Visibility gap
Trade scope and schedule context lives in the GC system — subs reconcile from emails and shared drives.
Trade-specific scope, schedule, and cost signals stay on the same record the GC and owner see — recommendations proposed for review.
Governed · Explainable · Operational · Lifecycle-aware
Three operational pain themes that surface before software categories.
Trade scope and schedule context lives in the GC system — subs reconcile from emails and shared drives.
Sub commitments and field deliveries reconcile late, after the work front has already moved.
Late visibility forces reactive change orders, payment disputes, and closeout punch-list churn.
Each signal becomes operational visibility with a lifecycle-aware implication — not a metric in isolation.
Three steps — signal, recommendation, governed action. Humans approve.
A trade / sub contractor signal is detected on the operational record — drift, gap, or exposure becomes visible context.
AI proposes an explainable, reversible option — anchored to the evidence that produced it.
The right role reviews, approves, or rejects. The action stays on the operational record.
Capability intent — not a feature matrix. Operational, evidence-aware, lifecycle-aware, workflow-oriented.
Visibility is grounded at the trade / sub contractor work front — not in summary dashboards.
Recommendations link back to the workflow evidence that produced them.
Context travels upstream and downstream on the same operational record.
Signals enter approved review paths inside the trade / sub contractor workflow — not isolated tools.
Persona ownership shapes review paths and approval boundaries.
Outcomes are framed conservatively — no guaranteed ROI claims.
Sub PO, delivery, and pay-app evidence stay on the same operational record.
Trade scope, schedule, and cost signals reconcile to one record.
Punch-list, evidence, and overrides remain on the operational record.
Cursor mounts related lifecycle products from aiProductsCatalog.js inside this slot. Sandbox renders a static placeholder only.
Cursor verifies every trade / sub contractor signal before publish.
Examples illustrative. Cursor to confirm production behavior before publish.
Operational intelligence earns trust only when AI is explainable, reversible, and scoped to the operating boundary.
Recommendations are decision support — not auto-applied actions.
Every recommendation links back to the workflow evidence that produced it.
Approvals, overrides, and reversals stay on the operational record.
Decisions are anchored to evidence — not opaque model outputs.
Role-aware permissions govern what each user can see, propose, or approve.
Organizational data stays bounded within tenant and role scope.
The operational intelligence layer is shaped to support future capabilities responsibly.
Workflow context is structured for future semantic trade / sub contractor discovery — governed and reviewable.
Recommendations adapt as trade / sub contractor signals mature — bounded by approval boundaries.
Future capabilities extend the same operational record — no parallel system to reconcile.
Automation expands only inside reviewable, reversible, role-bound boundaries.
Decisions, approvals, and overrides remain on the operational record for future context.
Recommendations stay scoped to role, approval boundary, and operational evidence.
Forward-looking statements are illustrative of platform direction. Cursor to confirm before publish.
A consultative walkthrough — not a generic software demo.