Accepting new data programs for Q3

AI data infrastructure

Better models begin with better data.

TrainLayer designs and operates custom data programs for AI teams—from collection and annotation to evaluation, quality assurance and versioned delivery.

Scope your dataset ↗Explore our work

Consent-aware sourcingHuman-reviewed qualityDocumented provenance

TRAINLAYER / OPERATIONS

LIVE

ACTIVE PROGRAMMultimodal Evaluation — 042

WEEK 03 / 06

Collection38,420

Primary review37,881

QA sample7,576

Accepted37,544

Agreement0.86+4.2%

Acceptance97.8%On target

Formats04JSONL · CSV

Built for teams working across

Generative AIComputer visionVoice AIRoboticsDocument intelligence

What we do

We turn difficult model requirements into reliable data operations.

Every program starts with the failure mode: what the model misses, misunderstands or handles inconsistently. We translate that into a sourcing plan, labeling system and measurable acceptance criteria.

Explore our operating model ↗

01Source

Custom data collection

Consent-aware collection programs designed around your target population, environment, modality and model objective.

Explore capability ↗

02Label

Data annotation

Human annotation workflows with clear taxonomies, calibrated reviewers and measurable acceptance criteria.

Explore capability ↗

03Evaluate

AI evaluation & RLHF

Human preference, rubric-based evaluation and red-team datasets for improving model behavior and reliability.

Explore capability ↗

04Generate

Synthetic data

Purpose-built synthetic datasets, verified by humans and delivered with documented generation and filtering methods.

Explore capability ↗

A measurable operating model

Not a black-box annotation vendor.

You get a documented workflow: collection protocol, taxonomy, reviewer calibration, acceptance thresholds, dataset card and version history.

Review governance ↗

01Define

Model objective, target population, edge cases and delivery specification.

02Produce

Source or generate data through controlled, traceable workflows.

03Calibrate

Train reviewers and measure agreement before production scales.

04Verify

Audit quality, document limitations and deliver versioned exports.

Selected specifications

See what model-ready looks like.

View all sample datasets ↗

SPEC / 01personhelmetvest

Image + video48K frames

Warehouse PPE Detection

A model-ready visual dataset for detecting helmets, reflective vests, safety shoes and restricted-zone violations.

97.4% audited label acceptance

SPEC / 02vendorGSTINinvoice-number

Documents32K pages

Invoice OCR India

Diverse Indian invoices and tax documents with field-level transcription, layout regions and line-item tables.

99.1% field transcription accuracy

SPEC / 03transcriptlanguageaccent

Audio4,200 hours

Indian Multilingual Speech

Read and conversational speech spanning Indian English, Hindi and regional languages across devices and environments.

Human-reviewed WER benchmarks

Generative AI✦Computer vision✦Voice AI✦Robotics✦Healthcare AI✦Enterprise documents✦Generative AI✦Computer vision✦Voice AI✦Robotics✦Healthcare AI✦Enterprise documents✦

Build the missing data layer

Where is your model failing today?

Tell us the use case, modality and target outcome. We’ll respond with a practical scoping path—not a generic sales deck.

Start a data program ↗