Data Annotation Platform

A data annotation platform is software for labeling and reviewing data used to train machine learning models. LabelFort is a data annotation platform built for regulated AI, which means it does two jobs at once: it produces the labels, and it produces the record of how they were made. Upload your data, choose the annotation type, run it through AI assisted or dual review workflows, and export the labels with the audit log, the agreement report, and the chain of custody attached.

LabelFort is certified against ISO 27001:2022, aligned to the SOC 2 Trust Services Criteria, and engineered to satisfy HIPAA, GDPR, and India's Digital Personal Data Protection Act. DPDP readiness is not an add on, it inherits from the already audited ISO baseline. A control mapping document and the DPDP readiness report are available for Legal and Compliance review during intake.

Image (bounding boxes, circles, polygons and polylines, brush masks and SAM assisted segmentation, keypoints and skeleton based pose), video (shape and track modes with persistent object identities, keyframe interpolation, AI assisted tracking), LiDAR and 3D point cloud (3D cuboids in synchronized multi view), medical DICOM (structured findings, measurements, landmarks), text and structured data (classification, sentiment, intent, field extraction through configurable forms, with CSV rows and PDF supported), audio (time segment labeling, verified transcription, speaker diarization), documents (VLM assisted extraction through OCR and VQA pipelines), geospatial imagery, and RLHF and evaluation workflows.

Quality is measured with Inter Annotator Agreement, scored using Cohen's kappa, with IoU or F1 agreement for geometric tasks, against a threshold above 0.90, validated on your dataset during the proof of concept and tracked in delivery reporting. Every annotation action, review, and configuration change is captured in an immutable audit trail and exports as a chain of custody record. Audit log coverage is 100% by design.

LabelFort ships with dedicated role based workspaces for Platform Admin, Admin, Operations Manager, Quality Manager, Annotator, Verifier, Auditor, and Client. Each role has its own routing, dashboards, and navigation, and access checks are enforced on protected verifier and auditor surfaces.

Yes. LabelFort is tool agnostic. Exports cover COCO including RLE, YOLO, KITTI, MOT17, labeled image ZIP, Excel or CSV, and NDJSON audit logs, with additional formats on request, and delivery lands in S3, GCS, or directly in your pipeline. File dimension and tracking attribute integrity are preserved end to end, so annotations do not drift relative to the underlying media.

Not through an open trial. The entry point is a one hour Compliance Review followed by a fixed $100 evidence grade proof of concept on your own data, up to 1,000 annotations, which produces a real evidence pack you can put in front of Legal before you commit to volume. That is a deliberate choice: an open trial shows you the interface, and a scoped proof of concept shows you the evidence.

Compliance Review, then an evidence grade proof of concept, then a governed pilot, then procurement ready scale. Pilot to production typically runs 30 to 45 days once the proof of concept evidence pack is signed off. We do not run open trials, and we do not enter engagements without a defined evidence output for Legal and Procurement review.

Yes. LabelFort supports structured RLHF preference collection, instruction tuning, evaluation rubrics, and red team workflows, with the same IAA reporting, role based QA, and audit coverage as every other project type.

LabelFort is a product of Predusk Technology Pvt. Ltd., an independent company with no hyperscaler or model lab ownership stake. Your training data, audit logs, and evidence packs do not route through, or back to, any competing foundation model lab.