High-quality, trainable, compliance-traceable multi-modal robotics datasets for embodied foundation models and humanoid robot vendors — professional capture teams plus end-to-end data security controls, so your model training is never blocked by data.
The bottleneck for embodied-intelligence model training stopped being algorithms long ago — it's data. But most teams end up with data that's task-inconsistent (operators following their gut), temporally misaligned (clock drift across multi-camera feeds, robot state, and force sensors), or impossible to audit (no clear record of source, site, or de-identification). No amount of algorithmic improvement can make up for this, and it drags down the entire iteration cycle.
EVST breaks embodied data services into two hard commitments: (1) Capture-team expertise — our capture engineers come from EVST's years of industrial robotics production-line integration experience. They understand robot kinematics, cycle time, and task decomposition, so the data they collect reflects standardized motion, not random button-pressing. (2) End-to-end data security — from physical isolation at the capture site, to encrypted transmission channels, to role-based access control and audit trails on the platform, every step is transparent and auditable. You don't receive a pile of raw bag files — you receive training-ready, compliance-traceable datasets.
A capture-engineer team with industrial robotics production-line integration backgrounds. Familiar with robotic-arm kinematics, task decomposition, and production cycle time. Multiple capture modalities supported — teleoperation, VR teaching, motion capture, and human-video imitation — adapted to different embodied foundation-model training needs.
Our in-house data-processing platform covers three alignment capabilities: clock, spatial, and semantic. Supports multi-granularity auto-slicing at the episode / subtask / skill level. Dual-layer labeling with VLM auto-annotation plus human review, producing mainstream trainable formats including LeRobot, HDF5, and Open X-Embodiment.
From physical access control at capture sites, to encrypted transmission channels, to platform-level RBAC and full operation logging — every step is auditable by the customer. Private deployment is supported, so data in sensitive scenarios never leaves the customer's internal network.
Multi-dimensional quality scoring (0–100) across sensor completeness, temporal smoothness, label confidence, and more. A full dataset quality report is produced before delivery, with sub-standard segments clearly flagged and traceable — preventing training data contamination.
Large-scale multi-modal data for training embodied foundation models — VLA (Vision-Language-Action), world models, diffusion policy models — covering general manipulation tasks like grasping, placing, assembly, and bimanual coordination.
Targeted data capture and fine-tuning dataset production for customer-specific embodiments (humanoid / wheeled / quadruped) and specific task scenarios. Supports customer-defined task lists and evaluation metrics.
Leveraging EVST's industrial robotics production-line resources to provide embodied data from real industrial scenarios — welding, assembly, machine tending, quality inspection. These are scarce scenario resources that pure data companies can't replicate.
For customers who have data but whose quality falls short, we provide alignment repair, re-slicing and re-labeling, compliant de-identification, and quality scoring — turning "unusable data" into "trainable data."
Two core differentiators. (1) Capture-team background — we aren't temporary workers hired for the project. Our team comes from EVST's years of industrial robotics production-line integration work. They understand robotic arms, process craft, and task decomposition, so the data they collect is naturally stronger on task consistency and physical plausibility. (2) Industrial scenario access — leveraging EVST's production-line resources in automotive parts, construction machinery, rail transit, and other heavy-industry settings, we deliver embodied data from real production lines — a scarce resource pure data companies can't reach.
Four layers of protection. Physical layer — the capture site supports customer on-site supervision, and equipment can be operated at a customer-designated location. Transmission layer — all data transmission is encrypted and never transits the public internet. Platform layer — RBAC permissions, full logging of data access, and independent customer audit. Delivery layer — NDAs and data-processing agreements are signed by default, spelling out ownership, usage boundaries, and destruction terms. For sensitive projects, fully on-premise deployment is available so data never leaves your internal network.
Our in-house processing platform runs quality assessment at every step — sensor completeness (dropped frames, latency), temporal alignment precision, trajectory smoothness, label confidence, and more, combined into a 0–100 score. Every episode carries its own quality label; sub-standard segments are clearly marked and traceable back to the capture source. A full dataset quality report is delivered, so customers can filter by quality score and avoid contaminating the training pipeline.
