Start small. Prove the operating model. Scale with evidence.
EcoKure begins with one consequential workflow, not an organisation-wide transformation. Each stage produces an artefact and a decision about whether to continue.
Generate a buyer-ready pilot brief.
Choose the conversation you are ready to have. EcoKure will show the workflow boundary, deployment environment, expected outcome and evidence path. Nothing here claims certification or commits a customer to production.
Start the conversation with measured AWS proof.
117,290 verifications · 0 performance errors · 19.47 ms p95 · 128.1 verifications/sec soak.
Eight stages, with a decision at every boundary.
Choose one workflow
Named start/end points, owner and out-of-scope systems.
Readiness evaluation
Baseline the current process, evidence and review burden.
Map the Control Pack
Versioned obligations, controls, evidence and reviewer roles.
Run in shadow mode
Observe and classify without controlling production.
Test a change event
Measure impact when rules, data or source evidence changes.
Review the EvidencePack
Inspect signed records, replay results, gaps and limitations.
Go / no-go decision
Proceed, extend, revise or stop against pre-agreed criteria.
Customer-boundary deployment
Only after validation, security and operating ownership are accepted.
What the enterprise receives.
| Stage | Artefact | Decision owner |
|---|---|---|
| Readiness | Workflow brief, baseline and risk boundary | Business / risk owner |
| Control mapping | Versioned Control Pack and evidence request list | Control owner |
| Shadow pilot | Decision stream, exceptions and review workload | Operations owner |
| Change event | Impact map, replay set and preserved set | Technical / scientific owner |
| Completion | EvidencePack, limitations and go/no-go record | Steering group |
Which workflow should we evaluate?
Life-sciences evidence change control is the first worked path. The same operating model can be configured for APRA, EU AI Act and other enterprise controls.
Start the conversation