Skip to content Skip to footer

Data Annotation & AI Training

Controlled annotation and QA at production scale.

BergFlow runs the controlled record for data labeling and AI training — structured intake, annotation, multi-pass QA, reviewer accountability, and lineage tracking — so every batch is traceable from receipt to delivery.

DATA ANNOTATIONRaw videoText + audioSensor framesACTIVE SAMPLEcar .98QAMODELUNLABELED · LABELED · QA-APPROVED · MODEL
96–98%Annotation accuracy across text, image, video, audio, and 3D
2+QA gates per batch
1,250+Trained specialists

Modalities

Every modality, one queue.

Text annotationImage labelingVideo segmentationAudio transcription3D point-cloudRLHF dataGolden setsReviewer QA

How it runs

Lineage from intake to delivery.

01

Structured intake

Every batch enters a labeled schema. Work items tracked from receipt to delivery with full lineage.

02

Multi-pass QA

At least two QA gates per batch. Error rates measured per reviewer, per modality, per task type.

03

Feedback-loop ready

Corrections, disagreements, and new instructions route back into BergFlow with audit history intact.

Next step

Send one batch through the queue.

A 4-week pilot benchmarks accuracy, throughput, and QA evidence on your own data.