Power your embodied AI, robotics, and autonomous systems with 99% accurate 3D point cloud and sensor fusion labeling.
Building true spatial intelligence requires more than just collecting raw sensor data; it demands flawless interpretation of the physical world. When autonomous vehicles or embodied robots rely on poorly labeled 3D point clouds, the cost of inaction is severe. Misaligned bounding boxes or missed object tracking can stall model deployment by critical weeks and cost millions in failed edge-case testing. Without pixel-perfect accuracy and robust semantic segmentation across temporal frames, your spatial models will consistently fail to understand complex, dynamic real-world environments safely.
Abaka AI transforms chaotic, unstructured sensor outputs into structured, training-ready spatial intelligence. Our 3D data annotation services seamlessly combine proprietary automation through the Abaka Forge platform with the precise judgment of expert human reviewers spanning 50+ countries. Whether you are dealing with sparse outdoor LiDAR scans or incredibly dense 3D indoor scenes, our SOC 2 and ISO 27001 certified pipelines ensure your data remains completely secure, exclusively yours, and 99% accurate. We deliver the foundational ground truth required to confidently deploy frontier AI.
Scaling 3D annotation operations often results in rapid quality degradation. Complex spatial reasoning and LiDAR-camera fusion tasks demand specialized expertise, not standard crowdsourcing. When reviewers lack fundamental domain knowledge in kinematics or spatial dimensions, annotation accuracy plummets well below 80%. This forces your machine learning engineers to waste up to 70% of their valuable time manually auditing, cleaning, and re-labeling point clouds instead of focusing on core algorithm development and model optimization.
As your sensor fleet expands, processing terabytes of multi-modal 3D data creates an impenetrable volume wall. Legacy labeling operations struggle to handle more than a few hundred dense frames daily. Without large-model automation to pre-annotate and structure the data effectively, your AI development pipeline bottlenecks immediately. This drastically delays critical perception model updates by several weeks, allowing competitors to reach deployment faster while your internal teams drown in a backlog of unstructured spatial data.
Mishandling proprietary sensor data introduces catastrophic IP and privacy risks. Capturing faces or license plates in unmasked LiDAR and high-resolution camera feeds can violate GDPR or CCPA requirements directly. Without fully segregated, secure data pipelines and strict SOC 2 compliance auditing, your organization faces severe legal and regulatory exposure. This often forces engineering teams to halt autonomous model research before it even reaches production, wasting months of development time and millions in funding while legal teams scramble to secure the data supply chain.
We specialize in dense and sparse 3D point cloud labeling for autonomous driving and robotics. Our teams expertly apply tight 3D cuboids, track dynamic objects across temporal 4D frames, and perform complex panoptic segmentation, ensuring your spatial models achieve a consistent 99% accuracy in diverse real-world environments.
Aligning multi-sensor outputs is absolutely critical for robust perception. We provide pixel-perfect LiDAR and camera fusion annotation, seamlessly mapping 2D high-resolution image pixels to 3D point clouds. This guarantees synchronized ground truth for complex driving environments, significantly reducing your model preprocessing time by up to 70%.
Assigning distinct class labels to every individual point in a massive 3D scan requires immense precision. Our specialized annotators deliver high-fidelity semantic and instance segmentation for 3D indoor scenes and sprawling outdoor environments, which is crucial for advanced embodied AI, spatial computing, and next-generation VR applications.
Understanding motion and trajectory is fundamental to autonomous systems. We track dynamic objects—such as pedestrians and vehicles—across sequential 3D LiDAR frames, interpolating movement trajectories and managing difficult occlusion scenarios. This continuous temporal annotation empowers your robotics to predict movement with unprecedented reliability and safety.
Build highly precise high-definition maps for Tier-1 autonomous driving programs. We meticulously annotate road networks, lane markers, traffic signs, and pedestrian crossings in 3D space. This provides the essential vectorized infrastructure data needed for safe, automated navigation at a highly competitive rate of just $3/km for road lanes.
