Robotics & Industrial AI Data Annotation

Robotics & Industrial

Perception data for machines that operate in the real world

Synnth annotates the 3D, visual, and sensor data behind robotic perception and industrial automation — object detection, pose estimation, and multi-sensor fusion for systems that have to get it right on the factory floor.

Overview

Industrial robotics and automation systems depend on perception models trained for tightly defined, high-stakes environments — bin picking, quality inspection, warehouse navigation, human-robot collaboration. Synnth builds and annotates the sensor datasets these systems need, from 3D point clouds to multi-camera pose data, matched to your specific hardware and operating environment.

What we do

Data collection & annotation across every AI modality

From sourcing raw data to delivering production-ready labeled datasets — Synnth covers the full pipeline across the four core data types that power modern AI.

Data collection

Industrial and factory-floor image and video capture
3D scanning and point cloud data collection
Multi-sensor rig recording (camera, depth, LiDAR)
Human-robot interaction scenario capture
Synthetic and simulated environment data generation

Annotation

3D point cloud object annotation and segmentation
Object detection and classification for factory automation
6D pose estimation
Sensor fusion labeling across camera, depth, and LiDAR inputs
Defect and anomaly annotation for quality inspection models
Human pose and gesture annotation for safety and collaboration systems

Why Synnth for robotics

Every Synnth project follows the same structured pipeline, regardless of data type, language, or volume. That consistency is not bureaucratic — it is the mechanism through which we maintain quality at scale.

3D annotation depth. Our teams work natively in 3D point cloud and depth data, not just 2D imagery adapted after the fact — critical for pose estimation and bin-picking accuracy.

Environment-specific sourcing. We capture data in the lighting, clutter, and layout conditions your robot actually operates in, rather than relying on generic industrial stock datasets.

Custom ontology for non-standard object sets. Industrial parts and defect types rarely match off-the-shelf taxonomies — we build labeling schemas around your specific part catalog and failure modes.

Sensor fusion accuracy across camera, depth, and LiDAR streams, aligned in 3D space for models that fuse multiple sensor inputs at inference time.

Delivery formats

2,000+ expert annotators, matched to your domain

COCO, PCD/point cloud formats, custom JSON schemas, or direct integration with your perception pipeline.

Ready to build AI on data you can trust?

Whether you need a small pilot batch or an ongoing production annotation pipeline — tell us what you’re building and we’ll tell you exactly how we can help.

FAQs

Common questions

Everything you need to know before starting a AI Data collection or annotation project with Synnth.

💡 Can’t find your answer here? Talk to our team — we typically respond within one business day.

Can you annotate 3D point cloud and depth sensor data?

Yes, this is a core capability — including point cloud segmentation, object annotation, and 6D pose estimation.

Do you source data specific to our factory environment?

Yes. We run environment-specific capture campaigns matched to your actual operating conditions rather than relying on generic industrial datasets.

Can you build labeling schemas for non-standard parts or defect types?

Yes. We build custom ontologies around your specific part catalog, defect taxonomy, or object set.

Get started

Start your AI Data collection or annotation project today

Tell us your use case, action taxonomy, environment, and volume. Our team responds within one business day with a scoping plan and no-obligation quote.