Mobile Mapping Data
We manage LiDAR, camera, GNSS, and IMU-based field data along with Mission IDs, device serials, and client delivery schemas.
HD Map DataOps
AI Spatial Data Platform
AI-Powered Autonomous HD Map DataOps
MetaBread is an AI-powered Autonomous HD Map DataOps platform that converts raw 3D point-cloud data captured by LiDAR and camera-based mobile mapping into Production-Grade HD Map Data.
Why HD Map DataOps
Consumer maps and street-view images represent a specific moment in the real world. Autonomous HD maps require a much more precise machine-readable layer of 3D spatial information, including lanes, traffic lights, signs, curbs, road boundaries, and roadside objects.
Whenever roadworks, lane changes, signal updates, sign replacements, or operational-domain expansion occur, HD map data must be produced, inspected, and updated again. MetaBread automates this recurring workflow with AI.
From LiDAR to HD Map
AI transforms unstructured 3D sensor data into high-quality structured data ready for delivery.
Technical Pipeline
The bottleneck is not just labeling. It is the entire post-capture DataOps pipeline.
We manage LiDAR, camera, GNSS, and IMU-based field data along with Mission IDs, device serials, and client delivery schemas.
AI generates initial object candidates and labeling drafts for lanes, signals, crosswalks, signs, and road assets.
The system detects location errors, missing objects, misclassification, schema mismatches, topology errors, and rejection risks.
Expert reviewers focus on high-difficulty and high-risk segments instead of performing full manual inspection.
Platform
MetaBread is not a simple labeling tool. It connects preprocessing, object candidate detection, auto-cleaning, client-specific schema conversion, Auto-QA, rejection learning, delivery packaging, and version history into one operational platform.
Order IDs, Mission IDs, and client-specific requirements
Preprocessing, coordinate alignment, and noise filtering
Object candidate detection and labeling drafts
Error candidates and missing-region detection
Object names, attributes, coordinates, and file formats
Deliverable packages, metadata, and version records
Agentic Workflow
Agentic Workflow is an operational layer that upgrades the HD map production process. With order numbers, serials, client schemas, and raw data, AI agents support work classification, review allocation, QA, rejection handling, and delivery packaging.
Business
Processing, QA, and delivery of autonomous HD map data according to client specifications.
Updates and re-inspection driven by road changes, domain expansion, and QA feedback.
Data cleansing, labeling, fine-tuning, custom AI agents, and enterprise AI deliverables.
Before-and-after image management, electronic consent, and medical image/customer management solutions.
Intellectual Property
Our patent portfolio covers HD Map DataOps, point-cloud Auto-QA, event-based data history management, medical AI, and platform automation.
Contact
AI-Powered Autonomous HD Map DataOps Platform