3D Point Cloud & LiDAR Automation Platform

Built for Autonomous Perception, Robotics, and Spatial Intelligence

3D Point Cloud Annotation Platform | LiDAR Labeling & Automation – JTheta.ai

Accelerate autonomous perception AI with JTheta.ai’s 3D Point Cloud Annotation Platform. AI-assisted LiDAR labeling for ADAS, robotics, and mapping teams. Experience faster, smarter automation for 3D data.

🧭 Purpose-Built for Mission-Critical 3D Perception

JTheta.ai empowers autonomous vehicle, robotics, and mapping teams with an intelligent 3D Point Cloud Annotation Platform designed to simplify and accelerate LiDAR data labeling.

Whether you’re developing ADAS perception models, SLAM systems, or spatial mapping solutions, our automation-first platform combines AI-assisted precision, multi-sensor fusion, and real-time collaboration to help your models see, learn, and adapt — faster and more accurately than ever before.

Built for the next generation of autonomy — from driver-assist systems to digital twins and mobile robotics.

Key Features

Jtheta.ai LiDAR Annotation Platform

✅ Multi-Sensor Fusion

Integrate LiDAR, RADAR, and camera data into a unified 3D workspace. Align, calibrate, and synchronize multiple sensors. Visualize multi-modal data with timestamp accuracy.

✅ AI-Assisted 3D Labeling

Accelerate your 3D annotation pipeline with automated pre-labeling powered by perception models. Supports bounding boxes, voxel segmentation, and object tracking.Reduces manual effort by up to 70%, maintaining human-level accuracy.

✅ Advanced 3D Point Cloud Viewer

High-performance visualization for dense point cloud datasets. Slice by frame, zoom by depth, switch between perspective and orthographic views. Visualize LiDAR intensity, distance, and classification layers.

✅ Sensor Calibration & Metadata Sync

Auto-calibrate extrinsic and intrinsic parameters and maintain full synchronization across modalities. Combine multiple viewpoints seamlessly.Retain timestamps, GPS, and IMU data for complete spatial context.

✅ Track-Level Object Linking

Maintain consistent object IDs across time sequences to train motion-aware models.

✅ Collaborative Workflow

Enable real-time, multi-user editing between annotators, reviewers, and QA teams.

✅ Flexible Export Formats

Export annotations in KITTI, nuScenes, Supervisely, Custom CSV, Custom JSON or custom formats. Easily integrate into PyTorch, TensorFlow, or ROS training pipelines.

✅ Voxel & Instance Segmentation

Annotate dense point clusters or voxelized volumes for high-fidelity learning.

Common Use Cases

Why Choose JTheta.ai for 3D LiDAR Automation

Unlike generic labeling tools, JTheta.ai fuses AI automation, multi-sensor fusion, and enterprise-grade collaboration into one powerful platform built for scale, accuracy, and security.

Feature

AI-Assisted Labeling

Multi-Sensor Fusion

Collaboration Workflow

Custom Export Formats

Cloud Performance

Annotation Speed

JTheta.ai

✅ Advanced 3D Pre-Labeling

✅ LiDAR + Camera + RADAR

✅ Real-Time Multi-User

✅ KITTI, COCO, JSON, ROS

✅ Scalable & Secure

⚡ Up to 3× Faster

Conventional Tools

⚪ Limited

⚪ Partial

⚪ Sequential

⚪ Fixed Templates

⚪ Varies

⚪ Manual & Slower

🔒 Enterprise-Grade Security & Compliance

HIPAA-ready infrastructure

End-to-end encryption for data transfer

Role-based access control (RBAC)

Private cloud or on-prem deployment options

🧠 How It Works

1️⃣ Upload & Sync — Import LiDAR, RADAR, and camera data. Automatic calibration aligns all sensors.

2️⃣ Auto-Prelabel — AI models generate accurate 3D bounding boxes or segmentation masks.

3️⃣ Review & Refine — Human experts validate and correct AI labels in real time.

4️⃣ Export & Integrate — Deliver structured annotations directly to your ML pipelines.

Start Automating 3D LiDAR Annotation with JTheta.ai

Simplify 3D labeling. Accelerate your perception pipeline.
Experience AI-powered automation built for teams designing the future of autonomy.

FAQ

Does JTheta.ai support multi-sensor fusion?

✅ Yes — LiDAR, camera, and RADAR streams are synchronized and calibrated automatically.

Can I customize export formats for my training pipeline?

✅ Absolutely — JSON, KITTI, COCO, ROS bag, and user-defined formats are supported.

Is JTheta.ai cloud-based or on-premise?

✅ Cloud-native by default, with optional on-prem deployment for defense and healthcare clients.

How does JTheta.ai improve annotation speed?

✅ Through AI-assisted pre-labeling and automation-first workflows, reducing manual effort by up to 70%.

JTHETA.AI