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Learning Architecture Report — PL-004 Intelligence Platform

Generated: 2026-07-04
Authority: Source-verified implementation audit
Platform: zaixos-intelligence-platform (PL-004)

Executive Summary

PL-004 implements the Intelligence Brain of ZAIXOS. It consumes platform events, mines patterns, generates recommendations and optimization proposals, and requires human approval before any deployment. It never executes tools or replaces PL-003.

Learning Pipeline

Execution (PL-003 events)
  ↓ Trace (ai.trace.* via PL-006)
  ↓ Evaluation (ai.evaluation.*)
  ↓ Pattern Mining (PatternMiningEngine)
  ↓ Root Cause Analysis (RootCauseAnalysisService)
  ↓ Recommendation (RecommendationEngine → PendingApproval)
  ↓ Optimization Proposal (OptimizationEngine → requiresApproval)
  ↓ Human Approval (ApprovalOrchestrationService)
  ↓ Deployment (handoff only — requires_manual_deployment)
  ↓ Verification (SimulationEngine)
  ↓ Continuous Learning (IntelligenceLearningEngine)

Orchestrator: LearningPipelineOrchestrator
Façade: EnterpriseIntelligencePlatform via EnterpriseIntelligenceContract

Optimization Graph

flowchart TD
    OBS[ObservationIngestService] --> PM[PatternMiningEngine]
    PM --> RCA[RootCauseAnalysisService]
    PM --> RE[RecommendationEngine]
    PM --> OE[OptimizationEngine]
    OE --> APP[ApprovalOrchestrationService]
    APP --> SIM[SimulationEngine]
    SIM --> LE[IntelligenceLearningEngine]
    PSI[PlatformSnapshotIngestService] --> OBS

Recommendation Graph

Pattern	Recommendation Category
execution.failure.root_cause	Capability / recovery
evaluation.regression.*	Quality
capability.degradation.*	Capability evolution
prompt.degradation.*	Prompt learning
provider.degradation.*	Provider routing
tool.instability.*	Tool improvements
memory.degradation.tenant	Memory learning
knowledge.degradation.tenant	Knowledge evolution
anomaly.latency / anomaly.cost	Latency / cost optimization

Platform Integration (Event-Based)

Source	Ingest Path	Event Types
PL-003	PlatformSnapshotIngestService	ai.capability.snapshot, ai.memory.snapshot, ai.provider.metrics
PL-005	PlatformSnapshotIngestService	ai.knowledge.metrics
PL-006	ObservationIngestService	ai.trace.completed, ai.trace.failed, ai.evaluation.regression, ai.tool.execution

No Composer dependency on zaixos/ai-platform — snapshots consumed as generic arrays.

Ownership Matrix

Capability	Owner	PL-004 Implementation
Pattern mining	PL-004	PatternMiningEngine
Recommendations	PL-004	RecommendationEngine
Optimization proposals	PL-004	OptimizationEngine
Human approval	PL-004	ApprovalOrchestrationService
Simulation / replay	PL-004	SimulationEngine
Provider intelligence	PL-004	ProviderIntelligenceService
Capability evolution	PL-004	CapabilityEvolutionService
Knowledge evolution	PL-004	KnowledgeEvolutionReportService
Execution	PL-003	Not in PL-004
Observability traces	PL-006	Consumed via events

Remaining Gaps

Gap	Severity
Persistent stores (all in-memory)	High
Product composer wiring (PRD-000/001)	High
Real-time event bus from PL-006	Medium
Queue-based async pipeline	Medium
PL-005 direct knowledge API (uses events only)	Medium
Stub ZipPlatform methods (evaluate, reason, plan)	Low

Risks

1. In-memory data lost on process restart
2. Simulation uses heuristic improvement factor — not live A/B
3. Products must push snapshots/events — no pull API from PL-003 yet

Migration Plan

1. Phase A (complete) — Core learning pipeline + enterprise intelligence platform
2. Phase B — Add PL-004 to product composer.json with event bridge
3. Phase C — Persistent observation and proposal stores
4. Phase D — PL-006 webhook/stream ingest
5. Phase E — Consumer GA @ 1.0.0

Certification

Verdict: CONDITIONALLY CERTIFIED
Maturity: 68/100 — core intelligence loop implemented; persistence and product wiring pending