State model
Append-only case events feed a current-state projection. Evidence rows keep source, observation time, validity, correction history and narrative usage.
Individual accounts can look ordinary while transaction timing, counterparties and device reuse reveal coordinated movement across a network.
A temporal graph engine proposes clusters, separates observed edges from inferred links, and ranks cases by evidential completeness and potential harm.
Organisations, systems and operating conditions are intentionally anonymised and recomposed. The design demonstrates engineering and banking-domain reasoning; it does not represent a named client estate, vendor product or measured production result.
A shared authority core coordinates independently owned capability cells, domain systems and operating evidence.
Permitted workModels may extract, compare and propose hypotheses. Deterministic policy gates and trained investigators own risk classification and disposition.
Consistency rulePin policy, list and evidence versions per case; retain contradiction and non-match evidence as well as supporting evidence.
Hard boundaryThe model is not a system of record, identity provider, policy authority or proof that an external effect occurred.
An alert or case requires evidence fan-out, deterministic triage, residual model reasoning and a defensible human disposition.
Cluster membership is an investigative lead, not an adverse decision; action requires independent policy evidence.
A deterministic outer workflow contains model-led work inside typed, observable calls. Dashed messages remain proposals until policy or a human grants authority.
Append-only case events feed a current-state projection. Evidence rows keep source, observation time, validity, correction history and narrative usage.
Use asynchronous ingestion and bounded parallel reads. Slow providers have independent timeout and circuit-breaker policy so one source cannot exhaust the case tier.
Pin policy and evidence versions at case open. Later corrections append and may trigger reassessment; they do not rewrite the historic basis silently.
These roles are deliberately vendor-neutral. Each can be independently owned, versioned and replaced.
Returns candidate entities and typed relationships with match features, contradictions, effective dates and non-merge evidence.
Chooses an approved model route by task, risk, evidence quality, latency budget and cost ceiling; enforces structured outputs.
Runs component, route, trajectory, failure, harm and outcome tests against the versioned system manifest.
Builds time-qualified projections from source events and reconciliations without becoming the legal system of record.
Appends request, versions, policy result, model proposal, approval, action receipt, readback, correction and custody events under one correlation key.
Evaluates identity, purpose, capability, amount, risk tier and policy version; returns allow, deny, step-up or human-review with reasons.
Durable records carry provenance, authority, effect and custody without turning a transcript into an uncontrolled memory store.
Pin policy, list and evidence versions per case; retain contradiction and non-match evidence as well as supporting evidence.
The selected design is not universally superior. It is the safer fit for this boundary and failure cost.
Bias consequential journeys against false merge and retain unresolved candidates.
Automatically merge the highest-scoring candidate.
Cost acceptedMore cases require clarification, but one person's authority or risk cannot silently attach to another.
Reserve larger models for residual reasoning after deterministic and smaller-model gates.
Send every request to the most capable available model.
Cost acceptedRouting adds evaluation work and operational complexity, but controls cost, latency and unnecessary data exposure.
Test prompts, models, tools, knowledge, policies, state transitions and human paths together.
Use a static answer-quality benchmark as the release gate.
Cost acceptedSystem evaluation takes longer and needs synthetic environments, but detects authority and recovery failures that answer scoring misses.
Use event-fed projections for scale and direct readback for consequential effects.
Fan out to all systems of record for every interaction.
Cost acceptedRead models introduce lag and reconciliation work, but reduce source load and make cross-system views feasible.
Use append-only events plus a rebuildable current-state projection.
Overwrite the case row with its latest status.
Cost acceptedReplay and storage are more complex, but point-in-time reconstruction and correction lineage remain possible.
Compile stable decision logic and retain retrieval for explanation and residual ambiguity.
Ask a model to interpret the source document for every request.
Cost acceptedRule compilation needs controlled change, but creates repeatable decisions, regression tests and clear exceptions.
Retries are bounded by knowledge of business effect; unknown outcome remains visible, owned and independently reconciled.
Actual thresholds belong to accountable service owners. The design exposes the equations and observables that those owners must baseline.
peak_enrichment_qps = peak_case_rate x sources_per_casereview_hours = residual_cases / investigator_throughputevidence_storage = cases x evidence_rows x retention_windowTokenise identity before model use, restrict sources by investigation purpose and retain only policy-required evidence.
A design is production-ready only when teams can prove what happened, recover it and change it safely.
false-merge and false-split test
source outage and incomplete-case test
blind sample of deterministic closes
investigator override drift review
Edge provenance, temporal windows, alternative explanations, feature contributions, case linkage and reviewer action.
Investigators decide case linkage, customer impact and external reporting.
Use shadow decisions and blind samples before allowing deterministic closes. Keep agent-touched cases under human disposition until operating evidence supports narrower review.
Investigation, policy, data, model-risk and operations owners retain decision and control accountability.