practice / data · data capture

Data capture for AI training. Real work, recorded the way a model needs it.

Some things a model needs to learn have never been written down. They happen on a job site, in a kitchen, at a bedside, inside a spreadsheet. eeko puts a camera, a screen recorder, or a teleoperation rig on the people who do that work, records it to a written protocol with consent from everyone involved, reviews every episode, and delivers it licensed with a signed record on each file.

Six capture methods Consent before capture Reviewed episode by episode Receipt by hash
Hero image · 840 × 1050
capture methods
6ways
camera, screen, teleoperation, voice, expert, sensor
worker pay
$12–30/hr
per accepted hour, by program
recordings before consent
0ever
worker, employer, and anyone on site
first reply
1day
with a draft protocol, not a brochure

What is data capture for AI training?

Data capture for AI training is the deliberate recording of real activity so a model can learn from it: a plumber's hands and eyes as they sweat a joint, an accountant's clicks as they close the month, an operator's commands as a robot arm picks a part, a nurse's voice as they hand over a shift. The recording is paired with labels that mark what was happening and when, and with consent from everyone who appears in it.

It differs from scraping or buying stock footage in every way that matters. The task is chosen in advance to match the capability being trained. The people are the ones who actually do the work, on their normal shift, not performers on a set. Variation comes from real conditions and from a protocol that asks for it. And because we arrange the recording, we can prove where every frame came from and that the person in it agreed.

eeko runs capture because the agents and robotics systems we build keep needing it. Egocentric footage teaches embodied models how a task unfolds. Screen recordings teach computer-use agents how work moves between applications. Teleoperation episodes are the raw material of robotics training data. None of it exists on the open web, and none of it should be taken without asking. The recordings come from our paid capture programs and from the specialists in the eeko human data network.

Capture pipeline image · 2100 × 900
Protocol, consent, recording, review, delivery. The same path for a dozen electricians on cameras and for a thousand hours of bookkeeping on screen.

Six capture methods, each run by the people who do the work.

Every method follows a written protocol, is checked against it before volume, and is reviewed before it reaches you.

01 / egocentricFIELD
Egocentric video
Tradespeople, cooks, caregivers, mechanics, and warehouse and farm workers wear a compact head- or chest-mounted camera for a normal shift. The footage carries the worker's own viewpoint: gaze, grip, tool choice, the check before moving on.
  • Worker's-eye video, labeled by task and phase
  • Hands and tools annotated, release on file
  • From the capture programs
02 / screenAGENTS
Screen and workflow recording
Bookkeepers, support agents, designers, and office staff record only the applications they pick, while doing their actual job. No camera. This is how a computer-use agent learns the real route through the tools people use all day.
  • Video plus a click, keystroke, and window log
  • Task edges marked, personal fields masked
  • See the screen-work program
03 / teleopROBOTICS
Robot teleoperation
Trained operators drive arms and mobile manipulators through a task protocol that fixes initial conditions, object sets, permitted strategies, and success criteria, so episodes compare cleanly across operators and sessions.
  • Joint and end-effector trajectories with commands
  • Wrist and scene cameras, pass or fail per episode
  • Detail under teleoperation data
04 / voiceAUDIO
Voice and conversation
Voice talent, call handlers, and linguists capture read and spontaneous speech, support calls, and dialogue across languages in ordinary rooms, with each participant's release recorded before the first take.
05 / expertEXPERTS
Expert demonstrations
Physicians, attorneys, engineers, and scientists work through tasks posted as AI training gigs: writing and grading answers, reasoning step by step, comparing outputs, reviewing peers, all in their own field at a rate they saw before accepting.
  • Demonstrations, preference pairs, rubric scores
  • Evaluation sets, second-expert reviewed
  • Join via apply as an expert
06 / sensor3D
Sensor and environment capture
When video is not enough we add what the task demands: depth and 3D scans of spaces and objects, tactile and force channels on robot hardware, vehicle and equipment telemetry, all time-aligned to the camera streams.
  • Depth maps, point clouds, meshes
  • Force, tactile, and telemetry aligned to video
  • See 3D and CAD datasets

Screen recording training data for computer-use agents.

An agent that has to work inside an ERP, a ticketing queue, or a design tool learns fastest from people who already do. We record them, carefully.

