How TeraContext.AI Works
The Complete Pre-Construction Pipeline — From RFP Upload to GC Proposal
TeraContext.AI takes your construction specification PDFs and drawing sets, automatically extracts and classifies their contents against industry-standard WBS taxonomies, and provides a complete workflow for generating subcontractor scope packages, managing bids, and assembling GC proposal responses.
1. Upload Your Documents
The first step is uploading your project documents. Drag and drop your files — the platform handles the rest.
Supported document types:
- Specification — your main spec book (this is what gets classified)
- Drawing — architectural, structural, MEP drawing sets
- Addendum — revisions to the original RFP
- Contract, Geotechnical, Bid Form, Other — supporting documents
Supported file formats: PDF, DOCX, XLSX, PPTX, Markdown, HTML, CSV, images (PNG, JPG, TIFF), and more.
Upload spec volumes as Specification type and drawing sets as Drawing type — this controls which AI pipeline runs on each document. Large spec books (1,000+ pages) may take 10-20 minutes to fully process. You can upload additional documents at any time, even while others are processing.
2. AI Processing Pipeline
Each document moves through a 7-phase AI pipeline automatically after upload:
| Phase | What Happens |
|---|---|
| 1. PDF Extraction | Text is extracted from every page |
| 2. Table Extraction | Tables are identified and converted to structured data |
| 3. Section Splitting | Spec sections are identified by format (e.g., “SECTION 03 30 00”). For drawings, title blocks and text content are extracted |
| 4. Embedding | Each section is converted to searchable vectors for AI retrieval |
| 5. WBS Classification | AI classifies each section against the project’s WBS taxonomy |
| 6. Graph Building | Cross-reference relationships are mapped |
| 7. Cross-Ref Validation | Classifications are validated for consistency |
Real-time progress tracking shows the status of each phase for every document.
3. Review & Classify
Once the AI has classified your spec sections, your team reviews the results. Each classification shows the assigned WBS code, confidence score, and classification method. Bulk operations let you confirm high-confidence classifications instantly — typically 70-80% of sections — while your estimators focus their time on edge cases and low-confidence items.
The AI does the heavy lifting. Your team makes the final call before scope packages are built.
4. WBS Taxonomy Standards
TeraContext.AI ships with 10 industry-standard WBS taxonomies:
| Taxonomy | Use Case |
|---|---|
| masterformat | Construction industry standard (default) — 546 codes |
| UFGS | Unified Facilities Guide Specifications (DoD projects) |
| UniFormat II | Elemental classification (cost estimating) |
| OmniClass | Broad construction classification |
| Uniclass 2015 | UK/international standard |
| FERC Generation | Utility/power generation |
| EPRI GN-COA | Power industry cost accounts |
| DOE Nuclear | Department of Energy nuclear projects |
| DOE Buildings | DOE building construction |
| NAHB Residential | Residential construction |
Custom taxonomies: Clone any standard taxonomy and customize it — add, rename, delete, or reorganize codes to match your firm’s classification system.
5. Scope Packages
Once classifications are approved, the platform bundles spec sections into trade-specific packages for subcontractor bidding. Auto-generate one package per division as a starting point, then customize — move sections between packages, rename, split, or merge until the scope breakdown matches how you actually bid.
Export each package as CSV, PDF, Word, or Markdown — ready to send to your subs.
6. Drawing Analysis
When you upload drawing sets, a vision LLM analyzes every page — extracting sheet numbers, titles, disciplines, general notes, keynotes, schedules, legends, and material callouts. Cross-references between drawings and spec sections are mapped automatically, both by explicit reference and by discipline.
All extracted text becomes searchable alongside your specifications.
7. Bid Management
Build your subcontractor directory across 29 standard construction trades. Invite subs to bid on specific scope packages, record their responses, and compare bids side-by-side.
For deeper analysis, upload a sub’s bid response document. The AI evaluates it for scope coverage, exclusions, alternates, qualifications, and risk flags — catching the buried exclusions that manual review misses.
8. Proposal Assembly
Assemble accepted sub bids into a complete GC proposal response. The platform generates a coverage matrix, gap analysis, per-trade narratives, and executive summary. Run a compliance check against the original RFP before submission. Export as PDF or Word for final editing.
Technology Under the Hood
TeraContext.AI uses specialized AI techniques designed for the scale and complexity of construction documents:
- Retrieval-Augmented Generation (RAG) — Semantic search optimized for masterformat structure, creating searchable vector indexes of your entire document collection
- GraphRAG — Knowledge graphs that capture relationships between specs, drawings, standards, and codes
- Multi-Layer Summarization — Hierarchical document understanding from division-level overviews down to individual spec sections
- Vision LLM — Multimodal AI that reads drawing pages, extracting title blocks, general notes, keynotes, and annotations directly from the sheet images
Supported Project Types
Multi-Family, Office, Municipal, Parking, Retail, Hotel, Strip Mall, Mixed Use, and Other.
Early Access
TeraContext.AI is currently available through our Early Access program. Contact us to see the platform in action with your own spec book.
| Contact Us | View Use Cases |