Adaptive Graph Intelligence Layer
For institutions that want structural coherence to keep up with real-world change.
What we do
We represent your organisation as a dynamic graph:
- Nodes: people, teams, labs, projects, decision bodies, resources.
- Edges: dependencies, flows, approvals, shared responsibilities, constraints.
On top of this graph, we:
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Ingest historical and live data on workloads, delays, approvals, and interactions.
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Train graph-based models (GNN/GCN-style) to:
- learn how stress and risk propagate through your structure,
- rank nodes and edges by criticality and vulnerability,
- detect early signatures of overload, conflict, and structural strain.
How it connects to optimisation
The Adaptive Graph Intelligence Layer:
- Produces priority scores and risk indicators that feed directly into the portfolio and capacity optimisation models.
- Flags emerging hotspots before they show up as visible failures.
- Suggests high-leverage interventions (where a small change in assignment or policy would have outsized effect).
Instead of re-running every expensive optimisation model from scratch whenever something changes, you:
- Use the graph intelligence layer for fast re-ranking and monitoring.
- Trigger deeper OR and structural coherence analysis only when and where it is needed.
What you get
- A living organisational graph with updated node and edge metrics.
- Watchlists for critical people, labs, projects, and interfaces.
- Early-warning dashboards for overload, conflict, and emerging incoherence.
- Integration hooks to push these signals into your BI and decision-making tools.
Why it matters
Static models age quickly. When projects, staff, and constraints change, your old “optimal plan” can become irrelevant.
The Adaptive Graph Intelligence Layer keeps your view of pressure, risk, and priority aligned with current reality — without rebuilding everything from zero each time.