Screen capture image · 1200 × 900
Only the chosen applications are captured. Clicks, keystrokes, and window changes are logged beside the video, and personal fields are masked before anyone reviews it.

What a screen session gives the model

  • The route — which application opens first, what gets copied where, which report is checked before the entry is posted.
  • The events — every click, keystroke, scroll, and window switch, timestamped against the frames.
  • The boundaries — where one task ends and the next begins, marked by the worker and confirmed in review.
  • The exceptions — the moment a value does not match and a person goes looking, which is the behavior an agent most needs to copy.

Programs run for bookkeepers and office workers, customer support agents, and designers and editors. The result feeds the same computer-use work we do under enterprise workflows.

Consent before capture

Nothing records until the worker, their employer, and anyone likely to be on site have agreed in writing. Each release is tied to the specific episodes it covers, not to a project in general.

Real shifts, not staged ones

People record the job they already have, during hours they already work. Variety comes from the protocol asking for it and from the day going the way days go, not from a script.

Masked by default

Anything in frame that is not the task, whether faces, other screens, or paperwork, gets blurred. Personal fields in screen video get masked. Location metadata is removed at intake and never reaches a buyer.

Twelve electricians, four weeks, one protocol.

An illustrative run of an egocentric capture project for a model learning residential electrical work. Every episode on the record.

// capture-elec-07.log consent.log review.log
tail -f
day 01 PROTOCOL Capture protocol v1 signed: panel work, outlet and switch replacement, troubleshooting. Required viewpoint, variations, and the definition of a complete episode written down.12 tasks · 3 variation axes · acceptance per episode SIGNED
day 03 CONSENT Twelve electricians from the skilled-trades program verified. Employer agreements and customer notices in place for scheduled jobs.identity and licence checked · releases bound to job IDs CLEARED
day 08 PILOT First 40 episodes checked against the protocol. Two workers asked to re-angle the camera; one task definition tightened in protocol v1.1.37 accepted · 3 re-recorded · pilot sample sent to buyer ADJUSTED
day 12 RECORD Volume capture under way. Each upload fingerprinted and frame-hashed at intake; faces of bystanders and unrelated screens blurred automatically, then spot-checked.accepted hours paid weekly RECORDING
day 24 REVIEW Every episode reviewed for protocol adherence and completeness. Task and phase boundaries labeled; hand and tool annotations added on the agreed subset.412 accepted · 29 rejected with reasons returned to workers LABELED
day 27 DELIVER Accepted set delivered as WebDataset shards with a Croissant card, consent references, a signed provenance record per file, and a receipt listing each file by hash.standing order opened for a second cohort SHIPPED

How a capture project runs, start to finish.

Four steps, fixed scope, fixed price, with a pilot before volume. A data lead replies to every request inside one business day.

STEP 01
Brief and protocol
You name the capability. We draft the capture protocol: the people, the tasks, the required view, the variations, and the test for a complete episode. Usually back to you within days.
STEP 02
Recruit and consent
Participants come out of our capture programs and the eeko expert network. We check identity and credentials, then gather written consent from the worker, the employer, and any customer who may be in frame.
STEP 03
Record
Workers record real shifts with the kit we send, or in the apps they already use. Early sessions are graded against the protocol; volume starts only after they pass. Pay is $12 to $30 per accepted hour, by program.
STEP 04
Review and deliver
Every episode is reviewed, out-of-scope material is masked, every file gets a fingerprint, and the accepted set ships labeled, with a signed provenance record and a hash-by-hash receipt, as WebDataset, Parquet, or JSON Lines.

Real workers, paid for real hours.

Sixteen capture programs cover the jobs a model most needs to watch. Each pays per accepted hour, supplies the kit, and handles consent.

Egocentric capture image · 800 × 1000
Egocentric — cooks, trades, mechanics, caregivers.
Teleoperation image · 800 × 1000
Teleoperation — trained operators on your hardware or ours.
Voice capture image · 800 × 1000
Voice — support agents and linguists in real acoustic conditions.
Capture kit image · 1200 × 900
The kit we ship: a small camera, a mount, a charger, and, when the protocol asks for it, a depth sensor. Nothing for the worker to buy.

