Right-sized human judgment for AI teams
From structured annotation to practitioner-led evaluation, we organize the contributors and review process each part of your project actually needs.
Data Creation & Annotation
Foundational data work for training and fine-tuning models: labeling, extraction, transcription, and validation across text, image, audio, video, and documents.
What you get
Labeled, structured, or cleaned datasets ready for training or evaluation.
Who does the work
Trained annotators for repeatable tasks, with domain-aware reviewers when context matters.
When it's useful
Building or expanding a training set, cleaning existing data, or moving into a new modality.
How quality is reviewed
Sampling, adjudication, and escalation to a senior reviewer on disagreement.
Image & Video Annotation
Bounding boxes, segmentation, keypoints, and frame-level review for computer vision models.
Text, Audio & Document Work
Classification, extraction, transcription, and document parsing across languages and formats.
Validation & Adjudication
Sampling, cross-checks, and disagreement resolution to keep labeled data consistent.
Practitioner & Expert Data
Realistic task creation, reference answers, and rubric design from people who have actually done the underlying work.
What you get
Task sets, ideal answers, grading rubrics, and validated professional scenarios.
Who does the work
Working practitioners create tasks and answers; senior specialists validate complex or high-impact work.
When it's useful
Testing a domain-specific model, building a benchmark, or grounding preference data in real practice.
How quality is reviewed
Cross-practitioner review plus specialist sign-off before anything is delivered.
Realistic Task Creation
Scenarios and benchmark items grounded in financial, operational, technical, and analytical workflows.
Reference Answers & Rubrics
Ideal answers and scoring criteria that reflect how the work is actually judged in practice.
Professional Workflow Simulation
Domain-specific review across business, enterprise software, research, and multilingual professional tasks.
Model Evaluation & Human Feedback
We evaluate not only whether a response appears plausible, but whether it would be considered usable by someone familiar with the underlying work.
What you get
Graded outputs, ranked comparisons, failure taxonomies, and targeted correction data.
Who does the work
Practitioners and domain-aware reviewers grade against a rubric; specialists adjudicate close calls.
When it's useful
Comparing model versions, building an eval set, or diagnosing why a model underperforms in practice.
How quality is reviewed
Inter-rater agreement checks and rubric calibration before full-scale grading begins.
Grading & Preference Ranking
Rubric-based scoring and pairwise comparison of model responses.
Benchmark Construction
Custom evaluation sets built around real tasks rather than generic public benchmarks.
Human Feedback & Correction Data
Targeted correction examples and demonstrations to support fine-tuning and post-training work.
Trust & safety review
Structured human review for harmful, inconsistent, or policy-violating model behavior. Scope depends on the domain and applicable risk level — this is a supporting review capability, not a standalone compliance program.
Managed Data Operations
We manage the operational layer between your team and a distributed contributor pool, so you don't have to build that infrastructure yourself.
What you get
A running workflow with qualified contributors, defined QA stages, and regular reporting.
Who does the work
A DataSea project lead coordinates contributors, reviewers, and escalation paths.
When it's useful
Turning a pilot into an ongoing pipeline, or when your team lacks bandwidth to manage contributors directly.
How quality is reviewed
Multi-stage QA with escalation paths and a reporting cadence agreed upfront.
Sourcing & Qualification
Finding and assessing contributors with the right background for your project.
Calibration & Multi-Stage QA
Onboarding, task design, and layered review so quality holds as work scales.
Flexible Project Scaling
Progress reporting and the ability to grow contributor capacity as scope changes.
Not sure which capability fits?
Tell us what you're building and where human judgment is currently the bottleneck — we'll help you scope the right starting point.