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Better data.
Better models.Built with human insight.

High-quality, ethically sourced datasets engineered for production AI models.

Human-in-the-loopTraceable by designBuilt to your spec
dataset_explorerIllustrative preview
ego_000142
First-person wearable-camera schema illustrationTwo illustrated hands reach toward a component on a workbench. Example field of view is 110 degrees, with synchronized camera and IMU metadata. This is a schematic, not real egocentric footage.action: grasp / demoWEARABLE RGB · HFOV 110° · 1080p / 60 FPSIMU 200 Hz · 6DoF · illustrated capture schema

480

frames / 8-second example

MP4 / JSONL + IMU

Example delivery format

The data layer between your task and a dataset built to spec.

CollectionAnnotationEvaluation

01 / Data for the way you build

Your model is specific.
Your data should be, too.

Specify the data your team needs. We shape the collection, annotation, and evaluation around your requirements.

100%

customizable to your exact needs.

Built strictly to client specifications. Capture settings, hardware, and acceptance criteria are agreed in writing before collection.

Schedule a technical meeting
Resolution & FPS
Your target dimensions and frame rate
Field of view
Optics, angle, and calibration
Sensor setup
RGB, depth, IMU, and synchronization
Hardware configuration
Wearables, mounts, and capture rigs
Industry domain
Your task, environment, and edge cases
Acceptance criteria
Your ontology and evaluation rubric

Video / Inspect the sample

From moving pixels
to useful signals.

Inspect three supplied egocentric industrial clips standardized to 1920 × 1080 at 60 FPS. Scrub, change playback speed, step through frames, and toggle demonstration bounding boxes. The 60 FPS encoding repeats source frames; source recordings are approximately 30 FPS. Inspect drilling, welding arcs, and seam assembly with task-specific metadata tags.

demo_track_01demo_track_02

1080p @ 60 FPS | Egocentric | Hand-Object Interaction | Tool Action Recognition

00:00:00 / 00:00:00
frame 0000 /1185

Egocentric Power Tool Operation & Drilling

Provided footage

Egocentric Video / Hand-Object Interaction

First-person hand tool alignment, drilling, and metal framing assembly.

hand_object_interactiontool_actiondrilling_alignment

Silent, locally served full-length preview. No autoplay or external media request. Playback is normalized to 1080p with source frames repeated to constant 60 FPS. Boxes and schema labels are illustrative, not ground-truth annotations.

Source & license provenance

User-supplied industrial footage: sample1.mp4. The original files remain unchanged. This full-length preview copy is scaled or letterboxed to Full HD, converted to constant 60 FPS by repeating source frames, and stripped of audio. Encoding: H.264 High / Level 4.2, yuv420p, MP4 with fast-start metadata. Posters are extracted from the supplied clips. No third-party license was supplied.

demo_track_01demo_track_02

1080p @ 60 FPS | Industrial CV | Welding Arc Detection | Extreme Contrast

00:00:00 / 00:00:00
frame 0000 /1218

Arc Welding & Spark Tracking

Provided footage

Egocentric Video / High-Intensity Industrial Process

Close-range arc welding footage with dynamic light contrast and particle tracking.

welding_arcspark_trackingextreme_contrast

Silent, locally served full-length preview. No autoplay or external media request. Playback is normalized to 1080p with source frames repeated to constant 60 FPS. Boxes and schema labels are illustrative, not ground-truth annotations.

Source & license provenance

User-supplied industrial footage: sample2.mp4. The original files remain unchanged. This full-length preview copy is scaled or letterboxed to Full HD, converted to constant 60 FPS by repeating source frames, and stripped of audio. Encoding: H.264 High / Level 4.2, yuv420p, MP4 with fast-start metadata. Posters are extracted from the supplied clips. No third-party license was supplied.

demo_track_01demo_track_02

1080p @ 60 FPS | Thermal/Visual | Metal Fabrication | Seam Tracking

00:00:00 / 00:00:00
frame 0000 /1247

Precision Metal Welding & Seam Assembly

Provided footage

Egocentric Video / Precision Manufacturing

First-person perspective of metal seam welding and structural fabrication.

metal_fabricationseam_trackingweld_alignment

Silent, locally served full-length preview. No autoplay or external media request. Playback is normalized to 1080p with source frames repeated to constant 60 FPS. Boxes and schema labels are illustrative, not ground-truth annotations. Thermal/Visual is a task-schema label; thermal-sensor acquisition has not been verified.

Source & license provenance

User-supplied industrial footage: sample3final.mp4. The original files remain unchanged. This full-length preview copy is scaled or letterboxed to Full HD, converted to constant 60 FPS by repeating source frames, and stripped of audio. Encoding: H.264 High / Level 4.2, yuv420p, MP4 with fast-start metadata. Posters are extracted from the supplied clips. No third-party license was supplied.

02 / Collection, annotation, evaluation

A pipeline built
around your problem.

Good data is a process. We connect collection, human annotation, and quality review around the acceptance criteria your model actually needs.

  1. 01

    Define the gaps

    Map the task, coverage requirements, data rights, and acceptance criteria with your ML team.

    OUTPUT / collection specification

  2. 02

    Collect with intent

    Recruit for the right conditions and contributor profiles. Capture consent and source records alongside each sample.

    OUTPUT / traceable raw samples

  3. 03

    Annotate & verify

    Apply your ontology, calibrate reviewers, and resolve disagreements against a shared quality rubric.

    OUTPUT / reviewed annotations

  4. 04

    Evaluate & deliver

    Package the agreed formats, splits, metadata, and version history so your team can inspect every handoff.

    OUTPUT / versioned dataset

03 / Trust at the sample level

Know what goes
into your model.

Ethical sourcing is part of the specification. So are lineage, review decisions, and the details your team needs to evaluate a dataset.

Read our delivery checklist
delivery_manifest.jsonExample
Version
v1.0.0
Source lineage
Per-sample reference
Usage rights
Project agreement
Quality report
Included in scope
Acceptance rubric
Agreed before collection
01

Human judgment in the loop

Task-specific guidelines, reviewer calibration, and an explicit path for ambiguous samples.

02

Rights that travel with the data

Source records, consent requirements, and permitted-use terms defined in the project agreement.

03

Quality you can inspect

Agreed coverage, annotation checks, and acceptance thresholds documented before collection begins.

Project-specific quality targets and licensing terms are confirmed during scoping. Preview counts are illustrative.

Partnerships / A clearer path to useful data

Open to
Data Partnerships

For content creators, platform owners, and enterprise providers: turn content you are authorized to license into a monetized, legal data pipeline. Commercial terms and permitted uses are agreed before collection or transfer.

Our production acceptance standard: 100% legally cleared, ethically acquired, and human-verified data collection. Each delivery must have documented rights, scoped consent, and a recorded human review. This is a delivery requirement, not an independent certification.

Discuss a data partnership

Partnership options / no endorsement implied

Creator partners

Original footage, speech, and specialist content

Ownership evidence · contributor permissions

Platform partners

Permissioned content libraries and recurring pipelines

Licensing chain · permitted-use controls

Enterprise partners

Domain-specific collections and governed data access

Contracted scope · review and audit records

No verified enterprise relationships or performance benchmarks have been supplied. Project-specific evidence is assessed during due diligence.

Prepare a project brief

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A conversation starts here

Contact Us

Discuss a specialized collection, a data partnership, or the technical details your next dataset needs.

Request a technical meeting
teambendata@gmail.com

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