CloudFactory provides managed data labeling and human-in-the-loop services for AI teams. Specialized operators annotate images, text, audio, and video with quality controls tailored to your taxonomy. Flexible pricing models scale from pilots to production, while workflow tools integrate with your pipelines. Security standards and signed NDAs protect sensitive data across industries like autonomous systems and healthcare.
Work with trained operators experienced in computer vision, NLP, and document processing. CloudFactory builds custom guidelines, gold sets, and double-blind checks to drive accuracy. Supervisors review edge cases and provide feedback loops until definitions are clear. You get detailed QA reports and issue tags that feed back into model training.
Connect your storage and labeling tools with APIs, webhooks, or secure portals. Jobs stream data in batches or real time, and instructions update without stopping work. Turnaround options support SLAs from rapid experiments to 24/7 pipelines. Metadata travels with each asset so audits and retraining remain straightforward.
Start with a narrow pilot to validate definitions and KPIs, then expand capacity as volume grows. Elastic staffing matches seasonality without compromising oversight. Estimators help predict time and budget, while dashboards show progress against quotas. You can blend locations to balance cost, latency, and language needs.
Access controls, background checks, and monitored facilities protect sensitive workloads. Data handling policies reflect requirements like HIPAA and GDPR where applicable. Encryption in transit and at rest, plus device restrictions, reduce risk. Audit trails preserve who did what and when so you can demonstrate compliance.
Difficult examples receive special routing to senior reviewers and domain experts. Playbooks capture decisions for rare scenarios so future labeling is consistent. Annotation tools include instructions and reference images in-line to aid judgment. Dispute workflows resolve disagreements quickly and document reasoning for model teams.
Recommended for AI, analytics, and research teams that need reliable ground truth at scale. CloudFactory combines trained talent with process rigor, which reduces iteration loops and improves dataset quality. Leads gain predictability on cost and timelines, while engineers get clearer signals for training and evaluation.
Training data quality limits model performance, and internal teams struggle to keep pace. CloudFactory supplies vetted operators, strong QA, and flexible workflows so you can scale without compromising standards. Security and governance address stakeholder concerns, and reporting shows impact. The result is faster cycles from labeling to model updates and fewer surprises in production.
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