How Teams Use Pillarworks

Illustrative scenarios — see how teams like yours could apply AI-assisted BOQ automation to real estimating challenges.

These are representative workflow scenarios, not customer testimonials. Pillarworks was validated against real council DA plan sets — every quantity extraction carries a confidence score and page reference for professional review.

Illustrative Scenario
Time reclaimed on tenders

Mid-Size Commercial Contractor

The Challenge

Processing 50+ tender documents monthly with a team of 4 estimators. Manual data entry is causing bottlenecks and missed tender deadlines.

The Shift

AI extraction handles the ingestion layer — estimators spend their time on pricing, scope review, and winning work, not transcription.

How Pillarworks helps

Every uploaded plan set produces a structured, editable BOQ draft within the same session. Estimators adjust and sign off rather than starting from a blank sheet.

Illustrative Scenario
Fewer manual transcription errors

Specialist Quantity Surveying Practice

The Challenge

Consultants spending billable hours reformatting unstructured PDFs into ASMM-compliant line items before any real cost advice can begin.

The Shift

The AI ingestion and formatting layer is automated. Consultants receive a structured draft on upload — ready for professional review and rate application.

How Pillarworks helps

Every extracted quantity carries a confidence score and a reference back to the source plan page, so reviewers can verify exactly what the AI found and why.

Illustrative Scenario
Confidence scores — not black-box output

Quantity Surveyor Reviewing a DA Plan Set

The Challenge

A QS receiving architectural PDFs needs to produce a preliminary BOQ quickly, but cannot accept AI output without knowing which items need scrutiny.

The Shift

Pillarworks was validated against real council DA plan sets — extraction results include per-item confidence scores and page references so the professional knows exactly where to look.

How Pillarworks helps

Items below the confidence threshold are flagged automatically. The QS reviews flagged items first, then approves the remainder — human sign-off is built into the workflow, not bolted on.