MIZ OKI Media · Decision Graph overview
This remembers why.
The MIZ OKI Decision Graph — an operating model, not a storage model
Definition
A Decision Graph preserves the complete lifecycle of every business decision: evidence, context, reasoning, policy, approval, action, and realized outcome — connected, inspectable, replayable.
Evidence → Context → Decision → Outcome → (back to Evidence)
Where existing structures stop
| Structure | Does well | Where it stops |
|---|---|---|
| Data warehouse | Complete durable history of facts | No decisions, approvals, or predictions |
| Semantic layer | Consistent metric definitions | No causes, policies, or outcomes |
| Knowledge graph | Entities and relationships | No authority, veto, or predicted-vs-realized |
| Vector database | Fast semantic similarity | Similarity is not causality or governance |
| Agent memory | Context for one AI agent | Not an auditable organizational record |
| Decision Graph | The decisions themselves, end to end | Complements the others — it does not replace them |
Six load-bearing properties
| Temporal memory | What was known at the moment of deciding — the only honest basis for judging a decision later |
| Provenance | Every observation carries source, quality, and identity resolution |
| Causal relationships | Cause is an inspectable claim with supporting and disconfirming evidence attached |
| Approval history | The named authority behind every decision — vetoes preserved beside approvals |
| Replay | Any decision re-walked end to end, with the evidence as it stood |
| Continuous learning | Predicted vs. realized scored on every decision; the graph gets harder to fool |
Why it matters
Systems that remember facts help you report. A system that remembers decisions helps you govern — and compounds: every outcome sharpens the next decision.