AI pre-construction for commercial GCs

From RFP to Proposal — AI That Does the Estimating Grind

Upload your spec book. Get WBS-classified scope packages, manage sub bids, and assemble your GC proposal — in hours, not weeks.

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Human-in-the-loop: your estimators approve every classification.

TeraContext.AI Review & Classify screen: a WBS tree of 5,998 spec and drawing sections, each classification shown with its code, source and confidence score

The pre-construction problem

What your estimating team faces on every bid

500–2,000+pages per spec book, across multiple volumes

50–500drawing sheets across 9+ disciplines

29trades of subcontractors, each needing the right scope

Addenda, contracts, geotech reports: hundreds more pages arriving throughout the bid period
Manual decomposition: reading every section, classifying by trade, building scope packages — by hand
Proposal assembly: pulling it all together into a coherent GC response under deadline pressure

The result? Weeks of manual work per bid. Missed sections that become change orders. Sub bids that don't cover the full scope. Proposals that leave money on the table — or leave scope uncovered.

How it works

One pipeline, from the RFP landing to the proposal shipping

01UploadSpecs, drawings, addenda, contracts
02ClassifyEvery section mapped to your WBS, with a confidence score
03ReviewEstimators confirm in bulk and fix the edge cases
04PackageTrade scope packages, auto-built by division
05BidInvite subs, analyze coverage and exclusions
06ProposeGC response with coverage matrix and gap analysis

What TeraContext.AI does

Built for the whole estimating workflow

Upload & Ingest

Drop in your spec PDFs, drawing sets, addenda, contracts, and geotech reports. The platform accepts PDF, DOCX, XLSX, PPTX, and images. Processing starts automatically.

AI Classification

A 7-phase AI pipeline extracts every spec section and classifies it against the industry-standard WBS format you bid against — 11 are supported, plus custom taxonomies. Each classification comes with a confidence score so your team knows exactly where to focus their review.

Human Review

Your estimators stay in control. Confirm high-confidence classifications in bulk, flag edge cases for discussion, and correct anything the AI got wrong. The AI does the heavy lifting; your team makes the final call.

Scope Package Generation

Bundle classified sections into trade-specific packages for subcontractor bidding. Auto-generate packages by division, then customize until the scope breakdown matches how you actually bid. Export each package as CSV, PDF, Word, or Markdown.

Drawing Analysis

A vision LLM analyzes every drawing page — extracting sheet metadata, general notes, keynotes, schedules, and material callouts. Cross-references between drawings and spec sections are mapped automatically.

Bid Management

Build your subcontractor directory across 29 standard construction trades. Invite subs to bid on specific scope packages. When bids come back, the AI analyzes each response for coverage, exclusions, alternates, qualifications, and risk flags — catching the buried exclusions that manual review misses.

Natural Language Query

Ask questions directly against your uploaded specs and drawings. Get AI-generated answers with source citations — spec section codes, drawing numbers, and page references.

Proposal Assembly

Assemble accepted sub bids into a complete GC proposal response with coverage matrix, gap analysis, per-trade narratives, and executive summary. Run a compliance check against the original RFP. Export as PDF or Word.

On a real bid set

A 10-document municipal library bid set, decomposed

Screens from a public municipal library and parking garage project: specs, drawings and addenda in; classified sections, trade packages and cited answers out.

Drawing index for the bid set: 246 sheets broken out by discipline — 54 architectural, 41 civil, 26 electrical, 55 structural and more — with every sheet's title, scale and page

Every drawing sheet, indexed by discipline

246 sheets read by the vision model and sorted into architectural, civil, electrical, fire protection, landscape, mechanical, plumbing and structural — with sheet numbers, titles, scales and 2,803 extracted text sections.

Scope packages screen listing 122 trade packages such as Access Doors, Air Barrier and Aluminum, each exportable to CSV, PDF, Word or Markdown

122 trade scope packages, ready to send

Classified sections roll up into trade packages you can rename, split and merge — then export for your subs in CSV, PDF, Word or Markdown.

Spec query answering 'What are the concrete strength requirements?' with values from structural sheets PS-001, S-101 and S-403 and spec sections 03 30 00, 31 23 00 and 05 50 00, citing 25 sources

Ask the spec book. Get a cited answer.

"What are the concrete strength requirements?" comes back with the values from the structural general notes, individual sheets and four spec sections — each with its sheet number or page range.

Built for commercial construction

11 industry-standard WBS formats — or your own

Works with open taxonomies such as UFGS, PennDOT-408, FERC Generation, DOE Nuclear and DOE Buildings, and customer-provided taxonomies such as the commercial spec division format, EPRI GN-COA and NAHB Residential — plus a custom taxonomy editor for firms with their own classification systems.

Commercial spec divisions
UFGS
PennDOT-408
FERC Generation
EPRI GN-COA
DOE Nuclear
DOE Buildings
NAHB Residential
+ Custom taxonomies

All major project types

Multi-Family, Office, Municipal, Parking, Retail, Hotel, Strip Mall, Mixed Use, and more.

A specialized AI pipeline

Seven phases — PDF extraction, table extraction, section splitting, embedding, WBS classification, graph building, cross-reference validation — purpose-built for construction documents, not adapted from a generic document tool.

Why TeraContext.AI