Demo listing. This page uses illustrative seed metadata to demonstrate the Atlas. Claims shown here are not verified product facts.
Planvector
Construction drawings intelligence
Turns construction sheet PDFs into versioned, confidence-scored geometry and annotations ready for estimating take-off.
Last verified 15 Sept 2026 · Updated 23 Sept 2026 · Metadata v5
Problem
Estimators still chat with multi-hundred-page PDF sets or trust opaque AI take-off guesses without sheet and revision control.
Outcome
Take-off-ready, revision-pinned sheet data with confidence scores and a human acceptance gate before export.
Who uses it
- Operations Analyst
- Quality Engineer
- Solution Architect
Key capabilities
Drawing-set ingest
IncludedRegister sheets with revision identity and supersede conflicts.
Domain:
drawing-setsGeometry vectorization
AI-assistedIncludedExtract measurable elements with confidence scores.
Human acceptance gate
IncludedAccept or reject AI geometry before take-off export.
Take-off-ready export
IncludedStructured payloads for Quantspan and estimating tools.
Domain:
exports
Typical workflow
Sheet intelligence to take-off export
Trigger: A drawing set PDF package is uploaded for a bid or project
Automated
Stage 1: Ingest and normalize sheets
System
AI-assisted
Stage 2: Vectorize geometry
System
Human checkpoint
Stage 3: Accept high-confidence elements
Estimator
Task
Stage 4: Resolve revision conflicts
Document controller
Automated
Stage 5: Export take-off payload
System
Task Automated AI-assisted Human checkpoint Decision
About this foundation
Planvector is the sheet-intelligence layer between raw drawing PDFs and estimating. It ingests drawing sets, normalizes sheets and revisions, vectorizes measurable geometry, attaches confidence scores, and exports structured payloads. Human acceptance gates block opaque model guesses. Quantspan prices from the export; Contextkeep owns knowledge chat; Planvector does not author CAD or priced bids.
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Sheet intelligence to take-off export
Trigger: A drawing set PDF package is uploaded for a bid or project
Automated
Stage 1: Ingest and normalize sheets
System
AI-assisted
Stage 2: Vectorize geometry
System
Human checkpoint
Stage 3: Accept high-confidence elements
Estimator
Task
Stage 4: Resolve revision conflicts
Document controller
Automated
Stage 5: Export take-off payload
System
Actors
Estimator, Document controller
Outputs
- Take-off-ready geometry package
Evidence generated
- Acceptance and revision trail
Exceptions
- Superseded sheets flag open elements
Task Automated AI-assisted Human checkpoint Decision
Included ships in the foundation · Configurable is switched or tuned per customer · Extension is customer-specific build scope · Planned is on the roadmap and not available today.
Drawing-set ingest
IncludedRegister sheets with revision identity and supersede conflicts.
Domain:
drawing-setsGeometry vectorization
AI-assistedIncludedExtract measurable elements with confidence scores.
Human acceptance gate
IncludedAccept or reject AI geometry before take-off export.
Take-off-ready export
IncludedStructured payloads for Quantspan and estimating tools.
Domain:
exportsCAD authoring
PlannedNative drawing authoring.
- Architecture class
- Domain-driven design, OpenAPI-first
- Bounded contexts
- 5
- API-first
- Yes — OpenAPI contracts are authoritative
- Identity
- Enterprise OIDC / SAML via the fazeZERO identity blueprint; tenant-aware role-based access.
- Multi-tenancy
- Tenant-aware
- Service boundaries
- 5 bounded contexts behind one API server.
- Integration approach
- Ports-and-adapters: every external system sits behind an adapter; OpenAPI contracts for inbound APIs.
- Eventing
- Integration events via transactional outbox.
- Storage abstraction
- Repository interfaces; DynamoDB or relational adapters.
- Deployment pattern
- Containerized API + web application; infrastructure as code per cloud profile.
- Architecture version
- 1.0
Approved domain names
- drawing-sets
- sheets
- geometry
- exports
- identity
- Web Application
- API Server
- Application Services
- Domain / Generated Core
- Adapters
- Customer Systems
Generator source, templates and factory orchestration are proprietary and are not part of this listing.
Reference Adapter: shipped and tested · Previously Integrated: delivered before · Standard API Pattern: integrates via a documented pattern · Customer-Specific: built in your implementation.
Document Management
| Integration | Status | Direction | Method |
|---|---|---|---|
| CDE / drawing repository | Standard API Pattern | inbound | REST API |
Data
| Integration | Status | Direction | Method |
|---|---|---|---|
| Estimating tools | Standard API Pattern | outbound | REST API |
Deployment
- Deployment models
- Private Cloud, Customer Cloud
- Cloud profiles
- Azure Profile, AWS Profile
- Containerized
- Yes
- Regions
- GLOBAL, UAE, SAUDI ARABIA
Cloud profiles describe approved deployment patterns. They are not formal marketplace certifications.
Data handling
- Stores customer data
- Yes
- Data leaves customer environment
- Configurable
- Uses external AI provider
- Configurable
- Sends logs externally
- No
- PII expected
- No
- Data-residency support
- Yes
- Subprocessors required
- Determined during customer configuration
Identity & access
- Authentication
- OIDC, Entra ID, SAML
- Authorization
- Role-Based, Tenant-Aware
- Source availability
- Proprietary
Support
- Implementation
- Delivered by fazeZERO or a certified partner during the Solution Definition and AI Production Sprints.
- Production support
- Production support available under a separate support agreement.
- Contact
- support@fazezero.com
Badges
fazeZERO Verified
Listing metadata and published technical claims have been reviewed by fazeZERO.
Issued 23 Sept 2026
Evidence shows that this listing represents real engineering. Internal metrics are only published when fazeZERO has approved them for publication.
Build
Automated tests
Deployment validation
- Last verification
- 15 Sept 2026
- Release
- 1.0.0
- Architecture version
- 1.0
- Listing metadata version
- 5
- Last published
- 23 Sept 2026