Warehouse Picking Robots: What Your Training Data Strategy Is Missing
Warehouse robots underperform in production not because of the model, but because training data missed the edge cases that matter.
Teleoperation, annotation, and evaluation programs — scoped, staffed, and running in four weeks. Built for embodied AI teams that need data, not vendors.
Every trajectory, frame, and label belongs to you. Your data never trains another client’s model.
VR, exo, and bilateral leader-follower rigs. Sub-10ms latency, 30Hz joint logging.
Egocentric video, hand pose, gaze tracking, and force gloves for VLA pre-training.
Synchronized RGB-D, lidar, IMU, tactile, and audio. Microsecond alignment.
Action segmentation, affordance masks, language captions, reward signals.
Isaac and MuJoCo scene generation, domain randomization, and sim-to-real bridging.
Held-out test sets, scenario libraries, and scoring infrastructure for model release.
Targeted collection for failure modes identified from your production model logs.
Trained, vetted operators in your studios. Maximum IP control. Best for surgical, autonomous, and high-stakes verticals.
Per FTE-month
Distributed operator network for scene diversity and geographic spread. Fast scale-up, lower per-hour rate.
Per task or per hour
Dedicated core for the spine of your dataset, crowdsourced edge for diversity and long-tail. Most production buyers.
Custom SOW
Whole-body trajectories, cross-embodiment data, and dexterous manipulation for bipedal platforms.
Long-horizon tasks in real environments with bimanual platforms like Aloha, Stretch, and Tiago.
Pick-pack-place demonstrations across SKU diversity, packaging variations, and edge case scenarios.
Procedure-grade teleop data with clinician operators. HIPAA-compliant collection and storage.
Six things that separate a Roborax program from a generic data labeling vendor.
Dedicated pods, crowdsource networks, or hybrid programs. Most vendors offer one model. We scope the right fit for your program before contract.
41 delivery centers across India, the Philippines, the US, Canada, the UK, and seven more countries. Scale or specialize by geography without changing vendors.
SOC 2 Type II, ISO 27001, HIPAA, ITAR, CMMC, UK GDPR, DPDP Act 2023. Regulated programs are not exceptions here — they are the default.
Standard ramp from signed SOW to first production batch. Operator recruitment, training, and calibration are built into the timeline, not added to it.
Average 14-month operator tenure on dedicated programs. Consistency within a program is not accidental — it is how we staff and retain.
20,000+ employees across Fusion CX. The operational infrastructure of a global BPO, purpose-built for embodied AI data. Scale on demand without notice.
Trajectories collected
Delivery centers
SOW to first batch
Label accuracy
FROM THE FIELD
Warehouse robots underperform in production not because of the model, but because training data missed the edge cases that matter.
Sub-millimeter precision, HIPAA compliance, and credentialed operators — surgical robot data has requirements general robotics programs cannot meet.
Robotics data quality is not a review meeting. At production scale it is automated validation, per-operator metrics, and same-day feedback loops.
Robot annotation is not image labeling with a new name. Temporal structure and task semantics demand distinct tooling and annotator qualification.
Simulation offers unlimited training data at zero cost. The sim-to-real gap is a structural problem, not a rendering one.
Language models scaled on internet data. Embodied AI must build its data from the physical world — and that changes everything.
Imitation learning and RL demand fundamentally different data. Teams built for one discover the mismatch only when transitioning to the other.
Hardware, environment, and task design can all be controlled. Operator fatigue is the variable that quietly degrades every dataset you collect.
VR teleop and physical demonstration both work — but not equally for every task. The right choice depends on task structure.
A solutions engineer replies within one business day with a
scoped SOW.