Train frontier systems to deeply understand human movement. We annotate complex 3D skeletal structures and precise keypoints from multi-view cameras and dense point clouds. This capability is vital for human-computer interaction models, embodied robotics, medical AI diagnostics, and advanced surveillance systems requiring exact posture and action recognition.
Enhance your frontier foundation models with logic-based spatial reasoning datasets. We actively formulate multi-layer QA pairs and spatial relationship annotations based on intricate 3D environments, effectively teaching foundation models how physical objects interact. This reliably bridges the persistent gap between raw computer vision and logical spatial reasoning.
Deploy autonomous agents safely through highly realistic simulated training. We design and expertly annotate custom reinforcement learning environments perfectly tailored to your specific hardware requirements. By structuring authentic 3D interaction data, we rapidly accelerate intelligent agent capability development for groundbreaking embodied AI applications.
Accelerate your model iteration cycles dramatically. By leveraging Abaka Forge's large-model automation and our global workforce of 1M+ specialized annotators, we process vast amounts of 3D point cloud and LiDAR data up to 50x faster, ensuring your perception models reach full production deployment critical weeks ahead of schedule.
Eliminate the massive overhead of hiring and maintaining an internal data labeling workforce. Our elastically scalable infrastructure allows you to pay only for the exact annotations you need, such as $100 per 3D indoor scene scan. Avoid hidden operational costs and drastically reduce your overall data processing expenditures.
Protect your proprietary spatial datasets with our enterprise-grade security protocols. Operating entirely under strict NDAs, SOC 2, ISO 27001, and GDPR compliance, our fully segregated secure pipelines guarantee 0% copyright risk and full IP provenance, definitively keeping your frontier autonomous AI safe from data breaches.
Seamlessly adapt to violently fluctuating data volumes. Whether you are launching an initial algorithmic pilot project or immediately scaling up to massive fleet deployments across 50+ countries, our on-demand custom capture pods and flexible global workforce expand instantly to meet your project's absolute maximum throughput requirements.
Complex 3D spatial data requires significantly more than general knowledge. We exclusively deploy scholar-network reviewers and specialized annotators meticulously trained in embodied AI, autonomous driving, and geospatial mapping. This highly targeted expertise ensures nuanced spatial reasoning tasks are executed with a mathematically guaranteed 99% accuracy.
Free your machine learning engineers to focus purely on algorithm development rather than manual data cleaning. By aggressively reducing sensor preprocessing time by 70%, strategic outsourcing empowers your core engineering team to innovate faster, continuously pushing the boundaries of what your frontier AI models can fundamentally achieve.
We provide Tier-1 autonomous driving programs with pixel-perfect LiDAR+Camera fusion, continuous 4D object tracking, and complex road lane annotations at just $3/km. Our highly accurate 3D datasets ensure your self-driving models navigate the most chaotic, complex urban environments safely and reliably.
Fuel your frontier foundation models with high-fidelity spatial reasoning data. We expertly annotate multi-modal 3D environments, enabling next-generation LLMs and advanced vision models to truly understand and natively interact with the physical world with unparalleled depth, logic, and rich spatial context.
Accelerate robotic deployment with custom RL environment design and comprehensive 3D indoor scene annotations. At just $100/scan, we rapidly deliver the foundational structural ground truth strictly necessary for embodied agents to perceive, physically manipulate, and navigate real-world spaces flawlessly.
Enhance critical medical AI diagnostics with highly precise 3D volumetric annotation. Our medically specialized scholar-network reviewers accurately label complex 3D scans and point clouds, actively supporting advanced applications in cutting-edge surgical robotics, detailed anatomical modeling, and automated disease detection.
Revolutionize the retail experience entirely with robust spatial intelligence. We densely annotate 3D store layouts and complex customer movement patterns using sensor fusion data, definitively enabling seamless cashier-less checkouts, automated robotic inventory management, and deeply immersive AR shopping environments.
While 3D data is unconventional in traditional finance, we robustly support property and asset valuation models by annotating dense 3D geospatial and architectural scans. This provides highly quantitative spatial data for advanced algorithmic risk assessment and next-generation real estate portfolio management.