Three ways in

Data capture questions.

Who does the recording in a data capture project?

Working people, not actors. Camera and screen footage comes from our capture programs: electricians, cooks, nurses, mechanics, warehouse staff, bookkeepers, and others, paid by the accepted hour, recording a shift they were working anyway. Teleoperation episodes come from trained operators. Expert demonstrations are written by specialists from the eeko expert network, each verified in their field before they see a task.

Can we control exactly what gets recorded?

Yes. Each project opens with a written capture protocol: which tasks, which viewpoint, which variations to cover, what the frame or screen must include, and what counts as a complete episode. Our team grades the opening sessions against that protocol before volume recording starts, and you approve sample episodes before the project scales. Changes to the protocol are versioned so later episodes can be told apart from earlier ones.

What equipment is used for egocentric and screen capture?

For first-person video we ship a compact head- or chest-mounted camera, and add a depth sensor when the protocol needs geometry. Screen work uses our recorder, which captures only the applications the worker has chosen and logs clicks, keystrokes, and window changes alongside the video. Teleoperation runs on your robot hardware or on ours, decided during scoping. Workers never pay for kit.

How are customers, patients, and bystanders handled in recordings?

Consent comes before capture, from the worker, the employer, and anyone likely to appear, including customers on site. Before review, faces and any screens or paperwork unrelated to the task are blurred, personal fields in screen video are masked, and location metadata is removed at intake. Clinical and care settings are recorded only where the facility and every person involved has agreed in writing. Recordings showing identifiable people are offered only with that consent on file.

Can eeko run a capture project inside our own company?

Yes. Your staff enroll together. eeko manages consent for each participant and pays every accepted hour, and you can take an exclusive licence on the result or, with your permission, let other buyers license it for a share of the fee. If your company already holds years of recordings, call logs, or records, see our sell your data page instead; that route needs no new recording at all.

What does a finished data capture project deliver?

Accepted episodes with the labels in your spec, such as task and phase boundaries, hand and tool annotations, or click and keystroke events, together with technical metadata, the consent references, and a signed provenance record for each file. It ships as WebDataset shards, Parquet, or JSON Lines pointing at the media, with a Croissant dataset card describing the set and a signed receipt listing every file by hash.

How much does a data capture project cost?

It depends on the method, the number of accepted hours, how specialised the people are, the labeling depth, and the licence. Worker pay runs from twelve to thirty dollars per accepted hour by program and is passed through transparently, with protocol design, review, masking, labeling, and delivery priced on top. Every project is quoted fixed scope and fixed price against the written protocol, and a small pilot batch comes before volume so you can check the footage in your own pipeline first.

Show us the task. We will go and record it.

Five minutes to send a request. A data lead replies inside one business day with a first draft of the protocol, a sourcing plan, and a fixed price for a pilot batch. No deck. A protocol and a date.

Experienced within

  • SOC 2 Type II
  • ISO 27001
  • HIPAA
  • HITRUST r2
  • ISO 27701
  • PCI DSS
  • NIST CSF 2.0
  • CMMC
  • FedRAMP
  • GDPR

Markets served.

As an enterprise AI agency, eeko systems delivers production AI systems remote-first across the United States and internationally — including these markets:

New York City, New York (NY)

Los Angeles, California (CA)

Chicago, Illinois (IL)

Houston, Texas (TX)

Phoenix, Arizona (AZ)

Philadelphia, Pennsylvania (PA)

San Antonio, Texas (TX)

San Diego, California (CA)

Dallas, Texas (TX)

San Jose, California (CA)

Austin, Texas (TX)

Jacksonville, Florida (FL)

Fort Worth, Texas (TX)

Columbus, Ohio (OH)

Charlotte, North Carolina (NC)

Indianapolis, Indiana (IN)

San Francisco, California (CA)

Seattle, Washington (WA)

Denver, Colorado (CO)

Washington, District of Columbia (DC)

Boston, Massachusetts (MA)

El Paso, Texas (TX)

Nashville, Tennessee (TN)

Detroit, Michigan (MI)

Oklahoma City, Oklahoma (OK)

Portland, Oregon (OR)

Las Vegas, Nevada (NV)

Memphis, Tennessee (TN)

