Data collection cases Apparel and textiles
Apparel workflow capture across skilled manual tasks
Public task evidence covering sewing, garment handling, edge work, and other fine manual operations.
Selected evidence
9 public evidence clips
Industrial Data Services
Industrial data built for models that operate in the real world.
PandectAI defines, collects, reviews, structures, and delivers physical-world data across operating environments that cannot be reproduced by web scraping alone.
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Data collection cases
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Data collection cases Electronics manufacturing
Electronics assembly workflow capture
Task-level video evidence across fine assembly, fitting, soldering, testing, and handling operations in electronics production.
Selected evidence
21 public evidence clips
Production domains
Data collection across specific industrial operations.
We can scope and coordinate data capture for the following production operations. Modalities, volume, locations, rights, and quality criteria are defined for each project.
Apparel & home textiles
- Seaming
- Pocket making
- Sleeve-cap positioning
- Collar attachment
- Cutting
- Heat sealing
- Button attaching
- Buttonhole making
- Pressing
- Packing
Leisure products
- Rattan weaving
- Spray painting
- Part unloading
- Full-line operations
- Packaging
Toy manufacturing
- Closing back-of-head seams
- Center-seam sewing
- Full-body stitching
- Turning face coverings
- Label attachment
Food & bakery
- Kneading
- Proofing
- Shaping
- Baking
- Piping and decorating
- Tempering
- Latte art
- Plating
Electronics manufacturing
- SMT placement
- Soldering
- Injection molding
- Assembly
- Testing
- Burn-in
- Packaging
Chemicals & pharmaceuticals
- Premixing and stirring
- Ultrafine milling
- Emulsifying and blending
- Filling and sealing
- Spray drying
- Blister packaging
Paper & packaging
- Slitting
- Laminating
- Die cutting
- Carton stitching
- Bag making
- Corona treatment
- Color printing and lamination
Footwear & light textiles
- Cutting
- Stitching
- Sole bonding
- Forming
- Quality inspection
- Packaging
Data designed across four dimensions.
01
Environment
Factories and machinery
Logistics and retail
Commercial workflows
Homes and everyday contexts
02
Capture
Ego and multi-view video
Hand motion and EMG
Object and equipment state
Synchronized sensor context
03
Structure
Task and action taxonomies
Object and tool labels
Reason-of-operation annotations
Rights and privacy documentation
04
Delivery
Model-ready files
Metadata and QA notes
Evaluation scenes
Iteration and recapture paths
From model requirement to governed delivery.
Define
Specify the target environment, task, modality, volume, labels, quality, rights, and delivery format.
Collect
Coordinate real-world capture with suitable locations, operators, devices, and operating procedures.
Review and structure
Screen rights and privacy, align signals, classify tasks, document context, and run QA.
Deliver and iterate
Package files, metadata, documentation, and a clear path for additional collection or evaluation.
For AI Labs
Proprietary physical data for Physical AI teams.
Turn model requirements into rights-reviewed demonstrations, operating scenes, edge cases, and evaluation contexts that are difficult to source from the open web.
01
Human demonstration sequences with task context
02
Multi-view scenes for embodied model training
03
Edge-case libraries from operating environments
04
Evaluation scenes for perception and planning
05
Object, tool, and workflow interaction data
06
Custom collection programs linked to research milestones