Pricing, margin, installed base
Test pricing assumptions against comparable historical projects; capture service and cross-sell potential in the installed base.
AI Value Diagnostic
Where AI moves EBITDA and cash in your business.
The AI Value Diagnostic is Kriyanta’s entry point for industrial companies. It starts with one CEO question: where does the organisation lose time, margin, revenue or cash, and which intervention would create the greatest value?
3 to 4 weeksDiagnostic sprint: interviews, process data and financial signals become a full value map
1 to 2 weeksTo first validated value levers
1 roadmapQuantified, prioritised and business-owned
Typical value pools
Where we start in industrial businesses.
The diagnostic examines the entire value chain and links every finding to an application that can address it. The goal is to identify ways to improve EBITDA and release cash.
Complexity, design-to-cost
Separate justified engineering from accumulated specification complexity.
Spend, should-cost, sourcing
Identify price outliers against physical performance drivers and settle make-or-buy part by part.
Capacity, OEE, lot sizes
Quantify losses along the value stream; raise machine availability and maintenance performance.
Inventory, receivables, payables
Map trapped cash, intercept early payments and reset safety stocks.
Central functions, spans of control
Automate administrative HR workflows while keeping personnel decisions with people.
Frequently asked questions
Questions and answers
How long does the AI Value Diagnostic take?
The diagnostic sprint takes 3 to 4 weeks. First validated value levers are typically available after 1 to 2 weeks.
What data do you need?
Interviews, process data and financial signals from your existing systems, such as purchase order, inventory, quotation and payment data from the ERP. Connectors are read-only by default and scoped to agreed systems.
Do we have to start with a full diagnostic?
No. An engagement can also begin with a defined value opportunity or a single application and then expand across additional functions and value levers.
Does every opportunity become an AI project?
No. The sequence is deliberate: eliminate unnecessary work, simplify what remains, automate what is deterministic, then apply AI where reasoning creates value. Where the bottleneck is governance, decision rights or process discipline, we say so.
What happens after the diagnostic?
Prioritised use cases are built, embedded into operations and measured against the agreed baseline. Each application has a designated owner, human approval points and a clear deployment sequence. We deploy one of our applications or build a custom one.