03 / Customer operations

Product Direction · In Development

SupportOS

Resolution Operations Platform

A support operating flow combining request classification, context retrieval, AI-assisted resolution, policy checks, SLA tracking, and human ownership.

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The operational problem

From fragmented work to a visible operating flow.

Customer requests arrive with uneven context, knowledge is scattered across wikis, SLA pressure grows, and generic chatbots produce ungrounded answers that violate company policy.

BEFORE

— Agents manually gather account history, agreements, and open tickets

— Policy enforcement varies depending on individual agent familiarity

— SLA timers run in separate tools with poor escalation visibility

— Escalations lose conversational context and force customers to repeat themselves

AFTER

+ Account context, active contracts, and prior tickets follow the request

+ Policy boundaries and confidence thresholds are evaluated deterministically

+ Low-confidence or sensitive tickets escalate immediately to specialist queues

+ Full evidence packages accompany every escalation for seamless handoff

System workflow

AI LayerDeterministic CodeHuman GateExternal / Outbox

One flow. Explicit boundaries.

STEP 01EXTERNAL

Request IngestionEmail / Ticket / API

STEP 02AI

Intent ClassificationCategory & urgency detection

STEP 03PERSISTENCE

Context RetrievalRAG over account & knowledge base

STEP 04AI

Draft ResolutionGrounded response proposal

STEP 05CODE

Policy & Safety GateDeterministic constraint check

STEP 06CODE

Confidence RoutingThreshold evaluation

STEP 07HUMAN

Human EscalationSpecialist review & ownership

STEP 08EXTERNAL

SLA & DispatchDurable notification & delivery

Unique signature · Resolution routing

Context retrieval, grounded drafting & SLA escalation.

01 / RETRIEVED CONTEXT GRAPHGrounded Knowledge & Contracts

Customer requests automatically pull account agreements, warranty terms, and prior ticket history. Drafts require direct citations to approved internal policy articles.

Active MSA + Account Tier + Approved KB

02 / CONFIDENCE & SLA ESCALATIONDeterministic Fallback Gate

Ambiguous requests or policy conflicts instantly trigger human escalation. The system attaches full context and provenance to prevent customer repetition.

CONFIDENCE < 0.85 → SPECIALIST QUEUE (SLA ACTIVE)

Architecture

The system around the intelligence.

LAYER / 01

Context & RAG Layer

Gathers account tier, active agreement terms, relevant knowledge base articles, and past ticket history before drafting.

Vector Search · Account Context Graph · RAG Pipeline

LAYER / 02

Resolution Layer

Proposes evidence-grounded answers with source citations and confidence metrics scoped to company knowledge.

LLM Reasoning Engine · Structured Output Schema

LAYER / 03

Policy & Constraint Layer

Deterministic rules enforce refund limits, legal disclaimers, escalation thresholds, and SLA priority rules.

Python Rule Engine · Policy Guardrails

LAYER / 04

Operations & Queue Layer

Maintains real-time SLA countdowns, routing queues, specialist assignments, and escalation traces.

Next.js Support Workspace · WebSocket / Event Bus

Reliability engineering

Failure is a state to design, not hide.

FAILURE MODE / 01Persisted Conversation State

Every draft, retrieved document chunk, and policy decision is permanently recorded in the ticket history.

FAILURE MODE / 02Traceable Knowledge Citations

Draft recommendations cite exact internal knowledge base article versions and agreement clauses.

FAILURE MODE / 03Safe Fallback Routing

Any query with ambiguity or confidence below 0.85 automatically defaults to human queues without customer disruption.

FAILURE MODE / 04Explicit SLA State

Escalation paths maintain uninterrupted SLA tracking regardless of agent handoffs or system transitions.

Human control

AI interprets. Code constrains. People authorize risk.

01AI Synthesizes Context

Language models summarize ticket context and prepare preliminary drafts based on authorized documentation.

02Policy Code Bounds Action

Deterministic software ensures refunds, contract amendments, or SLA breaches cannot be resolved without validation.

03Humans Own Sensitive Outcomes

Support specialists maintain full authority over complex customer disputes, billing adjustments, and edge cases.

04Context-Preserved Escalation

When escalated, specialists receive the entire evidence chain, retrieved knowledge, and prior attempts in one view.

Current limitations

What this page does not claim.

— This system is in product development; showcases demonstrate the architectural approach to intelligent support operations.

— No claim of active customer deployment is made without tenant verification.

— Knowledge integrations (Zendesk, Linear, Notion, Salesforce) require scoped workspace permissions.

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