Louisville, Kentucky (KY)

Baltimore, Maryland (MD)

Milwaukee, Wisconsin (WI)

Albuquerque, New Mexico (NM)

Tucson, Arizona (AZ)

Fresno, California (CA)

Sacramento, California (CA)

Kansas City, Missouri (MO)

Atlanta, Georgia (GA)

Miami, Florida (FL)

Colorado Springs, Colorado (CO)

Raleigh, North Carolina (NC)

Omaha, Nebraska (NE)

Long Beach, California (CA)

Virginia Beach, Virginia (VA)

Oakland, California (CA)

Minneapolis, Minnesota (MN)

Tulsa, Oklahoma (OK)

Arlington, Texas (TX)

New Orleans, Louisiana (LA)

Wichita, Kansas (KS)

Cleveland, Ohio (OH)

Tampa, Florida (FL)

Bakersfield, California (CA)

Aurora, Colorado (CO)

Honolulu, Hawaii (HI)

Anaheim, California (CA)

Santa Ana, California (CA)

Corpus Christi, Texas (TX)

Riverside, California (CA)

Lexington, Kentucky (KY)

St. Louis, Missouri (MO)

Stockton, California (CA)

Pittsburgh, Pennsylvania (PA)

Saint Paul, Minnesota (MN)

Cincinnati, Ohio (OH)

Greensboro, North Carolina (NC)

Anchorage, Alaska (AK)

Plano, Texas (TX)

Lincoln, Nebraska (NE)

Orlando, Florida (FL)

Irvine, California (CA)

Newark, New Jersey (NJ)

Toledo, Ohio (OH)

Durham, North Carolina (NC)

Chula Vista, California (CA)

Fort Wayne, Indiana (IN)

Jersey City, New Jersey (NJ)

St. Petersburg, Florida (FL)

Laredo, Texas (TX)

Madison, Wisconsin (WI)

Chandler, Arizona (AZ)

Buffalo, New York (NY)

Lubbock, Texas (TX)

Scottsdale, Arizona (AZ)

Reno, Nevada (NV)

Glendale, Arizona (AZ)

Gilbert, Arizona (AZ)

Winston-Salem, North Carolina (NC)

North Las Vegas, Nevada (NV)

Norfolk, Virginia (VA)

Chesapeake, Virginia (VA)

Fremont, California (CA)

Garland, Texas (TX)

Richmond, Virginia (VA)

Baton Rouge, Louisiana (LA)

Boise, Idaho (ID)

San Bernardino, California (CA)

Spokane, Washington (WA)

Des Moines, Iowa (IA)

Modesto, California (CA)

Birmingham, Alabama (AL)

Tacoma, Washington (WA)

Fontana, California (CA)

Oxnard, California (CA)

Fayetteville, North Carolina (NC)

Huntsville, Alabama (AL)

Moreno Valley, California (CA)

Rochester, New York (NY)

Glendale, California (CA)

Yonkers, New York (NY)

Augusta, Georgia (GA)

Amarillo, Texas (TX)

Little Rock, Arkansas (AR)

Akron, Ohio (OH)

Shreveport, Louisiana (LA)

Grand Rapids, Michigan (MI)

Mobile, Alabama (AL)

Salt Lake City, Utah (UT)

Huntsville, Texas (TX)

Tallahassee, Florida (FL)

Overland Park, Kansas (KS)

Knoxville, Tennessee (TN)

Worcester, Massachusetts (MA)

Brownsville, Texas (TX)

New Port Richey, Florida (FL)

Jackson, Mississippi (MS)

Providence, Rhode Island (RI)

Fort Lauderdale, Florida (FL)

Sioux Falls, South Dakota (SD)

Tempe, Arizona (AZ)

Cape Coral, Florida (FL)

Springfield, Missouri (MO)

Pembroke Pines, Florida (FL)

Eugene, Oregon (OR)

Peoria, Arizona (AZ)

Corona, California (CA)

Lancaster, California (CA)

Rockford, Illinois (IL)

Salinas, California (CA)

Palmdale, California (CA)

Springfield, Massachusetts (MA)

Charleston, South Carolina (SC)

Duluth, Minnesota (MN)

London, England (ENG)

Dublin, Ireland (IRE)