01
Discover
A new epic, agent version, changed tool, policy update, or service record creates or updates a Change Record.
SignalAzure DevOps epic changed
03
How it works
Follow one change from first signal to business outcome.
ChangeFlow operates as a continuous loop. Each stage adds context and evidence while keeping the authoritative record in its source system.
Discover→Impact→Ready→Release→Observe↻
The unified lifecycle
Eight stages. One traceable thread.
The output of each stage becomes structured input to the next, while scope changes can invalidate affected analysis or evidence.
Shared objectChange
Recordscope · owner · outcome
Recordscope · owner · outcome
01Discoversignal
02Understandcontext
03Impactrelationships
04Assessdelivery
05Validateevidence
06Decideauthority
07Observeoutcomes
08Learnimprove
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Context grows Human control points Feedback returns
02
Understand
The platform identifies what changed, why, who owns it, which release contains it, and what outcome it supports.
ContextAutonomous refund action
03
Analyze impact
Explicit relationships, approved documents, rules, and graph propagation identify affected processes, roles, systems, and controls.
ImpactStore manager affected
04
Assess delivery
Transparent signals expose schedule variance, scope churn, blocked dependencies, missing ownership, and readiness misalignment.
RiskAPI dependency unresolved
05
Validate
Technical, agent, security, operational, people, and measurement evidence is gathered and reviewed independently.
EvidenceEscalation test accepted
06
Decide + release
Policy calculates the recommendation. Named humans approve, reject, or grant a scoped and expiring exception.
DecisionConditional go
07
Observe
Adoption, successful outcomes, escalation, corrections, incidents, cost, and business measures are connected to the release.
Observation82% assisted resolution
08
Learn
Predicted impact is compared with reality. Reviewed lessons improve mappings, rules, policies, and later analysis.
LessonSupport ownership predicted incidents
The method
Four reasoning modes work together.
No single model or data source is trusted to infer enterprise impact alone.
Explicit relationships
Imported from authoritative systems and confirmed maps.
Semantic proposals
Extracted from approved documents with source and confidence.
Deterministic rules
Customer policy turns conditions into required review and work.
Bounded propagation
Typed graph paths extend impact without uncontrolled inference.
Evidence-first intelligence
A recommendation is only useful if people can challenge it.
Material claims keep their reasoning structure, instead of disappearing into generated prose.
Claim→Source→Method→Status→Review
Example claim
“Store managers are affected because they perform the refund approval process modified by Release 2.3.”
Start with one real release