Company

We sell capture programs, not a data lake.

Most egocentric footage on the market was collected without a spec, which is why teams discard around ninety percent of what they buy. Firsthand exists to invert that: fewer hours, captured against a named skill, with supervision attached and a consent chain you can show your counsel.
1,247hours

Validated hours delivered

how we count

Hours that passed sync + QA and shipped to a buyer. Recaptured and rejected hours excluded.

1.12ms

Median cross-stream sync error

how we count

Median absolute timestamp offset between head camera and every other stream, over 12,480 measured frames.

100%

Documented consent

how we count

Every participant signs a written commercial release before capture. Bystanders are de-identified or the clip is discarded.

9days

Median time to first delivery

how we count

Signed spec to first validated batch in your hands. Measured across Spec Pilot engagements.

How we operate

Five commitments that cost us money.

Each of these makes a batch slower or smaller. They are on this page because they are the reason a batch is usable.

Publish the number that could embarrass us
Sync error, reject rates and thin coverage are on the site because a buyer finds all three in week one anyway.
Pay for time, never per task
A bounty per episode optimises for speed and produces footage that fails QA. We pay hourly, including setup and breaks.
Discard rather than downgrade
If a bystander cannot be de-identified, or a session drifts out of calibration, the footage is deleted. It is not sold at a discount.
Say where the alternative wins
Ego4D is broader. EgoScale is larger. EgoDex has excellent hand pose. We publish that alongside our own numbers.
No capture without a spec
Unspecified hours are the reason teams throw away most of the footage they buy. We will not sell them.

What we will not do

The list matters more than the mission statement.

Real patient footage
Clinical capture happens only in training environments with simulated patients.
Covert capture
Every person in a manipulation region has signed a release. No hidden rigs, ever.
Children
No participants under 18, and clips with children in frame are discarded rather than blurred.
Scraped footage
We do not resell web video. Every hour in the catalog was captured by an operator we paid.
Surveillance buyers
We decline programs whose stated purpose is identifying or tracking individuals.

Case study

A bimanual loading policy that kept failing on half-full racks.

Anonymised at the buyer's request: a US humanoid lab, Series B, training a bimanual dishwasher-loading policy. Their footage was clean and their policy still failed the moment a rack was partially occupied.

620hours
Validated hours delivered in 11 weeks
11skills
Named skills in the spec, all cells filled
+21pts
Success rate on their internal dishwasher eval
7.4%
Batch reject rate — recaptured at our cost

The lab had 4,000 hours of public egocentric footage and a policy that scored well in simulation. In the real world it stalled on any rack that was already half loaded, because almost nothing in the public corpora shows a person recovering from a bad grasp inside a cluttered fixture.

We wrote a spec with a hard quota: 15% of every batch had to be a failure and recovery — dropped plate, wrong slot, tine collision — with the recovery captured through to completion. That quota is the whole case study.

Their words, lightly trimmed: “The failure cases were the only part we couldn’t buy anywhere else, and they moved the eval more than the other 500 hours combined.”

A dim multi-monitor QA workstation showing synchronized video tracks on a timeline next to a spreadsheet of measurements.
FIG 3 — QA station. Every batch is reviewed frame-accurate against the accept criteria before it ships. Rejects and their reasons go to the buyer with the batch.

Engagement timeline

  1. WEEK 0Spec written together: 11 skills, 6 kitchens, explicit failure-case quota of 15%
  2. WEEK 1Rig calibration on their object set — 34 SKUs of real crockery shipped to us
  3. WEEK 2First 50 h batch delivered in RLDS. They found a wrist extrinsics error. We recaptured 12 h.
  4. WEEK 4Cadence at 70 h/week. Coverage report per batch with the reject log attached.
  5. WEEK 11620 h delivered. Failure cases turned out to be the highest-value slice.

Anonymised with permission. Reference call available under NDA once a spec is scoped.

Company facts

The boring details.

Entity
Firsthand Data, Inc. — Delaware C-corp
Operating model
In-house capture ops, contracted operators, no capture subcontractors
Team
Robotics data engineering, capture operations, annotation review
Security
SOC 2 Type II in audit; delivery over signed URLs, per-org isolation
Contact
hello@ifirsthand.com

We are a small team by design. Capture operations, QA review and data engineering sit in the same standup, because a reject reason that never reaches the engineer who wrote the ingest check becomes a recurring defect.

If you are an embodied AI team, the fastest way to evaluate us is the free sample pack, then a Spec Pilot against one named skill. If you run capture operations of your own and want to contribute hours, the standards we hold contributors to are published in full.

Press, partnership and research enquiries all reach the same inbox: hello@ifirsthand.com.

Start with the sample, not a call.

Download the pack, read the schema, then bring us a skill you cannot currently train.