Operational intelligence · Two independent reference implementations

Customer Operations Intelligence

Evidence-oriented AI systems for live customer-service decisions: one centered on state and asynchronous enrichment on AWS, the other on policy-gated commercial guidance and bounded explanation on Azure.

Models explain. Runtime state and policy retain authority.The two systems share an engineering discipline, not a claim of one deployed cross-cloud product.
MaturityImplemented reference systems
AWS focusState authority, lineage and post-call enrichment
Azure focusPolicy-gated commercial decision workflow
EvidenceSynthetic scenarios and bounded live component validation
Why it exists

Customer operations need more than a persuasive answer.

Live service decisions combine changing conversation state, commercial policy, protected facts, delivery constraints and asynchronous follow-up. ARMIE treats these as explicit system responsibilities. The model can help interpret or explain; it does not silently own eligibility, operational truth or lifecycle state.

Conversation state→Business policy→Grounded guidance→Bounded explanation→Validated outcome
Two implementation lanes

Same discipline, different engineering questions.

AWS · Customer Intelligence Platform

Which state is allowed to become truth?

A FastAPI reference slice separates transcript revision, versioned snapshots, protected facts, business outcome and delivery lifecycle. Stale asynchronous work cannot overwrite newer state.

  • Browser Workbench and canonical conversation state
  • Monotonic UI sequencing and permission rechecks
  • Post-call lineage, idempotency and delete tombstones
  • SQLite default plus opt-in PostgreSQL persistence contract
  • Docker / EC2 demo path with CloudWatch and SSM
Azure · Commercial Decision Agent

Which commercial action is policy-authorized?

A governed decision workflow combines customer context, deterministic eligibility, synthetic guidance retrieval, bounded narration, validation and human decision support.

  • ML predicts; deterministic policy authorizes
  • Retrieval grounds; the LLM explains
  • Validator and fallback protect the output boundary
  • Container Apps, Azure OpenAI, Speech, Language, Event Hubs and Redis validated in bounded paths
  • Workbench exposes decision evidence and fallback behavior
AWS evidence

Versioned state prevents stale work from becoming current truth.

36Preliminary synthetic Bedrock canary requests across accessible profiles
4Concurrent requests in the bounded canary
SQLiteDefault live demo persistence
PostgreSQLOpt-in adapter with real container contract tests

The PostgreSQL adapter demonstrates a persistence contract and transaction behavior. It does not establish RDS deployment, live migration, multi-instance safety or recovery of live calls.

Azure evidence

Policy remains deterministic while narration stays replaceable.

Commercial Decision Agent

Eligibility and action selection remain governed by explicit policy.

Bounded narrator

The model explains an authorized decision rather than inventing one.

Live component validation

Selected Azure paths were measured directly; the results are engineering evidence, not an SLA.

Honest retrieval boundary

Guidance lookup is a labeled local synthetic stand-in; Azure AI Search is not claimed as the live path.

Public evidence boundary

These are two independently built reference implementations using synthetic scenarios. The page does not claim customer deployment, production scale, contact-center integration, cross-cloud failover, commercial outcomes or one unified multi-cloud product.

Current engineering state

Implemented systems, with production questions still open.

The AWS system demonstrates governed live-conversation state and asynchronous enrichment. The Azure system demonstrates governed commercial decision support and bounded AI narration. Production data integration, security operations, tenancy, scale, recovery objectives and customer-specific policy remain future delivery concerns rather than current public claims.

Related system

See how the same authority-first discipline is applied to incident investigation.

Explore Operational Intelligence ↗