AI Training Data Annotation & Labeling for Humanoid Robots
SHIRO BPO delivers production-grade AI data annotation for humanoid robots from Mysore, India. We provide 3D point cloud labeling for humanoid robots, LiDAR annotation, sensor fusion tagging, and image/video labeling -- the embodied AI training data that companies like Figure AI and Agility Robotics need to teach robots to see, grasp, and navigate the physical world.
Your humanoid robots are only as intelligent as the data they learn from. At SHIRO, we provide high-quality, human-verified data annotation services specifically designed for the robotics and AI industry. Our trained annotators in Mysore deliver meticulously labeled datasets across image, video, 3D point cloud, and multi-sensor modalities -- the kind of embodied AI training data that powers the perception systems of next-generation humanoid platforms.
We support the full spectrum of annotation types: bounding boxes, polygons, semantic and instance segmentation, keypoint detection, and 3D cuboids. Whether you are training vision models for object recognition, depth estimation, or grasping -- like the manipulation pipelines used by companies such as Figure AI and Agility Robotics -- our team delivers at scale with 99%+ accuracy.
Our sensor fusion capabilities allow us to align and annotate data across camera, LiDAR, radar, and IMU inputs -- critical for robots that must understand their environment in three dimensions. We also provide NLP and gesture annotation for human-robot interaction models, enabling natural language commands and physical gesture recognition.
SHIRO operates under strict NDAs with SOC 2-ready processes. Your proprietary datasets and IP are protected by enterprise-grade security protocols, air-gapped annotation environments, and role-based access controls. We are fully compliant with GDPR and India’s Digital Personal Data Protection Act 2023.
Key Benefits
Image & Video Annotation
Bounding box, polygon, semantic segmentation, and keypoint annotation for 2D visual data. Support for all major formats and annotation tools.
3D Point Cloud Labeling
3D cuboid annotation, point-level segmentation, and object tracking across LiDAR scans for spatial awareness and navigation training.
Sensor Fusion Tagging
Cross-modal annotation aligning camera, LiDAR, radar, and IMU data for comprehensive environmental understanding.
NLP & Gesture Annotation
Text classification, intent labeling, entity recognition, and gesture tagging for human-robot interaction and voice command models.
99%+ Quality Assurance
Multi-tier QA process with automated checks, human review, and consensus labeling to ensure consistently high annotation accuracy.
Scalable Teams
Flexible capacity from 10 to 500+ annotators on demand. Rapid ramp-up for large dataset projects without sacrificing quality.
Start with a free annotation pilot -- see our quality before you commit.
Get a Free Pilot3D Point Cloud & LiDAR Annotation
Our annotators work with raw LiDAR scans, dense point clouds, and multi-frame sequences to produce precise 3D cuboids, point-level semantic labels, and object tracking annotations. This data is critical for humanoid robots navigating real-world environments -- the same 3D point cloud labeling for humanoid robots that powers spatial awareness in platforms from Figure AI and Agility Robotics.
- 3D cuboid annotation with heading & velocity
- Point-level semantic segmentation
- Multi-frame temporal object tracking
- Cross-sensor alignment (LiDAR + Camera)
Why SHIRO for Humanoid Robotics Data Annotation
Not all annotation providers understand robotics. SHIRO was built specifically for humanoid AI -- our team, tools, and processes are purpose-engineered for embodied AI training data.
Mysore Talent Pool, Robotics-Trained
Our annotation workforce is drawn from Mysore's engineering colleges and trained specifically in 3D spatial reasoning, LiDAR interpretation, and robotic perception ontologies. This is not generic data labeling -- our team understands embodied AI.
99%+ Accuracy, Contractually Guaranteed
Every engagement includes an SLA-backed accuracy guarantee. Our multi-tier QA -- automated geometric checks, inter-annotator agreement scoring, and senior consensus review -- consistently delivers 99%+ accuracy across image, video, and 3D point cloud annotation.
Trusted by US Humanoid Robotics Innovators
SHIRO has delivered annotation for companies building humanoid robots at the level of Figure AI and Agility Robotics. Our anonymized case studies document 1.2M+ images annotated at 99.2% accuracy for a Series-B US robotics firm.
SOC 2-Ready, NDA-Protected
Air-gapped annotation environments, RBAC, encrypted transfer pipelines, and full compliance with GDPR and India's DPDP Act 2023. Your proprietary embodied AI training data is secured at every layer.
Pricing Tiers
Flexible plans designed to scale with your annotation needs. All pricing is custom-quoted based on data type, complexity, and volume.
Starter
For pilot projects and proof-of-concept datasets
- Up to 10,000 images / month
- 2D bounding box & polygon
- Single-pass QA review
- Standard delivery (5 business days)
- Email support
- Basic project dashboard
Professional
For production-grade datasets with multi-modal support
- Up to 100,000 assets / month
- 2D + 3D point cloud annotation
- Multi-tier QA with consensus voting
- Priority delivery (3 business days)
- Dedicated project manager
- Real-time QA dashboard access
- Sensor fusion tagging
- Custom taxonomy & ontology support
Enterprise
For large-scale, continuous annotation pipelines
- Unlimited volume
- All annotation types + NLP & gesture
- Dedicated annotation team (50-500+)
- Same-day rush delivery available
- 24/7 Slack / Teams integration
- Air-gapped secure environment
- SOC 2 compliance documentation
- Custom API integration & webhooks
- Quarterly business reviews
All plans include NDA coverage and data security guarantees. Volume discounts available for annual commitments.
Ready to see our annotation quality firsthand?
Get a Free QuoteSample Project Timeline
A typical engagement from kickoff to full production in 5-8 weeks. Timelines are customized based on data volume and complexity.
