Why AI Teams Struggle With 3D Data
AI is only as good as the data you feed it—and 3D is the messiest, least structured data most organizations have.
Unstructured 3D & 2D assets
scattered across PLM, DAM, SharePoint, engineering folders
Manual prep work
to rotate, convert, defeature, or derive training images
Slow experimentation
Slow experimentation → higher costs + lower-quality model outputs
Inconsistent metadata
and no unified schema
Difficult AI integrations
with existing platforms
The result: slow experimentation, low-quality model outputs, and expensive AI development cycles
The 3D Data Layer Purpose-Built for AI
VNTANA automatically transforms messy engineering files into a clean, structured, metadata-rich 3D/2D training dataset—ready for ML, vision AI, simulation, and generative AI workflows.
- Structured database for 3D & 2D
- Automated cleanup and orientation
- Consistent metadata labeling
- APIs designed for training pipelines
- Automated image generation for vision models
- A complete task orchestration layer for 3D data
Train Better Models. Automate More Processes. Deploy AI Faster.
Build Faster
Build datasets 90% faster with automated file prep
Better performance
Improve model performance with standardized, clean inputs
Streamline
Accelerate AI feature releases by removing manual bottlenecks.
Smooth
Reduce experimental friction through consistent datasets
Easy Cooporation
Integrate seamlessly with AWS, Azure, GCP, NVIDIA, Hugging Face
For the Long Term
Establish a future-proof 3D foundation supporting CAD, USD, glTF, FBX, OBJ, USDZ, images, videos.
Everything AI teams need to create clean, consistent 3D training data at scale
Intelligent Optimization™
Automated cleanup for ML-ready 3D assets.
- Auto-rotate + scale normalization
- Standardizes naming, hierarchies, mesh structure
- Ensures optimal polycount/file size
- Generates all format derivatives needed for AI ingestion
ModelOps for 3D
Orchestrate, test, and evaluate AI workflows.
- Build custom workflows (e.g., CAD → Optimized → Renders → Bucket)
- Plug in generative or vision AI tools
- Run cloud-based evaluations
- Compare model outputs across standardized datasets
Automated Multi-Angle Image Generation
Synthetic training data from real 3D assets.
- Generate consistent renders for vision training
- Customize angles, lighting, and variants
- Deliver image sets for classification, segmentation, defect detection, etc.
Robust API + Webhooks
Pull exactly what your AI needs. Push updates anywhere.
- Retrieve 3D/2D files and metadata via API
- Trigger workflows on upload or approval
- Sync to cloud buckets or AI frameworks
Tags, Attributes & Metadata
A structured dataset for ML.
- Standardized taxonomy
- Part names, materials, variants, features
- Version history & lineage
- Perfect for labeling and supervised learning
Use Cases for AI & ML Teams
Vision AI Training
Object detection, segmentation, defect detection, assembly identification.
Synthetic Data Generation
Automated renders + metadata for model training.
Generative AI Workflows
3D → 2D variants, material swaps, product personalization.
Simulation & Digital Twins
Prepare simulation-accurate versions of 3D assets.
Robotics & Automation
Standardized inputs for path planning and testing.
AI-Powered Product Configuration
Feed clean 3D data into real-time personalization engines.
Why VNTANA
Patented real-time 3D Intelligent Optimization
Built specifically for 3D/2D AI workflows
Scales to millions of assets
Fast deployment
without ripping or replacing systems
API-first architecture
Enterprise-grade security & role-based access
Trusted by Innovators Across Industries
From industrial equipment to sporting goods, leading brands trust VNTANA to power frictionless 3D experiences.
Ready to Transform Your 3D Workflow?
Join brands like Kohler and Puma scaling 3D content faster than ever.