practice / data · ai training data

AI training data. Made by people, proven per item.

eeko builds production AI for regulated enterprises, and the models under those systems keep running out of data nobody has published. So we source it. Custom datasets, expert annotation, and recorded real work from consenting people, with a cryptographic fingerprint, a consent record, and a signed provenance record on every item. Nothing scraped, ever.

Consent on every item Expert-checked Licensed in writing Pilot before volume
Hero image · 840 × 1050
first reply
1day
a data lead, not an autoresponder
modalities
7kinds
text, image, audio, video, 3D, documents, robotics
export formats
6fmt
JSON Lines, CSV, Parquet, WebDataset, COCO, Croissant
scraped items
0ever
a release or a licence behind every item

What is AI training data?

AI training data is the body of examples a model learns from: text, images, audio, video, 3D geometry, documents, and robot episodes, each paired with the labels, rankings, or outcomes that tell the model what a good result looks like. A model's ceiling is set by those examples. Train on scraped web pages and you get the average of the web. Train on what a radiologist, a litigator, or a master electrician actually does, and the model learns something the web never wrote down.

Most training data on the market has three defects. Nobody can say where it came from. Nobody asked the people in it. And a growing share was produced by another model, so the new one inherits the old one's mistakes. For a bank, a hospital, or a law firm, each defect is a question counsel will eventually ask.

eeko's data practice exists because we hit that wall ourselves. We build enterprise AI agents and RAG systems for regulated companies, and the models behind them need examples that live in no public corpus. So we built the supply: the eeko human data network of credential-checked experts, paid capture programs for skilled workers, and a licensing catalogue for creators and companies. Every item carries a verifiable record. Every person was paid. Every licence is in writing.

Practice overview image · 2100 × 900
From a written brief to a signed receipt: one pipeline for every modality, with the proof built as the data moves through it.

Who the data practice is for.

AI teams need data. Experts and workers can make it. Owners already hold it. We vet everyone, match each brief to the right people, and keep the record that proves permission on every item.

01 / ai teamsBUY
Labs, robotics companies, and enterprise ML teams
Tell us the capability and where your data falls short. We write the spec, source or commission the data, verify each item, and deliver it licensed. Start with training data for AI teams or send a dataset request.
  • Custom datasets to a written spec
  • Annotation of your data or ours
  • Standing orders as you scale
02 / experts & workersEARN
Specialists and skilled workers, paid for their judgment
Physicians, attorneys, engineers, and linguists take expert data annotation jobs in their own field at a rate shown before they accept. Tradespeople, nurses, mechanics, and office workers get paid to train AI by recording the job they already do.
03 / data ownersLICENSE
Creators, studios, companies, and homeowners
Hold work or records worth learning from? You set the price and terms. Creators license their work for AI through the eeko creator catalogue, companies sell company data, and anyone can list data for licensing for a person to review.
  • Your price, your terms, your call on exclusivity
  • Consent recorded per item
  • Paid per licence

Human-made training data, for every stage of the model.

Nine deliverables, one standard: identical intake, identical checks, identical signed delivery. The full list is under training data solutions.

01 / customCORE
A dataset that does not exist yet, built to your spec, acceptance bar and licence agreed up front.
02 / annotationCORE
Labels, captions, transcripts, and rubric scores from verified experts, author recorded on every label.
03 / captureFIELD
Egocentric video from workers on shift, screen recordings, teleoperation episodes, and consented voice.
04 / sftCORE
Demonstrations and reasoning traces written by practitioners and checked by a second specialist against your rubric.
05 / rlhfCORE
Comparisons judged by people qualified to say which answer is correct, not merely which one reads well.
06 / evalCORE
Unpublished, held-out test sets, so the benchmark measures capability rather than memorization.
07 / safetySAFETY
Adversarial prompts and graded responses from specialists who know what harm looks like in their domain.
08 / roboticsEMBODIED
Manipulation episodes from trained operators: joint states, wrist and scene video, and reviewed success labels.
09 / licensingCORE
Existing corpora, archives, and media from the catalogue, licensed per use with the term and exclusivity you need.

Seven kinds of data, one bar for all of them.

Whatever the model perceives, the intake is identical: fingerprint, origin check, consent, review, signature, receipt.

Modalities image · 1200 × 900
Speech, image, video, 3D, documents, text, and robot episodes, all shipped with the same record attached.

What we source, by modality

  • Speech and audio — released recordings, verbatim transcripts, phonetic labels.
  • Images — camera originals with releases, origin checks, and expert captions.
  • Video — first-person, instructional, and scene footage with per-frame hashes.
  • 3D and CAD — scans, meshes, and drawings with units.
  • Documents and records — contracts, filings, and tables, scanned and masked for personal data.
  • Text, reasoning, and robotics — practitioner-written demonstrations, multilingual sets, and teleoperation streams.

From a brief to a dataset, and the next one after it.

Most vendors sell what is in stock. We start from what the model needs, go and get it, and stay on as the need changes.

STEP 01
Brief and spec
You describe the capability, the failure modes, and the bar to clear. We return a written spec: what, how much, how good, under which licence. Nothing is sourced until you sign it.
STEP 02
Source and pilot
We match the spec to catalogue owners who hold suitable work and to the experts and workers who can make what is missing. A pilot batch reaches you before anything scales.
STEP 03
Verify
Fingerprint, origin check, duplicate check, safety and personal-data screen, second-expert review, then the consent record and signed provenance are bound to the item.
STEP 04
Deliver and repeat
Licensed and documented, in the format your pipeline reads, with a signed receipt naming each item and its hash. A standing order keeps matching work coming.

