221 clusters diagnosed · 18 countries · 9 structural patterns
Diagnostic intelligence and coordination infrastructure for regional innovation ecosystems. We've diagnosed 221 clusters across 18 countries. The same 9 structural patterns appear everywhere — regardless of sector, geography or funding. ClusterOS names the pattern, finds the leverage, and gives your ecosystem the infrastructure to compound.
ClusterOS runs every ecosystem through a structured diagnostic pipeline — moving from raw external evidence to precise intervention points. The public pipeline observes from outside, without interviews or surveys. Commissioned diagnostics layer in actor questionnaires and steward working sessions for higher-confidence findings.
An interactive diagnostic journey. Select your stalls, see the reinforcing stacks, test leverage hypotheses, and configure a Digital OS architecture — all from self-assessment. The starting point, not the endpoint.
Observes from outside. Maps stalls the steward may not have named — or named incorrectly. The self-diagnostic and the commissioned diagnostic sometimes agree. Sometimes they don't. The difference is the point.
For ecosystems running the digital substrate, evidence is continuous. Every actor signal updates the diagnostic picture. The stall configuration is no longer a snapshot — it's a live read.
ClusterOS is what comes after it — the coordination infrastructure that makes the findings actionable, keeps the ecosystem legible in real time, and turns complexity from something you periodically summarise into something you continuously govern. The diagnostic tells you what your ecosystem is doing. The platform changes it.
See how the platform works →The platform serves different actors differently. Find your entry point.
Development agencies commission strategies. They produce roadmaps, priority sectors, and action plans. Then the cluster keeps doing what it was doing — because the structural blocker was never named. ClusterOS names it.
Model Context Protocol. Sovereign database per EDA. Actor journeys generated at runtime from live data. Intelligence at the protocol layer — not hardcoded into an interface. When the AI model improves, everything the platform produces improves automatically.
Regime type is the strongest structural predictor of company outcomes — stronger than sector or geography. Cycling ecosystems compound. Anchored ecosystems extract. The diagnostic tells you which one you're backing into.
Most consultants diagnose at the wrong layer. The stall is behavioural — but it looks structural from the outside. A diagnostic names the blocker in a way a strategy can't. That's a different kind of deliverable.
A procurement RFI, a research output, a hiring signal — in a connected substrate, each reaches founders, researchers and stewards with intelligence specific to what they need. Not broadcast. Coordination.
You're funding activity. That's not the same as funding outcomes. The question isn't whether your EDAs are active — it's whether activity is converting to structural change. Those require different measurements.
Findings · 75 diagnostics · 18 countries
We have run the ClusterOS diagnostic across 75 clusters — cyber security in Belfast, Tel Aviv, Cheltenham, Singapore; advanced manufacturing in the Basque Country; the Cambridge tech ecosystem; Orlando's ten innovation clusters and more. The finding that surprised us most is not what each ecosystem is doing wrong. It is how consistently they do the same things.
Three stalls appear in almost every ecosystem we have diagnosed, regardless of country, sector, or maturity stage:
Three patterns cut across everything — regardless of what a cluster makes, who funds it, or where it sits. Coordination is the default response to pressure, in every cluster we examined. The Narrative × Activity stack is the most resilient configuration we have found. And single-stall interventions almost always fail — because the stack compensates.
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How does the diagnostic identify stalls? Who built this and why?Framework · 5 stages · Evidence to leverage
A stall is not a failure. It is a behavioural substitution — the system doing something observable instead of something harder. Every behaviour that looks like dysfunction makes perfect sense from inside the actor's constraints. Stalls are sensible responses that became defaults.
When stalls reinforce each other — when one lowers the cost of another — they form a stack. Stacks are why your cluster works hard and goes nowhere. And why single interventions never seem to stick.
The diagnostic moves through five stages:
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What did 75 diagnostics find? How is it built? Show me the architectureArchitecture · MCP substrate · Sovereign data
ClusterOS is the coordination layer for a regional economy. Not a platform with AI features added. Not a dashboard. Not a CRM with analytics bolted on. An infrastructure layer — where every actor's selfish action generates typed signals that make the whole system more intelligent, without any actor needing to care about the ecosystem.
The backend exposes the ecosystem database as a defined set of named MCP tools. The AI calls those tools at runtime to assemble what each actor needs at each moment. Intelligence is not pre-baked — it is reasoned fresh from live data on every call. When the underlying model improves, everything the platform produces improves automatically.
One event — an anchor posting a procurement RFI — produces four completely different intelligence surfaces depending on who receives it:
| Actor | What the AI surfaces |
|---|---|
| Founder | "This RFI matches your declared capability profile. Application window: 14 days. Three preparation steps available in your journey." A specific, timely signal — not a general announcement they may never have seen. |
| Researcher | "This procurement signal aligns with your published work. Two founders in your cluster are potential commercial intermediaries." Academic work connected to live commercial demand without monitoring procurement feeds. |
| Steward | "Buy-side demand signal detected. Four founders have matching capability. Bridging score: 31/100. Possible Stall 4 (Anchor–Founder Disconnect)." A systems-level view, not an activity log. |
| Anchor | "A founder in your sector cluster has reached validation stage. Capability profile now accessible. No premature disclosure required." Relevant capability surfaced at the right moment. |
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Who built this? What's the background? Walk me through the diagnostic frameworkAbout · Edinburgh · 1995 → present
In a different domain. For a different kind of complex system. The intellectual move is the same: take a system whose behaviour is hard to see, build rigorous models to make that behaviour legible, and give the institutions that govern it something they can actually act on.
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Show me what 75 diagnostics found Request a diagnostic →Pattern matching · Structural resemblances
These clusters share your stall profile. Their diagnostic data is live — stalls, stacks, leverage hypotheses. See how the configuration plays out in different contexts.
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How does the diagnostic identify these patterns? What did all 75 diagnostics find?