ClusterOS Diagnostic Profile
London Climate Tech Net Zero
London Climate Tech Net Zero draws £4.27bn of UKRI lead-led funding across 14,017 grants, anchored by University College London (20%), Imperial College London (20%), with Connected Places Catapult on the industrial side.
The cluster shows high-confidence "Re-proving instead of narrowing" and "Forgiving instead of redesigning" behaviour — research narrative is reinforced by recurring programme launches rather than narrowing toward commercial scaling, with academic capacity reabsorbing the cluster's signal.
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Same data examined through five diagnostic lenses — Pipeline, Leverage, Triple Helix, Throughput, Collaboration. The interactive diagnostic is currently in private preview.
Sources: UKRI Gateway to Research (grants, outcomes); OpenAlex (publications); Companies House (spin-out lifecycle); DSIT (cluster mapping); Public investment data. Snapshot May 2026.
Stabilisation stacks · Why single interventions fail
Value extraction events generate narrative about ecosystem success; narrative legitimises continued extraction by framing it as ecosystem contribution; uncertainty about whether extraction is harmful absorbed by the success narrative.
"If one UKRI funder published annual data separating value retention (spin-offs headquartered in London, IP owned by London entities, follow-on capital to London non-anchors) from value generation (patents filed, spin-offs created, follow-on funding events), it might reduce the system's ability to absorb success and uncertainty signals without exposing whether extraction is occurring."
Leverage hypotheses are testable perturbations, not prescriptions. Where demand-side behaviour is weakly visible, the correct move is observation — improving visibility before attempting change.
Structural resemblances · Clusters with similar stall configurations
A full ClusterOS diagnostic adds actor questionnaire data, working sessions, and anchor interviews — producing higher-confidence stall identification, board-ready stack analysis, and leverage hypotheses calibrated to your specific context.