contracts set the price, the margin and the delivery promise.
Plan
Demand, capacity, materials and schedules decide what runs where and when.
Source
Suppliers, lead times, prices and quality set material cost and risk.
Make
Lines, machines, people, yield, scrap and downtime turn materials into product.
Deliver
Inventory, warehouses and logistics decide whether orders arrive on time and in full.
Service & Collect
Invoices, milestones, warranty and service turn orders into cash and repeat business.
We connect all six into one model of your business, however you manufacture.
Who we serve
Built for the way you manufacture.
Process manufacturers
Make in batches or continuous flow: building materials, chemicals, plastics, packaging and metals.
Where we help
- Yield, losses and energy per tonne
- Batch quality and traceability
- Raw material price and stock exposure
Engineer-to-order & project manufacturers
Build to each customer's specification: fabrication, industrial systems, energy and infrastructure.
Where we help
- Estimated versus actual cost per project
- Milestone billing and project cash flow
- Procurement and subcontractor spend
Multi-plant manufacturing groups
Many plants, countries, ERPs and operating companies to bring together.
Where we help
- Group performance on one set of definitions
- Plant-to-plant benchmarking
- Consolidated procurement spend
What we do
See it clearly. Then let AI act on it.
We combine industry understanding with the technical know-how to build what you need, from analytics and automation to AI agents that act. These are the most common starting points, and the last card in each row covers everything else.
See itAnalytics and decision intelligence: one trusted view, and what to do next.
Plan · Source · DeliverAnalytics
Supply Chain Intelligence
Supply chain intelligence connects demand, plans, materials, suppliers, inventory and deliveries, so plants have what they need and customers get orders on time, without tying up working capital.
- Demand and S&OP within real capacity limits
- Material shortages and supplier lead-time risk
- Raw material, work-in-progress and finished stock
- On-time in-full (OTIF) delivery and logistics
Quote & OrderAnalytics
Commercial & Order Intelligence
Commercial & order intelligence connects inquiries, quotes, contracts, orders and actual costs, so sales can price with confidence and see which customers and products really make money.
- Quote-to-order conversion and win/loss
- Quoted versus actual margin by order and customer
- Order book, backlog and delivery-promise risk
- Product and customer profitability
Make · SourceAnalytics
Quality & Traceability Intelligence
Quality & traceability intelligence links inspections, defects, batches, supplier lots and customer complaints, so quality issues are found early and traced to their cause.
- Scrap, rework and first-pass yield
- Batch and lot genealogy from supplier to customer
- Supplier non-conformance trends
- Complaint and warranty root cause
Delivered withBusiness Intelligence & Analytics
Across the value chainAnalytics
People & Workforce Intelligence
People & workforce intelligence connects HR, payroll, time and attendance, and production data to show how skills, shifts, overtime and attrition affect output, safety and cost.
- Labor productivity and cost per unit by line and shift
- Overtime, absenteeism and attrition by site and role
- Skills coverage and shift planning
- Safety incidents and near-miss trends
Delivered withBusiness Intelligence & Analytics
Need something else analyzed or automated? Talk to an expert →
Act on itAutomation and AI agents that do the work, with people approving what matters.
OrderAutomation
Order Processing Automation
Order processing automation reads orders from customers and distributors, whether they arrive by email, PDF, portal or spreadsheet, checks them against price lists, credit and stock, and creates sales orders in your ERP.
- Orders captured from email, PDF, portals and spreadsheets
- Price, credit and stock checked before entry
- Sales orders created in SAP, Dynamics 365 or Oracle
- 90%+ less manual order entry
Delivered withZebo
MakeAutomation
Maintenance & Technical Knowledge
Maintenance and technical knowledge puts manuals, service bulletins and past job cards behind an AI assistant, and connects maintenance history to cost and downtime.
- Answers from manuals and bulletins, with the source cited
- Repeat-failure and maintenance history analysis
- Maintenance cost by asset, line and plant
- OEE and machine data connected where MES or SCADA data is available
Delivered withKnowledge Assistants
Service & CollectAutomation
Order-to-Cash & Collections Automation
Order-to-cash intelligence follows every order through invoicing, milestone billing, disputes and collections, so finance can bill faster and collect what's owed.
- Unbilled orders and missed milestones
- Customer credit limits and exposure
- Disputes matched to delivery and quality records
- Collections prioritized and followed up by AI agents
SourceAutomation
AP & Procurement Automation
AP & procurement automation uses AI to capture, match and post supplier invoices into your ERP, routing only the exceptions to people.
- PO and non-PO supplier invoice capture
- Matching against purchase orders and goods receipts
- Exception routing and approvals
- Posting into SAP, Dynamics 365, Oracle and more
Delivered withSerina
Talk to an expert
Which of these would make the biggest difference?
Tell us where your teams lose the most time today. We’ll show you what we would fix first, on the systems you already run.
Our differentiator
Semantics is in our name. What about your AI?
A manufacturing ontology is a shared model of your business: the products, bills of materials, orders, machines, batches, suppliers, shipments and people you deal with, how they relate and what each term means. People, analytics and AI agents all work from it.
From insight to action
A dashboard tells you what happened. We help you act on it.
Two examples of the same pattern: detect, understand, recommend, act, learn.
Rising scrap on a production line
For plant and quality leaders
- DetectScrap on one line rises from 2.6% to 4.2% in three weeks.
