In DevelopmentAutomation System

AI Cross-System Labor Engine

An AI operations layer that detects cross-system gaps and completes coordination work under approval controls.

Labor Engine command center dashboard with a setup banner and empty-state cards for critical issues, pending AI actions, customer risks, drift signals, and integration health. — Command center, empty state

What it solves

Companies do not fail because one system is missing; they fail because their systems do not agree. The CRM says one thing, the inbox another, the calendar changed, the invoice was never sent, the support ticket escalated, and the Slack message got buried. Humans are the glue holding these systems together, wasting time on manual coordination between them.

Built for Small and mid-market companies (roughly 20 to 500 people) already running several disconnected SaaS tools but lacking a large operations team; founders, COOs, and revenue/customer-success leaders.

Overview

The platform connects a company's business apps and normalizes their activity into a unified operational work graph. It detects cross-system inconsistencies, stalled work, missing owners, broken promises, and organizational drift, then explains each issue in plain English and recommends a resolution. Users approve actions manually or promote trusted low-risk workflows to autopilot; the system executes across connected systems, logs every action, and reports measurable ROI.

What this demonstrates

Implements a reusable multi-provider OAuth integration framework with token encryption and a common provider interface. Builds event ingestion and normalization into a work graph with fuzzy identity resolution, an inconsistency/drift detection engine, and an AI reasoning layer whose output is parsed into structured JSON and routed through risk-based approval before a safe, idempotent, audited execution layer.

What makes it different

Companies do not fail because one system is missing. They fail because the systems do not agree. This is the AI operations layer that keeps your company's systems aligned.

AI Chief of Staff, not a workflow builderRecommends automations from observed behavior instead of forcing manual configuration.
Human approval controlsHigh-risk actions require approval; trusted workflows can be promoted to autopilot.
Evidence on every edgeGraph edges include evidence; low-confidence matches stay reviewable.
AI never decides permissions or executes blindlyAI is barred from auth, billing authorization, and destructive actions without policy checks.
Explain every issuePlain-English explanations of why each issue was created; users can mark detections wrong.
Log everythingEvery meaningful action generates an audit log; sensitive tokens are masked.

Core capabilities · 14

Integration Framework
Reusable OAuth, token encryption, webhook, and sync architecture with a provider abstraction layer.
Event Ingestion & Normalization
Convert external activity into deduplicated, normalized WorkEvents with raw payloads stored.
Operational Work Graph
Connect people, customers, deals, tickets, invoices, tasks, and conversations with confidence scoring.
Inconsistency Detection Engine
Detect missing follow-ups, CRM mismatches, billing gaps, untracked promises, and stale deals.
Drift Detection Engine
Model baselines and flag unhealthy shifts in sales, support, billing, operations, and relationships.
AI Reasoning & Context Engine
Extract commitments, analyze sentiment, and recommend actions from structured context packets.
Recommended Action Engine
Turn issues into routed, risk-classified actions with previews, edits, and bulk approvals.
Execution Layer
Safely execute approved actions across systems with idempotency, retries, and logging.
Command Center Dashboard
Daily view of critical issues, pending approvals, customer risks, drift, and time saved.
Approval Inbox
Pending actions with evidence, editable previews, and approve, reject, snooze, or automate.
Admin, Governance & Security
Role-based permissions, approval policies, sensitive-data controls, and audit logs.
ROI & Analytics
Track issues detected, actions completed, follow-ups saved, and estimated hours saved.
Onboarding & Activation
Guided setup to connect apps, detect a first issue, and approve a first AI action.
Automation Rules
Promote trusted low-risk workflows to autopilot within approval policy.

How it works

Connect business apps
Build a unified work graph from all systems
Detect cross-system gaps and drift
Review the AI explanation and recommendation
Approve actions or promote them to autopilot
Execute across systems and log every action

Key screens

DashboardCommand center of risks, approvals, drift, and integration health.
IntegrationsProvider cards with connection status and health.
IssuesInbox of detected cross-system inconsistencies.
ApprovalsPending AI actions awaiting human decision.
ActionsRecommended and executed actions with results.
Work GraphSearchable customer, deal, ticket, and person view.
DriftTrend signals, baselines, and deviations.
AnalyticsROI and time-saved metrics.
SettingsRoles, policies, and governance.

Data model

Workspace
User
ConnectedApp
ExternalEntity
WorkEvent
WorkGraphNode
WorkGraphEdge
DetectedIssue
RecommendedAction
Approval
ExecutedAction
AutomationRule
AuditLog
RoiMetric

Screens · 4

Labor Engine getting-started checklist of four setup steps, a Connect Gmail prompt, and illustrative example issue cards like an unowned escalated ticket and a closed-won deal with no invoice. — Getting-started checklist

Labor Engine integrations page with six connector cards — Gmail, Google Calendar, Slack, HubSpot, QuickBooks, Zendesk — all marked not configured. — Integrations, none configured

Labor Engine ROI and analytics page with zeroed metric tiles for actions completed, time saved, and issues detected, plus editable per-action time-saved assumptions. — ROI and analytics

Labor Engine settings on the Policies tab for governance and automation, with toggles requiring approval before external messages and controlling autopilot risk levels. — Governance and automation policies

How it is built

A Next.js/React app backed by Prisma over PostgreSQL, with per-provider adapters, a sync runner for event ingestion, Auth.js for authentication, and an Anthropic-backed reasoning service. Connected-app tokens are encrypted at rest and every meaningful action writes an audit log.