What travels with every item.

Verification is not a sticker applied at the end. It is a record built step by step, from intake to receipt. An illustrative record for one audio file:

// item-4k7q.record batch.log audit.chain
tail -f
00:00 INTAKE File received from a verified speaker. Exact SHA-256 computed, acoustic fingerprint generated.audio/wav · 4 min 12 s · supplied kit HASHED
00:01 ORIGIN Metadata and embedded credentials inspected for generator signatures and digital-source-type fields. None found.EXIF/XMP · IPTC · content credentials HUMAN
00:02 CONSENT Speaker release and AI-training permission bound to the item. Licence scope: training and evaluation, 12 months.release ref attached BOUND
00:05 SCREEN Block-lists and safety classifier clear. One phone number in the transcript masked.masking logged MASKED
02:40 REVIEW Transcript and phonetic labels written by a linguist, checked by a second.2 passes · label source recorded REVIEWED
02:41 SIGN Provenance record signed with the eeko registry key, appended to the hash-chained audit trail, hash anchored to a public timestamp.Ed25519 · OpenTimestamps SIGNED
02:42 DELIVER Added to the order. The signed receipt lists it by ID and hash.WebDataset shard · Croissant card RECEIPTED

The method, layer by layer, is on the verified human data page.

Expert data annotation by people who practice the field.

Frontier models are short of judgment, not compute. We pay specialists well to supply it. See AI training experts by field.

Radiology expert image · 800 × 1000
Radiology — imaging labels and reads from board-certified radiologists.
Contract law expert image · 800 × 1000
Contract law — clause extraction and risk grading from practicing attorneys.
Teleoperation expert image · 800 × 1000
Teleoperation — manipulation episodes from trained operators.

Credential-checked, by field

Licenses, degrees, and work history are verified before an expert sees a task, and each expert is only shown work in the field we verified. Sixteen fields, from clinical medicine to software architecture and music theory.

Rate shown before you accept

Every gig lists its field, pay, and time commitment up front, and payouts run automatically once identity and tax details are confirmed. Already on another data platform? Try the beat-your-rate offer.

Second-expert review

An agreed share of every batch is independently checked by a second specialist, and labels are marked by source: expert-reviewed, creator-stated, or model-suggested. Ready to join? Apply as an expert.

Recorded real work from the people who do it every day.

Some capabilities cannot be written down. They have to be watched. Our capture programs pay skilled workers to record real shifts to a written protocol.

Capture program image · 1200 × 900
A head-mounted camera on a working electrician: the gaze, the grip, the test, and the moment the job is called done.

Sixteen programs, one protocol

Pay runs from $12 to $30 per accepted hour by program, kit supplied. Homeowners in Minneapolis, Chicago, and Miami can get a free home service in exchange for letting the tradesperson record the visit. The list is under get paid to train AI; the method is on the data capture page.

Delivery image · 2100 × 900
Shipped the way your pipeline already reads data, with a receipt that names each item and the hash to check it against.

AI training data questions.

What is AI training data?

AI training data is the body of examples a model learns from, paired with the labels, rankings, or outcomes that define a correct result: text, images, audio, video, 3D geometry, documents, or recorded robot episodes. A model cannot outgrow its examples, so what matters is who made each one, whether they agreed, whether a qualified person checked it, and whether you can prove all of that later.

How much does custom AI training data cost?

Price follows the modality, the expertise involved, the volume, the licence term, and whether you want exclusivity. Catalogue items carry the price the owner set. Commissioned work is quoted against a written spec after a scoping call, always fixed scope and fixed price, and a paid pilot batch comes first so you can judge the data on your own model before buying volume.

Is human-made training data legal to use commercially?

Everything we deliver is licensed in writing for the uses you name, with the term and exclusivity you choose. Each item is tied to a release or a licence from whoever holds the rights, and items showing identifiable people are offered only once their permission for AI training is recorded. Licence, consent reference, and item hash travel together, so permission can be shown per item, not just per dataset.

Do you annotate data we already have?

Yes. Send us text, documents, images, video, audio, 3D files, or robot episodes and we label them to your rubric. Work that needs a specialist goes to a verified one in that field, so clinical notes are labeled by clinicians and contracts by attorneys. Every label names its author, a second expert checks an agreed share, and the set comes back in your pipeline's format with a signed receipt.

How do I get paid to train AI with eeko?

Two routes. Domain experts browse the open AI training gigs, which show the field, the pay, and the time commitment before you apply, or join the expert network and get invited when matching work opens. Skilled workers in trades, care, kitchens, warehouses, and offices join a capture program and earn twelve to thirty dollars per accepted hour recording the job they already do.

Can my company sell or license its data for AI training?

Yes. List the recordings, documents, records, or media your company holds, state who owns the rights and whether the people in it consented, and set your price and licence terms. A person at eeko reviews every listing before any buyer sees it, personal data is masked before delivery, and you are paid per licence. Individual creators license their work the same way through the creator catalogue.

How quickly can you deliver a dataset?

A data lead answers every request inside one business day with the questions we need resolved and an initial sourcing plan. A written spec usually follows within days, and a pilot batch ships before any production volume. Catalogue items can ship once the licence is signed; commissioned expert work and capture projects take longer because real people have to do real work.

Tell us what the model needs to learn.

Send a dataset request in five minutes, or book a thirty minute briefing. A data lead replies inside one business day with the questions we need answered and a first sourcing plan. No deck. A spec, a pilot, and a price.

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)