01
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.
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.
01 What we do
A custom data pilot
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.
A custom data pilot
02 Two starting points
Start with one model decision
Both paths end with an accepted, client-specific dataset—not labor hours, software seats, or access to an undifferentiated crowd.
01
You have rollouts or generated outcomes but do not trust where they fail or whether a model change improved them.
02
You need demonstrations, interactions, decisions, failures, recoveries, or outcomes that cannot be sourced off the shelf.
03 Pilot designs
Three focused offers
Pilot / 01
Qualified reviewers locate the first invalid transition in action-conditioned rollouts, classify the failure, assess progress and outcomes, and adjudicate disagreement.
Pilot / 02
Qualified people create complete episodes connecting an initial state, action or interaction, resulting state, outcome, and quality status.
Pilot / 03
Blinded human review tests whether synthetic or simulated data is physically, causally, behaviorally, and operationally suitable for its intended use.
Evaluation to training Turn recurring evaluation failures into targeted human-created training data, then test the next model version again.
Example See how an omelette task becomes structured action-and-outcome training data
04 Capabilities
Explore all capabilitiesEvaluate model behavior, create missing training examples, or build a dataset around your company's workflows.
01 / Evaluate
Test voice agents, review robot and human videos, and compare model responses against clear criteria.
Explore evaluation02 / Create
Create targeted examples and capture human actions, decisions, corrections, and outcomes.
Explore training data03 / Your company
Turn company knowledge, customer conversations, and employee expertise into reviewed datasets for your AI application.
Explore enterprise datasets05 Method
A closed-loop program
Every engagement begins with the model decision the data must support, then works backward to the people, evidence, rights, and controls required.
01
State what the dataset must capture and how it will be used.
02
Define the data unit, protocol, rubric, rights, and acceptance test.
03
Qualify the right people and operate collection or evaluation.
04
Validate, review, adjudicate, reject, retake, and preserve provenance.
05
Provide accepted data, structured metadata, and quality documentation.
The dataset you need may not exist yet
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.
hello@consequencelabs.com941-321-8471
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