Transform raw aerial and satellite point clouds into highly actionable maps. We precisely label dense 3D topographies, complex building footprints, and sprawling infrastructure networks, immediately providing the essential vectorized data critically required for modern urban planning, environmental monitoring, and intelligent logistics.
Significantly enhance threat detection and perimeter security through highly robust 3D surveillance annotation. We strictly process LiDAR and radar point clouds to accurately track anomalous movements and objects in 4D space, adhering exclusively to secure, segregated pipeline protocols at all times.
Optimize fully automated farming and smart manufacturing with verified 3D sensor data. We precisely annotate complex crop topographies, intricate factory floor layouts, and machinery kinematics, actively empowering industrial robots to operate autonomously and highly efficiently in dynamic, complex outdoor and indoor environments.
We begin by thoroughly analyzing your raw 3D point cloud or complex sensor fusion data. Our expert machine learning engineers collaborate with your team to define strict, customized annotation guidelines. Next, we configure the proprietary Abaka Forge platform to natively handle your specific LiDAR or camera output formats. Finally, we establish fully segregated, SOC 2 and ISO 27001 compliant data transfer protocols, ensuring your proprietary spatial information remains completely secure and protected from day one of the engagement.
We systematically execute an initial pilot run using a highly curated subset of your 3D data. Our specialized annotators apply precise 3D cuboids and initial semantic segmentation. Together, we meticulously review the results, actively refining the edge-case guidelines and resolving spatial ambiguities to ensure we consistently hit your uncompromising 99% accuracy targets before we begin scaling operations.
With your spatial guidelines permanently locked, we deploy powerful large-model automation via Abaka Forge to pre-label the data, accelerating the overall process by up to 50x. Our 1,000,000+ global workforce seamlessly takes over the complex spatial reasoning and multi-layer QA tasks, rapidly processing massive volumes of dense sensor data without ever sacrificing precision.
We reliably deliver fully annotated 3D datasets in continuous, predictable batches. Every single 3D bounding box, tracked trajectory, and fused LiDAR frame undergoes rigorous multi-layer quality assurance. We strictly cap throughput at 500 files per day per annotator, completely ensuring zero quality decay while permanently maintaining strict compliance with your project specifications.
Your deeply experienced, dedicated success manager conducts weekly strategic synchronization meetings. We transparently review throughput metrics, proactively address any new spatial edge-cases discovered in the 3D data, and dynamically adjust our capture pods and workforce allocation to perfectly match your constantly evolving AI development velocity and production schedule.
Abaka Forge provides comprehensive support for complex spatial datasets. From dense 3D indoor scenes to synchronized autonomous vehicle sensor arrays, we deliver precision annotations across all critical modalities and industry-standard formats, ensuring your models receive the exact ground truth required.
| Modality | Annotation Types | Tools | Output Formats |
|---|---|---|---|
| Text | Spatial Reasoning QA, Scene Descriptions, Metadata Tagging | Abaka Forge | JSON, CSV, TXT |
| LLM RLHF | Prompt Engineering, Spatial Logic Eval, Factuality Checking | Abaka Forge | JSONL, Parquet, Arrow |
| Image | 2D Bounding Boxes, Polygons, Keypoints, Semantic Segmentation | Abaka Forge | COCO, YOLO, Pascal VOC |
| Video | Temporal Object Tracking, Event Tagging, Action Recognition | Abaka Forge | MP4, AVI, Frame-level JSON |
| 3D/4D Point Cloud | 3D Cuboids, Point-wise Segmentation, 4D Tracking | Abaka Forge | PCD, PLY, LAS, JSON |
| LiDAR + Camera fusion | Sensor Calibration, Multi-view Fusion, 2D-to-3D Mapping | Abaka Forge | Custom JSON, NuScenes-format, Rosbag |
| Audio | Speech-to-Text, Spatial Audio Tagging, Event Classification | Abaka Forge | WAV, MP3, Text-grid |
The customer was heavily struggling to scale their autonomous vehicle perception models due to severe, persistent bottlenecks in their core data pipeline. Processing massive volumes of completely unstructured LiDAR and high-resolution camera feeds resulted in a crippling 40% error rate in 3D object tracking during complex urban scenarios. Their internal engineering teams were vastly overwhelmed, spending critical development time manually correcting misaligned bounding boxes and delayed sensor fusion mappings. This widespread quality decay actively threatened to push their next-generation driving model deployment back by several critical months, endangering key market milestones.