- UnderstandThe rise follows a material lot change from one supplier, and the main press is running longer between maintenance.
- RecommendHold the remaining lot, raise a supplier claim and bring forward preventive maintenance.
- ActOnce the plant manager approves, the hold, claim and maintenance work order are created in ERP, quality and maintenance systems.
- LearnScrap, OEE and supplier quality are tracked until the line is back on target.
A key order at risk of shipping late
For operations and commercial leaders
- DetectA major customer order is projected to miss its delivery date by six days.
- UnderstandAn agent traces it to a late component from one supplier and a capacity clash on the same line.
- RecommendExpedite the component from an approved alternative supplier and resequence two lower-priority orders.
- ActAfter approval, the purchase order and revised schedule are issued, and sales confirms the date with the customer.
- LearnSupplier lead-time performance and schedule changes feed the next planning cycle.
Illustrative examples. Every action runs within the approval rules you set.
Results
Measured in your numbers.
We don’t borrow results from other industries. Every manufacturing engagement starts by measuring today’s baseline, and success is proven against it. These are the measures we track most often.
- OEE
- Scrap rate
- On-time delivery
- Inventory days
- Cost per unit
- First-time fix rate
- Days sales outstanding
- Cost per invoice
Client work
Manufacturing work we've delivered.
An automotive manufacturer's service network
A knowledge assistant for service technicians
Repair manuals, service bulletins and past job cards answered in seconds, with the source cited, so workshops diagnose faster and get it right first time.
A diversified GCC industrial group
One view across operating companies
Brought data from several operating companies and ERPs into one governed model for group-wide performance and management reporting.
A global manufacturer's regional business
Automated supplier invoice processing
Automated capture, matching and posting of supplier invoices into the ERP, with exceptions routed to the right approvers.
Where to start
Three ways to start. Each one stands on its own.
Each is a fixed-scope engagement on your own data, measured against today’s baseline.
Analytics
Plant & margin view
OEE, scrap, late orders and margin by product and customer, in one governed view built on your ERP and plant data.
Business Intelligence & Analytics →AutomationSupplier invoices with Serina
Material, freight and service invoices captured, matched to orders and receipts, and posted to the ERP.
Serina →AutomationTechnician knowledge assistant
An assistant that answers technicians from manuals, bulletins and past job cards, with the source for every answer.
Knowledge Assistants →Every engagement follows the same path: measure today’s baseline, connect and model the data, prove it on a real workflow, then scale.
FAQ
Frequently asked questions
About manufacturing AI
Do you work with discrete, process and project manufacturers?
Yes. Discrete, process and engineer-to-order manufacturers share the same value chain but measure it differently, from OEE and batch yield to project cost and milestone billing. We model the way you manufacture, whether you run one plant or many.
Analytics
What is supply chain intelligence for manufacturing?
Supply chain intelligence connects demand, S&OP plans, capacity, materials, suppliers, inventory and deliveries. It shows where material shortages, excess stock or late orders are building up, and recommends actions such as expediting, re-sequencing or rebalancing stock.
What is quality and traceability intelligence?
Quality and traceability intelligence links inspections, defects, batches, supplier lots and customer complaints. It shows where scrap and rework come from, traces any batch from supplier to customer, and helps teams find root causes before issues reach customers.
Can you use machine and sensor data?
Yes. Where machine data is available through MES, historians, SCADA or IoT platforms, we bring it into the same model as ERP, quality and maintenance data. Where it isn't, we start with the data you already have, such as production confirmations and downtime logs, and add machine data later.
Automation and AI
Can AI enter customer orders into our ERP?
Yes. Zebo, the Data Semantics order-to-cash agent, reads customer and distributor orders from email, PDF, portals and spreadsheets, checks them against price lists, credit and stock, and creates sales orders in your ERP, cutting manual order entry by 90% or more.
What is maintenance and technical knowledge?
Maintenance and technical knowledge puts manuals, service bulletins and past job cards behind an AI assistant that answers technicians and engineers with the source cited, and connects maintenance history to cost and downtime. Where MES or SCADA data is available, OEE and machine data join the same model.
Are people still in control when AI agents act in manufacturing?
Yes. Agents monitor, explain and prepare actions such as a maintenance work order, a supplier claim or an invoice posting. Actions run within the approval rules you set, and every recommendation, approval and outcome is logged.
Data and platforms
Do we need to replace our ERP, MES or BI platform?
No. Data Semantics connects to the systems you already run, such as SAP, Microsoft Dynamics 365, Oracle and Salesforce, plus MES, quality, maintenance, warehouse and HR systems. Intelligence and agents sit across them, and approved actions are written back into them.
Which platforms do you build manufacturing analytics and AI on?
Data Semantics builds on Microsoft Fabric, Databricks or Snowflake for the data foundation, Power BI for analytics, Azure AI Foundry, Copilot Studio and the Microsoft Agent Framework with Azure OpenAI, Claude or open-weight models for AI agents, and Power Platform and Logic Apps for workflow and integration. Data Semantics is a Microsoft Solutions Partner for Data & AI and Digital & App Innovation.
Getting started
How do manufacturers start with AI?
Yes, and we recommend it. Common starting points are OEE and downtime, scrap and quality, late-order risk, quote margin, supplier invoice automation or collections. The data model built for the first use case is reused for the next.
Bring us the problem costing you most.
A line that keeps going down. Scrap you can't explain. Orders that ship late. Quotes that lose money. Start there.
