Data Service High-Quality Sensor

High-Quality Sensor Data Annotation for Real-World AI Performance

Train, validate, and deploy perception systems with expertly annotated multimodal sensor data.

Turn Raw Sensor Streams into Reliable, Model-Ready Intelligence

DDD provides end-to-end sensor data annotation services for perception systems that rely on complex, high-volume sensor inputs. We work across LiDAR, radar, RGB cameras, depth sensors, IMU, and fused sensor data, ensuring every frame, point cloud, and signal is accurately labeled, validated, and enriched for model training and evaluation.

Tell Us About Your Project

Our Services

Time-Series Event Labeling (IoT & Industrial Sensors)

Annotate events, states, and anomalies on sensor streams with precise timestamps and durations.
Supports custom taxonomies (fault codes, operating modes) and consistent labeling across devices/sites.

Anomaly Detection Ground Truth (Quality & Predictive Maintenance)

Create validated “normal vs. abnormal” labels and severity levels for model training and evaluation. Includes root-cause tagging (when available), exclusion rules, and high-confidence gold sets.

Sensor Data Cleaning, Synchronization & Resampling

Align multi-sensor feeds, correct time drift, handle missing values, and standardize sampling rates.
Outputs are analysis-ready and consistent for ML pipelines and monitoring dashboards.

Multisensor Fusion Annotation (IMU/GPS/Radar/
LiDAR/Telemetry)

Annotate correlated events across sensors (e.g., braking + vibration spike + GPS context) to capture full situations.
Enables robust training datasets for robotics, mobility, and industrial operations.

Quality Assurance, Calibration Metadata & Dataset Audits

Run QA checks for label consistency, boundary accuracy, and class balance across time-series datasets. Deliver calibration/context metadata (device, location, operating conditions) and audit reports for traceability.

Use Cases We Support

Multimodal Perception Training

Annotate synchronized camera, LiDAR, radar, and IMU data to train robust sensor-fusion models.

3D Point Cloud Annotation

High-precision 3D bounding boxes, semantic segmentation, and instance labeling for LiDAR-based perception.

Edge-Case & Failure Mode Curation

Identify, annotate, and catalog rare, ambiguous, or safety-critical scenarios that challenge model performance.

Autonomous Navigation & Path Planning

Label dynamic objects, drivable space, obstacles, and trajectories across time-series sensor data.

Human-Machine Interaction Modeling

Annotate gestures, pose, intent, and motion patterns for humanoids and collaborative robots.

Medical & Biosensor Data Interpretation

Label time-series and multimodal healthcare sensor data for diagnostics, monitoring, and predictive models.

Agricultural Sensing & Automation

Annotate sensor data for crop health monitoring, yield estimation, and autonomous farming equipment.

Industries We Support

Autonomous Driving

High-precision sensor annotation to improve perception, prediction, and planning in real-world driving conditions.

ADAS

Accurate labeling of safety-critical scenarios to support validation, compliance, and reliability testing.

Robotics

Sensor-rich data annotation for navigation, manipulation, and real-time decision-making systems.

Healthcare

Secure, compliant annotation of medical and biosensor data for AI-driven diagnostics and monitoring.

Agriculture Technology

Sensor data labeling for precision agriculture, autonomous machinery, and crop analytics.

Humanoids

Multimodal annotation to enable perception, motion understanding, and human-robot interaction.

End-to-End Sensor Data Annotation Workflow

Whether you need a one-time dataset or a continuous annotation pipeline, DDD manages the full lifecycle:

Discovery & Scoping

We assess your model goals, sensor modalities, failure points, and performance gaps.

Annotation Strategy Design

Define schemas, taxonomies, edge-case categories, accuracy thresholds, and tooling requirements.

Data Ingestion & Pre-Processing

Secure ingestion, synchronization, and normalization of raw sensor streams.

AI-Assisted Annotation

Combine automation with expert human review to scale efficiently without sacrificing quality.

Domain Expert Validation

Specialized reviewers validate annotations against safety, accuracy, and scenario-specific criteria.

Curation, Enrichment & Metadata Tagging

Cleaned, structured datasets enriched with contextual metadata for reuse and analysis.

Quality Assurance & Audit Trails

Multi-layer QA, inter-annotator agreement checks, and full traceability.

Delivery & Continuous Feedback Loop

Seamless integration into training pipelines with feedback-driven iteration.

What Our Clients Say

DDD helped us uncover and annotate critical edge cases we were missing. Their sensor expertise directly improved our model stability in real-world testing.

— Head of Perception Engineering, Autonomous Vehicle Company

Their ability to handle multimodal sensor data at scale, without sacrificing accuracy, made DDD a true extension of our team.

— Director of AI, Robotics Company

From LiDAR to time-series sensor data, DDD delivered clean, consistent datasets that accelerated our deployment timelines.

— CTO, AgTech Platform

The quality of their annotations significantly improved our perception and motion models in complex environments.

— Product Lead, Humanoid Robotics Company

Why Choose DDD?

Edge-Case-Focused Approach

We prioritize rare, ambiguous, and safety-critical scenarios where model performance matters most.

Human-in-the-Loop at Scale

AI-assisted workflows combined with trained domain experts deliver both speed and precision.

Flexible Engagement Models

Seamlessly scale from pilots and proofs-of-concept to long-term annotation pipelines.

Secure, Compliant Operations

Built to handle sensitive, regulated, and proprietary sensor data with confidence.

DDD’s Commitment to Security & Compliance

Your sensitive sensor data is protected at every stage through rigorous global standards and secure operational infrastructure.

Verified controls across security, confidentiality, and system reliability.

Holistic information security management with continuous audits.

Responsible handling of personal, biometric, and medical sensor data.

Automotive-grade protection for mobility and vehicle AI workflows.

High-Precision Sensor Data Annotation for Real-World AI

Talk to an Expert

Frequently Asked Questions

What annotation types do you offer for 3D and sensor data?

Our capabilities include 3D bounding boxes, semantic and instance segmentation, point-level labeling, trajectory tracking, pose and motion annotation, and time-series labeling.

How do you handle edge cases and rare scenarios?

We actively identify, curate, and annotate rare, ambiguous, and safety-critical edge cases that are often underrepresented but critical for real-world performance.

Can you support both one-time projects and ongoing pipelines?

Absolutely. We support pilot datasets, validation efforts, and fully managed, continuous annotation pipelines that scale with your model lifecycle.

How do you ensure annotation accuracy and consistency?

We apply multi-layer QA, inter-annotator agreement checks, domain expert validation, and full audit trails to ensure production-grade quality.

Do you use AI-assisted annotation tools?

We combine automation and AI-assisted tooling with human-in-the-loop review to improve speed while maintaining accuracy and reliability.