From Titan
Production, material & quality context
Detect manufacturing losses, risks and opportunities early
Titan Says monitors trusted manufacturing data in Titan, investigates meaningful changes, quantifies the business impact and brings the evidence to the team that can act.
What Titan Says does
Detect the change. Investigate the context. Surface the impact.
Detect meaningful changes, investigate the relevant context and surface the impact with evidence.
Detect a meaningful manufacturing change
Monitor signals such as yield, quality, throughput or stock and identify changes that move outside the expected manufacturing context.
Investigate the context and quantify the impact
Check approved context such as product, line, shift, batch or recipe and translate the result into kilos, hours, euros or service risk.
Surface the result with evidence
Bring the responsible team the affected scope, quantified impact and supporting evidence so they can judge whether action is worthwhile.
Workflow at a glance
Trusted manufacturing data in Titan
Governed production, material, quality, planning, machine and sensor context with shared business definitions.
Titan Says monitoring & investigation
Detect meaningful changes, investigate approved context and keep the business-impact logic explicit and reviewable.
Responsible team
Receive the result with context, impact and evidence in the channel where the team already works.
Manufacturing use cases
Start with one recurring manufacturing loss, risk or opportunity you can measure
The strongest use cases recur often enough to monitor, have enough context in Titan to investigate and have an impact the responsible team can validate.
Common starting points
Pick one problem that occurs often enough to be worth monitoring.
Yield loss
Example shown →Quality loss
Throughput loss
Stock risk
Illustrative Titan Says output
Yield loss requires review
Signal
Yield remains below the expected level across consecutive runs.
Evidence
Estimated material loss
€18k / week
Based on agreed material-loss logic.
Owner
Production
Next step
Review affected SKUs, lines and recent run conditions.
Illustrative example. Thresholds and impact logic are defined per use case with the responsible team.
From Titan Says
€18k estimated weekly material loss
Yield
93.3%
Scope
3 SKUs
Evidence
6 runs
Most of the loss is concentrated in 2 SKUs on Line 3
Both patterns started after the same recipe change. Review the affected runs before deciding on corrective action.
From signal to team
Bring the signal to the team where they already work
Titan Says delivers the signal with the affected scope, quantified impact and supporting evidence. From there, Ask Titan lets the team investigate products, runs, lines, batches or other underlying data from the same governed context.
Titan Says surfaces the signal
Show affected scope, quantified impact and the evidence behind it.
Ask Titan continues the investigation
Ask follow-up questions about products, runs, lines, batches or other underlying data.
Deliver the signal through
How AI is used
AI investigates. Business rules calculate. People decide.
Titan Says uses AI where flexibility helps:
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Investigate approved manufacturing context and find relevant patterns as new evidence appears.
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Keep thresholds, impact calculations and business rules explicit, governed and reviewable.
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Keep the evidence behind each surfaced risk or opportunity traceable so teams can review how the conclusion was reached.
The responsible team remains in control and decides whether and how to act.
Control model
AI investigation
Choose what context to investigate next
Explore approved manufacturing context such as product, line, shift, batch, recipe or quality as new evidence appears.
Governed business logic
Calculate impact with explicit rules
Thresholds, formulas and impact calculations use governed inputs and agreed business logic that can be reviewed and tested.
Human decision
The responsible team decides what to do
Titan Says provides the evidence and quantified impact. People remain responsible for prioritisation and action.
First use case
Start with one Titan Says use case worth validating
Bring one recurring manufacturing loss, risk or opportunity. In 30 minutes, we map the signal, the Titan data required, the impact logic and the evidence needed to determine whether it is a good fit.
30 minutes · No preparation needed · Start with one recurring manufacturing problem
A good first use case has
A measurable problem
A recurring loss, risk or opportunity with a clear owner.
Relevant Titan data
Enough governed context to investigate without guessing.
An explicit impact rule
A business rule the responsible team can validate.
Questions before you start with Titan Says?
Practical answers about what Titan Says monitors, how impact is calculated, where AI is used and how it works with Titan and Ask Titan.
What does Titan Says monitor?
Titan Says monitors trusted manufacturing data in Titan for changes related to a defined business problem. Depending on the use case, that can include production, material, quality, inventory, planning, machine, sensor or maintenance context.
How is Titan Says different from a normal alert?
A normal alert usually checks one predefined condition. Titan Says can investigate a meaningful change within a defined manufacturing use case, choose relevant follow-up checks, quantify the business impact and surface the result with supporting evidence.
How is business impact calculated?
Kilos, hours, euros or other business impact are calculated with explicit business logic on governed Titan data. AI can help decide what to investigate and explain, while the calculation itself remains testable and traceable.
How does Titan Says work with Ask Titan?
Titan Says identifies and packages a risk or opportunity with its affected scope, impact and evidence. Ask Titan lets a user continue from that same context with follow-up questions about products, SKUs, batches, sites, lines, orders or other underlying data.
Does Titan Says make business decisions automatically?
No. Titan Says brings evidence and quantified impact to the responsible team. People validate the context and decide whether an operational or commercial action makes sense.
Does Titan Says need real-time data or every source system connected?
No. Some use cases benefit from event data while others work well with scheduled updates. A first use case only needs the manufacturing data required to investigate that specific problem and support a measurable decision.