Noetva

Ontology-driven decision intelligence

From fragmented enterprise data to explainable decisions

CTEC connects supplier, material, product, and facility records into one traceable ontology — so when a disruption hits, you can see exactly what's affected, why a recommendation was made, and approve or reject it with traceable evidence.

The journey

From fragmented data to explainable decisions

  1. Stage 1

    Import Data

    Source records are imported from sample datasets.

  2. Stage 2

    Map Schema

    Technical fields are mapped to business concepts.

  3. Stage 3

    Explore Ontology

    Connected relationships reveal business impact — which materials, products, facilities, and revenue are affected.

  4. Stage 4

    Decision Flow

    Explicit, deterministic rules evaluate the evidence.

  5. Stage 5

    Recommendation

    The recommendation is presented for human review.

A working example

Supplier risk, made explainable

When a key supplier is disrupted, CTEC traces the connected path from that supplier through the material it provides, the product that depends on it, and the facility where it's assembled — surfacing exactly how much revenue is exposed. If the affected material is single-sourced, CTEC evaluates whether a qualified alternate supplier has the capacity to absorb part of the demand, and proposes an allocation within that capacity. Every fact behind the recommendation — the disruption, the sourcing concentration, the alternate's readiness — is shown alongside it, and a person decides whether to approve or reject it.

What CTEC does

Major capabilities

Ontology construction

Technical records from separate systems are mapped into one connected, business-readable model.

Connected impact analysis

Relationships reveal which materials, products, facilities, and revenue are affected by an event — not just the event itself.

Explainable decision policies

Recommendations come from explicit, deterministic rules applied to evidence — not an opaque model.

Human approval

Every recommendation is proposed, never applied automatically. A person approves or rejects it.

Explainability and control

Deterministic rules, human decisions

CTEC does not use an opaque model to decide what happens next. Recommendation factors and rule conditions reference sample fixture filenames and row indexes. The recommendation is presented for human review — Approve or Reject records one reviewer decision in the current rendered demo session. No operational action is executed and no enterprise system is updated.

See it work on a real scenario

Walk through the full import-to-recommendation journey with a sample supplier disruption.

Explore Supplier Risk