Platform to manage your Data [Annotation]

DataFoundry gives clarity to data annotation cost, quality, and progress across vendors, tools, and data types.

Built for Scale

End-to-end annotation operations platform

From project kickoff to final delivery, manage every aspect of your annotation pipeline with enterprise-grade tools designed for regulated industries.

Real-Time Analytics

Monitor cost per task, throughput by stage, and quality metrics across all vendors in one unified dashboard.

Audit-Ready Compliance

Complete audit trails for every data import, annotation decision, and guideline change. Export compliance reports instantly.

Import logs
Decision trails
Change history

Vendor Performance

Compare annotation quality, turnaround time, and cost efficiency across multiple vendors with side-by-side analytics.

Throughput Optimization

Identify bottlenecks in your labeling pipeline with daily throughput charts. Optimize resource allocation in real-time.

Deploy faster

Everything you need to manage annotation ops

Stop managing labeling via spreadsheets. Get real-time visibility into your data pipeline.

Cost & Quality Metrics
Track spend per scan, rejection rates, and rework costs across all your projects and vendors.
Throughput Analysis
Visualize daily throughput by stage. Identify bottlenecks in labeling or QA steps immediately.
Vendor Management
Compare vendor performance side-by-side. Monitor capacity and utilization of your internal and external teams.
Governance & Audit
Full audit trails for every import and change. Maintain a registry of datasets, guidelines, and evaluations.

Built For

Teams managing mission-critical AI data

DataFoundry is designed for ML teams in regulated industries who need audit trails, vendor controls, and quality assurance built into their annotation workflows.

Healthcare AI

FDA-compliant workflows

Automotive Vision

ADAS & autonomous driving

Research Labs

Clinical AI research

Enterprise ML

Production-grade pipelines

Join teams running compliant annotation programs in medical devices, autonomous vehicles, and clinical AI.