State model
A partitioned event log feeds time-windowed operational state. Per-entity sequence and watermark prevent late or duplicate events from appearing current.
A uniform speed target encourages teams to remove checks from high-consequence journeys or over-engineer low-risk interactions.
The controller allocates a latency budget by risk class, runs safe checks concurrently, caches only version-qualified artefacts and degrades to a narrower certified route when dependencies slow.
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 workThe assurance layer observes and evaluates; it may trigger a stop or review but cannot redefine business policy from telemetry alone.
Consistency ruleCarry one correlation chain across synchronous and asynchronous hops and separate event occurrence from observation and processing time.
Hard boundaryThe model is not a system of record, identity provider, policy authority or proof that an external effect occurred.
Events or conversation turns require a decision before the underlying situation changes, with strict latency and back-pressure constraints.
No latency target may bypass authority, freshness, eligibility or effect verification; degradation always reduces capability rather than control strength.
A deterministic outer workflow contains model-led work inside typed, observable calls. Dashed messages remain proposals until policy or a human grants authority.
A partitioned event log feeds time-windowed operational state. Per-entity sequence and watermark prevent late or duplicate events from appearing current.
Use streaming ingestion for signals, low-latency feature or state reads for the hot path, and asynchronous enrichment outside the decision budget.
Point-in-time correctness takes precedence over the newest unqualified value. Late events trigger correction or review instead of mutating the old decision invisibly.
These roles are deliberately vendor-neutral. Each can be independently owned, versioned and replaced.
Accepts a typed evidence request and returns the minimum permitted facts with source, event time, observation time, validity and exclusions.
Evaluates identity, purpose, capability, amount, risk tier and policy version; returns allow, deny, step-up or human-review with reasons.
Chooses an approved model route by task, risk, evidence quality, latency budget and cost ceiling; enforces structured outputs.
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.
Durable records carry provenance, authority, effect and custody without turning a transcript into an uncontrolled memory store.
Carry one correlation chain across synchronous and asynchronous hops and separate event occurrence from observation and processing time.
The selected design is not universally superior. It is the safer fit for this boundary and failure cost.
Prefetch stable, purpose-safe facts; acquire volatile facts on demand against a time-qualified snapshot.
Load a broad customer profile at session start.
Cost acceptedThe selected design adds source calls and latency, but reduces stale data, excess exposure and accidental reuse.
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.
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.
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.
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.
partition_rate = peak_events_per_second / active_partitionsdecision_budget = ingest + state_read + policy + score + action_commitbacklog_clear_time = queued_events / recovery_throughputCollect the minimum diagnostic metadata, tokenise subjects and keep raw prompts or case evidence behind stricter access and retention.
A design is production-ready only when teams can prove what happened, recover it and change it safely.
trace and outcome completeness
control-bypass and false-negative review
cost and human-effort attribution
kill-switch and recovery exercise
Route class, latency budget, dependency timings, cache keys, checks completed, degradation decision, outcome and service-level breach.
Service and risk owners set route-specific budgets and approve degradation policy.
Start with advisory intervention and measured shadow scoring. Increase automation only when peak-load, late-event and fallback tests preserve the control outcome.
Service, control, finance, model, data and operations owners interpret evidence and decide intervention.