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Mobile · iOS App

iOS App for field execution intelligence.

iOS App is positioned as a governed, field-to-office surface — not a standalone mobile feature. Cursor must confirm exact product positioning before publish.

Field reality

Three field pain themes iOS App helps address.

Field data delay

Information captured in the field arrives in the office hours or days later, after decisions have already moved on.

Missing context

Photos, notes, and entries arrive without the location, trade, or activity they relate to.

Rework risk

Disconnected field updates lead to work redone, double-entered, or invoiced without supporting evidence.

Operational signals

Signals the field surfaces to the office.

  • Capture without metadata
    Photos and notes without job, location, or activity attached.
    Reduces searchability for downstream legal, warranty, and turnover use.
  • Repeated late submissions
    Crews submitting daily activity after cutoff for three or more days in a row.
    Highlights a coaching or staffing pattern, not a single missed day.
  • Unread office responses
    Office comments and approvals not viewed by the originating field user.
    Indicates field workflow visibility gaps worth a session-level review.
  • Repeat captures of the same item
    Multiple field users capturing the same observation within the same shift.
    Suggests record-of-truth confusion to resolve at the project setup level.
Three-step loop

How iOS App captures, recommends, and finalizes.

1

Capture in context

Field user records the entry against a job, location, and activity.

2

Governed recommendation

Platform suggests where the entry belongs, who should review it, and what record to draft.

3

Reviewed action

A human reviewer approves, edits, or rejects — the action is logged with originator and approver.

Capabilities

iOS App capabilities

Contextual capture

Field entries are linked to job, location, trade, and activity at the point of capture.

Field-to-office sync

Entries are visible in the office workspace as soon as connectivity allows.

Role-aware routing

Reviewers and approvers are suggested based on role, trade, and project setup.

Auditable timeline

Each entry shows the originator, time, edits, approvals, and final state in one timeline.

What the AI does

Assistance, not automation.

AI assistance in this product is descriptive and recommendation-oriented. Final decisions stay with the field, office, or leadership reviewer.

Summarizes

Drafts a short summary of a daily or activity entry the user can edit.

Suggests

Suggests the most likely job, location, or recipient for a capture.

Flags

Flags entries missing context or that contradict an earlier entry.

Organizes

Groups related captures so the office sees one record, not five fragments.

Extracts

Extracts key fields from a photo, scan, or voice note for human confirmation.

Prepares

Prepares a draft record so review time is spent confirming, not retyping.

Outcome themes

Operational outcomes teams aim for.

These outcomes are illustrative and should be confirmed against active customer evidence before being used externally.

Faster field-to-office loop

Aims to shrink the gap between capture and office visibility from days to the same shift.

Cleaner operational evidence

Aims to raise the share of entries with full context attached at capture time.

Less back-and-forth

Aims to reduce reviewer follow-up needed to act on a field capture.

Who uses it

Roles touched by this surface.

Field teamsForemenSuperintendentsProject managersSafety leadsInspectorsOffice teamsExecutives
Related

Related mobile and lifecycle products

Cursor mounts related mobile/lifecycle products from aiProductsCatalog.js here.

Proof teaser

Evidence flow for this surface.

Field signal
Evidence source
Recommendation
Status
Capture without metadata
Mobile capture event log
Prompt the user to tag location and activity before submit.
Late submissions
Submission timestamps vs project cutoff
Suggest reminder cadence for the responsible foreman.
Unreviewed entries
Office reviewer activity log
Surface a review queue grouped by trade.
Duplicate captures
Same-day capture similarity
Merge prompt with originator attribution.
Governance & trust

Field intelligence under human control.

Mobile recommendations are advisory. People remain accountable for what gets submitted, approved, or sent to a customer.

AI proposes, people approve

Mobile recommendations are framed as suggestions. Field, office, and lead roles confirm before any record is committed.

Field and office in the same loop

Every field capture surfaces in the office workspace with the same context, timestamp, and originator visible to both sides.

Role-aware permissions

Foremen, superintendents, PMs, safety, and inspectors see only the workflows and records their role allows.

Audit trail by default

Capture, edit, approval, and submission events are logged so a record can be reconstructed without guesswork.

Tenant boundaries

Project, company, and tenant scopes are enforced; cross-tenant data is never blended in field views.

Explainable recommendations

Every suggested action shows the inputs it considered — photo, voice note, time entry, or related document.

Future readiness

Where this mobile surface is headed.

These directions describe roadmap intent — they are not commitments and must be confirmed by Cursor before publication.

Voice-first capture

Drafting entries from a voice note so field users keep their hands on the work.

Photo-assisted workflows

Suggesting record type and context from the content of a photo.

Offline-aware experience

Designing the capture flow so intermittent connectivity is the expected case.

Field-to-office intelligence

Routing captures to the right reviewer based on role and trade context.

Drawing intelligence

Tying field captures to the drawing sheet and revision they reference.

Governed recommendations

Recommendations stay advisory; people remain accountable for what is submitted.

See it on a live job

Walk a working iOS App loop with our team.

We mirror your current field workflows on a sample job and show the governed recommendations your team would see in the first week.