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QGIS AI Vectorizer
AI-powered raster-to-vector map digitization
QGIS plugin that uses neural networks to automatically trace lines and polygons from raster maps, providing AI-assisted autocomplete for faster digitization of scanned maps, engineering drawings, and geologic surveys.
$500K raised 🚀 Early Stage
Founded 2022 • 30+ government agencies (US, UK, Brazil, India, Australia); 4-person team; $440K ARR (as of 2025)
Why This Tool Exists
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The Problem
GIS professionals manually digitize raster maps and scanned documents by clicking each vertex, taking 2-3 hours per map. Geological surveys, utility plans, historical maps, and engineering drawings remain locked in paper format or PDFs, requiring extensive manual tracing.
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The Solution
AI Vectorizer learns what you're tracing and autocompletes lines and polygons in real-time. Users click twice along a feature, and the AI predicts and draws the complete line, reducing digitization time by ~50% while handling curved, dashed, and complex line styles.
How You Use It
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Delivery Method
Plugin
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Integrations
QGIS ArcGIS CAD (export)
Disciplines
Civil Engineering, Landscape Architecture, Facility Management, Owner/Developer
Project Phases
Pre-Design, Design Development
Project Types
Infrastructure, Institutional
Data Transparency
Exactly what this tool uses and how
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Input
What it needs
Required: Raster map or image (GeoTIFF, PNG, PDF, scanned document), QGIS vector layer (LineString, MultiLine, or Polygon)
Optional: User-drawn partial traces, Style reference data
Formats: PNG, JPG, GeoTIFF, PDF, Scanned raster images
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Output
What you get
Format: Vector features (lines or polygons)
Fields: Digitized line features, Polygon boundaries and fills, Geometry coordinates, Feature attributes (manual entry by user)
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Algorithm
How it works
Model: Proprietary neural network (architecture details not publicly disclosed)
Accuracy: Claims 4x faster digitization than manual tracing; accuracy not quantified but tool allows real-time user corrections
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Privacy
How your data is protected
Retention: Raster context around cursor sent to Bunting Labs servers during vectorization; Organizations plan users may request immediate deletion after processing; Personal/Professional tiers: data retained per privacy policy (specific retention period not specified)
Training: Not explicitly stated whether vectorization data used for AI model training; pricing page indicates 'Zero Data Retention' and 'no model training' for Professional tier, suggesting opt-in training for Personal tier
Compliance: GDPR (EU/EEA rights), CCPA (California consumer rights), CalOPPA (California online privacy), PCI-DSS (payment processing)
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API
Integration
Endpoint:
Contact vendor for API accessMethod: Plugin-based (REST API for third-party integration not publicly documented)
Use Cases
- • Digitizing historical topographic maps for GIS databases
- • Converting utility infrastructure maps (water, sewer, electrical) from paper to vector
- • Automating as-built engineering drawing digitization
- • Geological survey digitization (fault lines, soil boundaries, mineral deposits)
- • Cadastral map digitization for land records
Pricing
Free
Free trial (email signup, no credit card required)
Pro
Personal tier $20/seat/month (40 vectorization chunks/day, 10GB storage); Professional tier $99/seat/month (unlimited vectorization, zero data retention, no model training)
Enterprise
Organizations plan with custom pricing; on-premises deployment available
📚 Research Sources & Data Quality Last verified: 2026-02-01
Data Sources (10)
- 🔗 https://buntinglabs.com/solutions/ai-vectorizer-qgis-plugin
- 🔗 https://buntinglabs.com/pricing
- 🔗 https://buntinglabs.com/legal/privacy
- 🔗 https://buntinglabs.com/blog/introducing-ai-qgis-plugin-for-vectorization
- 🔗 https://buntinglabs.com/blog/ai-vectorizer-for-qgis-v2-launch
- 🔗 https://plugins.qgis.org/plugins/buntinglabs-qgis-plugin/
- 🔗 https://github.com/BuntingLabs/buntinglabs-qgis-plugin
- 🔗 https://crunchbase.com/organization/bunting-labs
- 🔗 https://getlatka.com/companies/buntinglabs.com
- 🔗 https://www.ycombinator.com/companies/bunting-labs
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Verified Data (18)
problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, maturityStage, customerBase, fundingTotal, vendor, website, pricing, control-features, useCases, input-output-specs, compliance
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Not Found (7)
algorithm-architecture-details, accuracy-quantified-metrics, soc2-certification, data-retention-period-specific, training-data-usage-explicit, webhook-support, third-party-api-documentation
Our Commitment: We only include verified data from official sources. If information isn't publicly available, we mark it as "Not publicly specified" rather than guessing.