−30%
First-plan preparation time
Solutions for food manufacturing
Planning, production, quality, stock, procurement, logistics, commercial and finance all need different answers. Titan keeps the underlying definitions and context connected as the decision moves through the business.
A day with Titan
Swipe to follow the day
08:00
Plan the day
Bring orders, materials and capacity together in Titan.
10:30
Check the deviation
Titan Says flags excess giveaway. The production team checks the line.
16:00
Review the impact
Operations and finance review the material use and cost of the same order.
One day, multiple roles: each team works on its own decision while the underlying operational context stays connected.
Swipe to follow the day
Illustrative scenario with demo data.
Results achieved with Titan
Who it’s for
Role based insights on top of one governed model. Less discussion about numbers, more action.
Constraints, priorities, and plan stability in one view.
Performance, loss, and downtime drivers per line or plant.
Stock risk, ageing, and shortages before they hit the plan.
Customer performance and drivers, tied to the same numbers as ops.
Solutions
Each solution is a clear starting point, and they all connect to the same platform when you expand.
Improve OEE by pinpointing downtime, speed loss, and quality loss per line and shift using live factory data.
OEE snapshot
OEE
82%
Protect service levels with one overview of inbound and outbound flows, constraints, and delivery risk.
Today route status
Departures
149
On time
124
At risk
18
Reduce waste and free working capital with a real time view of stock, ageing, and expiry risk.
Expiry risk
One customer and channel view for margin, volume and service, aligned with finance.
Margin by channel
Connect production, waste and commercial data to margin so finance sees what drives profit.
Margin bridge
Current margin
€1.8M
Change
+€370k
Procurement cockpit for buyers with one view of suppliers, prices, contracts and risk.
Supplier score
Principles
Each solution is a focused cockpit. Titan standardizes your key definitions on an Azure Databricks foundation.
In practice: you get reusable building blocks, with numbers that stay stable as you scale.
Result
Shared tables and definitions across production, supply chain, finance, and commercial.
Start with one use case, then replicate the same patterns to other plants and teams.
Access control, quality checks, and encryption are built in, so trust grows over time.
When you add Ask Titan, answers are grounded in the same trusted model and sources.
Ask questions in MS Teams across factory, stock, finance, customers and suppliers. Without building new dashboards.
Expiry risk (next 7 days)
Based on current stock, FEFO rules, open orders and planned production.
Short, practical answers we often cover with operations, finance, and IT teams.
No. Most teams start with one solution that improves one decision first. When definitions are stable and value is proven, you expand to the next module.
Each solution is a module on top of the same Titan foundation. That means one data model approach, one definition layer, and a consistent way to scale across plants and teams.
Start where the decision pain is highest. Common starting points are stock risk, factory performance, service risk, or margin. If you share the decision, we can recommend the simplest first scope.
Often ERP plus one operational source that adds context, such as WMS, planning, MES, or quality. We start with the minimum data needed to answer the first decision reliably.
We centralize KPI definitions in the semantic layer, validate them with owners, and version changes. That reduces rework and keeps dashboards and AI answers aligned.
Yes. Ask Titan works on the same governed data and definitions, so users can ask questions in Microsoft Teams without creating new calculations or conflicting numbers.
With a focused scope and quick data access, a first usable output is often possible within weeks. The key is tight scope and fast validation of definitions.
In a short call we map your plants and systems, pick the best entry point, and outline a practical plan to go live.
No big program. Concrete use cases, clear ownership and short cycles.
Typical start