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Egocentric video
First-person RGB stream at 1080p / 30fps. The view your robot will eventually see.
stream · rgb_pov · 30fps · h264
Status · taking design partners · Q3 2026
The Data Foundryfor Physical AI.
Custom human-demonstration datasets for robotics teams. Task-specific. Legally clean. Captured by a trained operator network across the Middle East, delivered to your schema in weeks, not quarters.
Task families
0+
Pilot turnaround
0–0wk
Sensor channels
0
Region
MENA → Global
02
// data specification
Robotics-grade signal,
not generic footage.
Every episode ships with synchronized multimodal capture, structured metadata, and a commercial license. Formatted to your pipeline's schema.
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Third-person reference
External-view capture for QA, annotation, and object-state verification.
stream · rgb_third · sync_locked
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Hand pose & IMU
3D hand tracking and wrist inertial data for contact-rich bimanual tasks.
stream · hand_3d + imu_9dof
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Task metadata
Step segmentation, object labels, environment tags, instruction text. All timestamped.
format · json · custom_schema
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Success / failure labels
Curated success episodes plus controlled failure cases for policy evaluation.
label · pass_fail + edge_modes
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Privacy-redacted, licensed
Face / voice / document redaction. Signed consent. Full commercial training rights.
compliance · gdpr_e · pdpl_eg
03
// task families
Where your robot currently fails.
We collect against it.
Four operational task families today. Custom protocols available on request: bring us the spec and we'll scope a pilot.
01 · household
Household Manipulation
Bimanual manipulation across home environments: laundry, dishes, cleaning, organization. The longest-tail task distribution for general-purpose humanoids.
representative tasks
→Folding: shirts, pants, towels, sheets
→Loading & unloading dishwashers
→Wiping counters, tables, mirrors
→Opening drawers, retrieving items
→Sorting laundry & household objects
→Making beds, arranging pillows
04
// operating model
An operational layer
for embodied AI.
Not a marketplace. Not gig labor. A disciplined data pipeline engineered for robot policy training.
01
Fast workforce ramp
Pre-screened operator bench in Egypt, ready to deploy once a SOW is signed. Days, not months, from contract to first batch.
02
Lower cost per hour
MENA labor economics + disciplined operations = approved-hour pricing US-based vendors structurally can't match.
03
Custom task protocols
We don't sell a generic dataset. Every engagement starts with the task your robot fails at, then a protocol designed against it.
04
QA & metadata included
Every episode passes through a multi-tier QA workflow. Metadata is structured, not improvised. Delivered in your schema.
05
Commercial usage rights
Signed operator releases, bystander redaction, environment consent. Data ships ready for training with no procurement-blocking surprises.
05
// design partner program
Start small.
Scale on signal.
Three engagement shapes, designed to de-risk procurement and prove data value before scale. Pricing reflects QA-approved hours.
01 · Feasibility Sprint
Discovery
$10–25k
10–25 approved hours · 2–3 wk
- +3–5 task variants
- +Basic egocentric capture
- +Standard metadata + QA report
- +Consent & rights documentation
- +Delivery in your schema
02 · Full Pilot
TaskPack
$50–250k
100–300 approved hours · 4–8 wk
- +10–20 task variants
- +Multi-view capture (POV + reference)
- +Optional hand pose / IMU / glove
- +Step segmentation + object labels
- +Weekly batched delivery
- +Recollection on QA failures
03 · Retainer
Dedicated Pod
Custom
monthly retainer · exclusive ops
- +Dedicated operator team
- +Customer-exclusive protocols
- +Continuous task expansion
- +Embedded ops & QA leads
- +Data exclusivity options
// 06 · start a conversation
Tell us the task your robot fails at.
Whether you need a 25-hour feasibility check or a dedicated MENA collection pod, the conversation starts the same way: what task, what failure mode, what would prove value.
RESPONSE_SLA< 48h
NDAon request
REGIONglobal delivery
CONTACThello@quivoc.com