Kickoff & Discovery
- Requirements workshop with your ML team
- Annotation taxonomy & guideline creation
- Tool setup and environment provisioning
- Security & NDA onboarding
Pilot Sprint
- Annotate 500-1,000 sample assets
- Client review & feedback session
- Calibrate quality rubric & edge cases
- Finalize annotation SOP document
Ramp-Up
- Train full annotation team (10-50 annotators)
- Begin production at 25% capacity
- Daily QA metrics reporting
- Iterate on feedback from pilot corrections
Full Production
- 100% throughput at target volume
- Multi-tier QA achieving 99%+ accuracy
- Weekly delivery batches in your format
- Continuous calibration & annotator scoring
Steady State & Optimization
- Sustained delivery pipeline
- Monthly accuracy & throughput reports
- Taxonomy updates as models evolve
- Quarterly business reviews with your team
99.2% Accuracy for a Leading Robotics Firm
How SHIRO helped a US-based humanoid robotics company annotate 1.2 million images at 99.2% accuracy while cutting costs by 58%.
99.2%
Final Accuracy
1.2M+
Images Annotated
72 hrs
Turnaround Time
58%
Cost Savings
The Challenge
A Series-B humanoid robotics startup needed to annotate 1.2 million images capturing indoor household environments for their manipulation and navigation models. Their existing US-based vendor was producing annotations at 94% accuracy with a 10-day turnaround -- below the 98% threshold their ML pipeline required and too slow for their release cadence.
The SHIRO Solution
We assembled a dedicated 120-person annotation team in Mysore, trained on the client's custom taxonomy covering 340 object categories across kitchen, living room, and bathroom environments. Our multi-tier QA process included automated geometric validation, inter-annotator agreement scoring, and a senior reviewer consensus layer for ambiguous edge cases.
The Results
Within 8 weeks, SHIRO reached steady-state delivery of 50,000 annotated images per week at 99.2% accuracy -- exceeding the client's 98% threshold. Turnaround time was reduced from 10 business days to 72 hours per batch. The client reported a 58% reduction in annotation costs compared to their previous vendor, and their object detection model's mAP score improved by 4.7 percentage points after retraining on SHIRO-annotated data.
“SHIRO's annotation quality directly improved our model performance. The 99.2% accuracy rate and 72-hour turnaround transformed our training data pipeline from a bottleneck into a competitive advantage.”
-- VP of AI, US Humanoid Robotics Company
Real-time QA dashboard tracking accuracy, throughput, and annotator performance.
Key Milestones
- Week 1: Pilot at 96.8% accuracy
- Week 2: Calibrated to 98.4% accuracy
- Week 4: Reached 99.0%+ at 25k/week
- Week 6: Full throughput at 50k/week
- Week 8: Steady state at 99.2% accuracy
Frequently Asked Questions
Common questions about our AI data annotation services for humanoid robots.
- What types of data annotation does SHIRO provide for humanoid robots?
- SHIRO provides image annotation (bounding box, polygon, keypoint, semantic segmentation), video annotation with temporal tracking, 3D point cloud labeling from LiDAR scans, sensor fusion tagging across camera-LiDAR-radar-IMU, and NLP plus gesture annotation for human-robot interaction models.
- What accuracy rate does SHIRO guarantee for AI training data annotation?
- SHIRO guarantees 99%+ annotation accuracy through a multi-tier QA process: automated geometric validation, inter-annotator agreement scoring, and a senior reviewer consensus layer. Our case studies document 99.2% accuracy across 1.2 million annotated images.
- How does SHIRO handle data security for proprietary robotics datasets?
- SHIRO operates under strict NDAs with SOC 2-ready processes. We offer air-gapped annotation environments, role-based access controls (RBAC), encrypted data transfer, and compliance with GDPR and India's DPDP Act 2023. Your proprietary datasets and IP are fully protected.
- How quickly can SHIRO scale annotation teams for large robotics projects?
- SHIRO can scale from 10 to 500+ trained annotators within 2 weeks. Our Mysore facility maintains a bench of pre-trained annotation specialists who can be onboarded to new robotics projects with minimal ramp-up time.
- What is the typical turnaround time for a data annotation pilot project?
- A typical pilot takes 1-2 weeks: Week 1 covers discovery, taxonomy creation, and tool setup. Week 2 delivers 500-1,000 annotated sample assets for your review. Full production ramp-up follows within 3-4 weeks after pilot approval.
- Does SHIRO support 3D point cloud labeling for humanoid robots specifically?
- Yes. 3D point cloud labeling for humanoid robots is our flagship capability. We annotate raw LiDAR scans with 3D cuboids (including heading and velocity), point-level semantic segmentation, multi-frame temporal tracking, and cross-sensor alignment between LiDAR and camera data.
How We Work
Discovery & Scoping
We analyze your data types, annotation requirements, quality standards, and delivery timelines to create a detailed project plan.
Pilot Annotation
We annotate a representative sample of your data so you can validate quality, taxonomy, and edge-case handling before full production.
Team Training
Our annotators are trained on your specific guidelines, ontology, and quality rubric with ongoing calibration sessions.
Production & QA
Full-scale annotation with multi-tier quality assurance: automated checks, human spot-checks, and consensus voting for ambiguous cases.
Delivery & Iteration
Annotated datasets delivered in your preferred format with detailed metrics. Continuous feedback loops to improve accuracy over time.
What Our Clients Say
“SHIRO transformed our annotation operations. Their team delivered consistently high-quality work that exceeded our expectations and directly improved our model performance.”
-- VP of Operations, US Technology Firm
Ready to accelerate your robotics operations?
Contact us for a free annotation pilot and discover how SHIRO can accelerate your embodied AI training data pipeline.
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