Evaluate predicted futures. You have rollouts or generated outcomes but do not trust where they fail or whether a model change improved them.
Human data for actions, outcomes, and what happens next.
Custom human-generated datasets for AI.
Tell us what data your model needs. We design the collection, find and guide the right people, manage quality, and deliver a finished dataset for training, evaluation, or both.
World models. Physical AI. Embodied systems. Simulation. Agents.
01 / WHAT WE DO
The dataset your model needs may not exist yet.
We create custom human-generated datasets that cannot be scraped, simulated reliably, or bought off the shelf. We define the data and protocol, qualify the right people, operate collection or evaluation, control quality, and deliver the finished dataset in an agreed format.
02 / TWO STARTING POINTS
Start with one model decision
Evaluate a future or create the experience that is missing.
Both paths end with an accepted, client-specific dataset—not labor hours, software seats, or access to an undifferentiated crowd.
Create missing human experience. You need demonstrations, interactions, decisions, failures, recoveries, or outcomes that cannot be sourced off the shelf.
03 / PILOT DESIGNS
Three focused offers
Human-created data and evaluation for what happens next.
PILOT / 01
Rollout evaluation
Qualified reviewers locate the first invalid transition in action-conditioned rollouts, classify the failure, assess progress and outcomes, and adjudicate disagreement.
- Failure transitions
- Outcome judgments
- Reusable rubrics
PILOT / 02
Human-created action + outcome data
Qualified people create complete episodes connecting an initial state, action or interaction, resulting state, outcome, and quality status.
- Demonstrations
- Failures + recoveries
- Counterfactuals
PILOT / 03
Synthetic-data acceptance audit
Blinded human review tests whether synthetic or simulated data is physically, causally, behaviorally, and operationally suitable for its intended use.
- Matched comparisons
- Failure classifications
- Acceptance recommendation
Evaluation to training: turn recurring evaluation failures into targeted human-created training data, then test the next model version again.
See how an omelette task becomes structured action-and-outcome training data
04 / CAPABILITIES
Human data for the work your AI needs to do.
Evaluate model behavior, create missing training examples, or build a dataset around your company's workflows.
01 / EVALUATE
Human evaluation
Test voice agents, review robot and human videos, and compare model responses against clear criteria.
Explore evaluation02 / CREATE
Training data & demonstrations
Create targeted examples and capture human actions, decisions, corrections, and outcomes.
Explore training data03 / YOUR COMPANY
Private enterprise datasets
Turn company knowledge, customer conversations, and employee expertise into reviewed datasets for your AI application.
Explore enterprise datasets05 / METHOD
A closed-loop program
Designed around the dataset you need.
Every engagement begins with the model decision the data must support, then works backward to the people, evidence, rights, and controls required.
- 01Define
State what the dataset must capture and how it will be used.
- 02Specify
Define the data unit, protocol, rubric, rights, and acceptance test.
- 03Produce
Qualify the right people and operate collection or evaluation.
- 04Control
Validate, review, adjudicate, reject, retake, and preserve provenance.
- 05Deliver
Provide accepted data, structured metadata, and quality documentation.
The dataset you need may not exist yet
What dataset does your model need?
Tell us what the data should capture, who or what it should represent, and how your team expects to use it. We will help define a bounded pilot and finished delivery.
Email hello@consequencelabs.com or call 941-321-8471. We do not use a contact form.
Scope a pilot