Build the data layer your model is missing.
From custom collection to recurring evaluation pipelines, TrainLayer structures each engagement around the model objective, failure mode and evidence required for acceptance.
From source data to verified delivery.
Choose a focused service or combine capabilities into one managed data program.
Custom data collection
Collect custom text, image, video, audio and document data with consent tracking, contributor recruitment, quality controls and documented provenance.
Explore custom AI data collection services ↗02LabelData annotation
Human data annotation for text, image, video, audio and documents with taxonomy design, reviewer calibration, multi-stage QA and measurable acceptance criteria.
Explore data annotation company for AI ↗03EvaluateAI evaluation & RLHF
Build human preference, response ranking, rubric scoring, red-team and expert evaluation datasets for language and multimodal AI systems.
Explore RLHF and AI evaluation services ↗04GenerateSynthetic data
Generate and validate synthetic text, image, document and multimodal datasets for rare cases, privacy-sensitive scenarios and controlled coverage expansion.
Explore synthetic data generation services ↗05VerifyDataset QA
Audit AI datasets for annotation quality, duplication, leakage, imbalance, provenance, documentation gaps and model-relevant coverage risks.
Explore AI dataset quality audit ↗06OperateEnterprise data pipelines
Operate recurring AI data collection, annotation, evaluation, QA and versioned delivery workflows with dedicated processes and measurable service levels.
Explore managed AI data pipeline services ↗Start with the model failure.
Share what the system gets wrong and what data you currently have. We will help identify the most practical first program.
Scope a project ↗