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Value creation levers

Industrial AI applications across the value chain.

Below are our growing number of value creation levers that can be deployed. They can be extended to client-specific value creation problems.

Value creation levers by function

  1. 01

    Sales & Tendering

    • Specification Deviation ManagementLess manual reading and correcting of customer specifications.
    • Offer CreationMargins estimated from comparable history and product data.
    • After-Sales RFQ-to-QuoteData gaps resolved before the quote manager steps in.
    • Live Pricing ExecutionQuote guidance and concession floors that protect margin.
    • Installed Base MonetisationService renewals and cross-sell prioritised.
    • Account IntelligenceCRM, installed base, quote and service signals in one brief.
  2. 02

    Engineering

    • Design Data OptimisationManufacturing- and supplier-ready design data: shorter lead time, accurate data, less searching.
    • Design-to-CostCost drivers and over-specification made visible.
    • Part Reuse & StandardisationExisting parts found before new ones are created.
    • Engineering Change ImpactCost and supply impact assessed before release.
  3. 03

    Procurement & Sourcing

    • Spend & Should-Cost OptimisationPrice outliers against physical cost drivers.
    • RFQ-Ready Sourcing PackagesBundled by part family, with supplier scouting.
    • Make-or-Buy DecisionsPart by part, refreshed as costs move.
    • Supplier Contract ReviewLess manual reading, correcting and commenting in contract management.
  4. 04

    Manufacturing & Maintenance

    • Digital Value StreamLosses in equipment, inventory, lead time and productivity quantified.
    • Lot-Size & Changeover OptimisationCapacity released without new equipment.
    • Maintenance IntelligenceFaster fault resolution, higher machine availability.
    • Spare-Parts OptimisationCritical spares on hand, less capital tied up.
  5. 05

    Finance & Cash

    • Working Capital IntelligenceTrapped cash mapped across AR, AP and inventory; drift flagged early.
    • Safety-Stock ResetERP parameters reset against actual demand, tracked to cash.
    • Early-Payment InterceptionNon-compliant supplier payments stopped before they leave SAP.
  6. 06

    HR & Organisation

    • Application IntakeCompleteness checks and routing to HR.
    • Interview & Onboarding CoordinationScheduling and onboarding tasks across systems.
    • HR Service RoutingEmployee requests routed to the right owner.
    • Central Functions & Spans of ControlWhere administration can be simplified.
    • Personnel decisions stay with people.

How success is measured

The test is the business outcome.

The test is not whether an AI output sounds intelligent. The test is whether the workflow produces the business outcome it was designed to deliver. That is why the client defines what good looks like before deployment. Example measures include:

Pricing

Live Pricing Execution

  • Contribution margin
  • Quotation win rate
  • Discount leakage
  • Below-floor approvals
Inventory

Inventory Policy Execution

  • Realised cash
  • Service stability
  • Stock-out risk
Procurement

Direct Material Cost Optimiser

  • Implemented savings
  • Qualification success
  • Supplier quality
  • Resilience of supply
Industries

Industrials · Manufacturing · Automotive · Pharmaceutical manufacturing · Consumer goods · Private-equity-backed industrial businesses

Frequently asked questions

Questions and answers

Do the applications run on our data?

Yes. Client deployments use the client’s data in an environment the client controls. The reference results published on kriyanta.ai were demonstrated on reference datasets.

Which systems do the applications work with?

With your existing systems: ERP (e.g. SAP, Oracle), MES, PLM, CRM, files such as Excel and CSV, and APIs or IoT sources. Connection is through standard APIs or, where available, your existing MCP gateway. Your systems remain the system of record.

Ready-to-deploy application or custom build?

Both. Ready-to-deploy applications package reusable industrial transformation logic and are configured to your data, systems and operating environment. Fully customised applications are purpose-built around your specific operational challenge.

Who makes the decisions: the AI or people?

Consequential actions require explicit human approval. Every action is classified: automatic within policy, approval-required or not permitted. Personnel decisions remain with authorised HR professionals.