Accurately labeled LiDAR data to help your autonomous systems see, sense, and navigate the world with precision.
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Our trained annotation specialists bring hands-on experience in LiDAR and depth-sensing data. From object detection to semantic segmentation, we ensure every 3D frame is precisely labeled to support complex AV and robotic workflows.
Our dedicated annotation team ensures every dataset is crafted with accuracy and care—empowering AI with human intelligence.
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We provide precise 3D point cloud annotations for autonomous vehicles, robotics, and mapping, including classification, segmentation, tracking, and semantic labeling to help your AI navigate complex environments confidently.
2D Bounding Boxes
Precisely track and detect objects in video frames for real-time applications and analytics.
Semantic Segmentations
Assign pixel-level labels to video frames for detailed understanding in autonomous systems.
Cuboid Annotation
Capture object depth and dimensions, enabling accurate spatial recognition for robotics and AR/VR.
Polygon Annotations
Identify key body or facial points for advanced motion tracking and pose estimation in videos.
Line and Polyline
Annotate object trajectories or lane markings, enhancing autonomous driving and traffic control systems.
We adapt quickly to your evolving project needs. Whether you're launching a proof of concept or scaling to millions of annotations, our agile workflow ensures speed, flexibility, and consistent quality — without the bottlenecks
Your data is your asset — and we treat it that way. We follow strict data privacy protocols, secure infrastructure practices, and industry-grade compliance standards to ensure your information stays protected at every step.
From emerging startups to global enterprises, we offer scalable pricing models that align with your budget and goals. You get top-tier annotation quality — without the enterprise-only price tag.
From initial consultation to final delivery, our 3D LiDAR annotation workflow is built for accuracy and transparency. We start by understanding your project needs, then carefully label and review the point cloud data with expert teams. Throughout, we incorporate your feedback to ensure every detail meets your standards — delivering ready-to-use data that powers your AV and robotics applications.
We start by aligning on your annotation goals, data formats, and key success metrics.
This phase ensures a clear understanding of your project scope and technical needs.
Your raw data is cleaned, structured, and annotated using best-fit tools and techniques.
Our skilled team ensures high precision and efficiency throughout the process.
We share annotated samples for your review. Your feedback guides refinement of labeling instructions, ensuring the workflow is optimized to your expectations.
A thorough QA process is conducted with multi-level checks—combining expert review and automation to validate accuracy, consistency, and compliance with guidelines.
The fully annotated dataset is delivered in your desired format, on time.
We offer continuous support for updates, scaling, or retraining as your AI models evolve.
Our clients share how Intellisane AI’s precise and reliable annotation services boosted their AI projects, showcasing our commitment to quality and trust.
Intellisane AI played a key role in helping us reach 97% accuracy in automating foundation layout detection. Their deep understanding of spatial data and labeling precision brought measurable improvements to our AI pipeline. The team was communicative, detail-oriented, and delivered everything ahead of schedule.S. RagavanSr. ML Engineer
Our fashion AI model required pixel-level segmentation across 72 garment categories—and Intellisane AI handled it flawlessly. They quickly adapted to our complex annotation guidelines and delivered consistent, high-quality labels at scale. Their domain focus, speed, and attention to visual detail were exactly what we needed.Valerio ColamatteoSr. AI Scientist & Team Lead
For our ADAS project, Intellisane AI delivered precise vehicle annotations across diverse traffic scenes, including multiple object classes and occlusion scenarios. Their expertise in automotive data workflows and quality-first mindset helped us pass all validation checks, with timely delivery and professional communication throughout.Raphael LopezCo-Founder & CTO
Explore how 3D point cloud annotation supports innovation across robotics, automotive, healthcare, logistics, construction, and more.
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