Abaka AI aggressively integrated our proprietary Abaka Forge platform directly with the client's data lakes through deeply secure, fully SOC 2 compliant pipelines. We immediately deployed a highly specialized team of 3D annotators meticulously trained in temporal 4D object tracking and LiDAR-camera fusion. By systematically leveraging large-model automation to precisely pre-annotate standard road environments, our human experts focused exclusively on notoriously difficult edge-cases like obscured pedestrians and highly complex intersections, successfully ensuring a rigorous multi-layer QA process at massive scale.
Within exactly three weeks, the autonomous driving program saw a complete, transformative turnaround in their spatial data operations. We systematically reduced their data preprocessing time by 70%, consistently delivering fully synchronized 3D point cloud annotations with an undeniable 99% accuracy rate. The resulting high-fidelity ground truth actively enabled their perception models to successfully navigate previously failing edge-cases with total confidence, ultimately allowing the engineering team to confidently launch their dramatically updated self-driving architecture two full weeks ahead of the initially revised schedule.
Abaka AI completely transformed our spatial data pipeline. Their ability to consistently deliver 99% accurate 3D point cloud annotations at scale allowed us to deploy our latest embodied robotics models confidently. The direct integration with Abaka Forge was impressively seamless and entirely secure.
The precision of their LiDAR and high-resolution camera fusion labeling is entirely unmatched in the industry. We were struggling heavily with massive volume walls, but Abaka's specialized annotators and automated workflows aggressively accelerated our autonomous driving perception training by several months.
Security and compliance were our absolute top concerns when outsourcing sensitive 3D scan data. Abaka's strict SOC 2 and ISO 27001 fully segregated pipelines gave us the exact peace of mind we critically needed. They are a genuinely trustworthy data partner for frontier models.
Their unit pricing is brilliantly transparent and highly competitive. Paying just $100 per 3D indoor scene scan for such incredibly high-quality semantic segmentation has drastically reduced our R&D costs without ever compromising our perception model's performance in real-world environments.
Abaka AI effectively bridges the vast gap between raw spatial data and reliable, production-ready models by powerfully combining the 50x processing speed of the Abaka Forge platform with the highly nuanced intelligence of over 1 million globally distributed, deeply specialized annotators. We never build competing foundation models; your 3D sensor data remains exclusively yours forever, permanently ensuring complete IP protection while consistently delivering a guaranteed 99% accuracy rate for your most complex LiDAR, multi-sensor point cloud, and embodied AI datasets.
Your highly sensitive sensor data is never repurposed, resold, or shared. We strictly provide full IP provenance with 0% copyright risk, backed completely by strict NDAs and enterprise-grade security.
Our fully segregated secure pipelines are comprehensively compliant with SOC 2, ISO 27001, GDPR, and CCPA, completely ensuring your proprietary 3D datasets are massively protected at all times.
From small initial pilot runs to massive autonomous vehicle fleet deployments, our on-demand capture pods and elastic workforce flawlessly handle any volume. We enforce a maximum of 500 files/day per annotator to maintain pristine 3D labeling quality.
We do not rely on generic crowdsourcing. Our scholar-network reviewers are trained specifically in complex spatial reasoning, 3D kinematics, and multi-sensor fusion, providing the highly specialized knowledge critically required for frontier AI.
Entirely self-funded and profitable, we operate completely without VC pressure, allowing us to consistently offer highly straightforward pricing. Whether it is $3/km for road lane annotations or $100/scan for 3D indoor scenes, you always know exactly what you are paying for.
Annotate the Present. Train the Future. Partner with Abaka AI to build flawlessly accurate 3D datasets for your embodied agents and autonomous systems.
