— Platform · Delivery APIs
Every dexset dataset ships through delivery APIs with versioning, signed access, and schema mapping — so data lands in your training infrastructure, not in a folder of zip files.
Dataset delivery dashboard
— Capabilities
Each dataset ships as an immutable, versioned release. Reproduce any training run by pinning the exact version it used.
Time-limited signed URLs and access-controlled endpoints for every delivery. No public buckets, no shared links.
Map labels, fields, and metadata to your internal schema once. Every future delivery follows the same contract.
Pull complete datasets or only the clips added since your last sync, keeping pipelines current without re-downloads.
Get notified when a batch passes quality review and becomes available, so training jobs can trigger automatically.
Every transfer is logged with version, recipient, checksum, and timestamp for full traceability and audit.
— In Scope
— Compliance & Trust
From first consent form to final delivery, dexset workflows are built to meet data protection, security, and labor standards across the regions where we capture and the regions where our customers operate.
Every participant is briefed and signs a release before capture begins. Consent records attach to each clip, and withdrawal requests are honored across all delivered versions.
Face blurring, anonymization, and exclusion zones are applied wherever required. We minimize personal data by design and never collect more than the task brief demands.
Footage is encrypted in transit and at rest, with role-based access controls, signed delivery URLs, and per-recipient transfer records on every dataset.
Capture and delivery workflows are designed to align with GDPR and UK GDPR, CCPA/CPRA, PIPL, APPI, and LGPD requirements, with regional data-residency options where needed.
Source, consent, capture, environment, and annotation records persist for every dataset, supporting audits that run from raw footage to the exported training file.
Capture operators, demonstrators, and annotators are fairly paid and work under documented, safe conditions — quality data should never come from exploitative labor.
— What Teams Say
★★★★★
“The egocentric hand-pose labels are the best we have evaluated. Our grasp success rate improved 18% after one fine-tuning round.”
Priya Raman
Manipulation Lead, AI Robotics Company
★★★★★
“Coverage scoring meant we knew exactly what variation we were missing before training, not after burning a GPU budget on it.”
Sofia Almeida
Perception Engineer, AI Robotics Company
★★★★★
“We sent one task brief and got back a dataset that loaded into our pipeline on the first try. Custom schema, zero rework.”
Marcus Chen
ML Infrastructure Lead, Independent Robotics Vendor
— FAQ
Through versioned releases accessible via signed API endpoints or direct cloud-storage transfer. Each release is immutable and checksummed, so any training run can be reproduced by pinning the exact dataset version it consumed.
Yes. Webhooks fire when a batch passes quality review and becomes available, so ingestion and training jobs can start without anyone manually checking for new data.
Yes. After an initial full delivery, your pipeline can pull only the clips and annotations added since the last sync — keeping recurring programs current without repeated full downloads.
Time-limited signed URLs, access-controlled endpoints, and per-recipient delivery records with checksums and timestamps. No public buckets, no shared static links.
Tell us your format and infrastructure. We map the delivery contract before the first capture.