Frequently Asked Questions
Find answers to common questions about our annotation services, quality assurance, scalability, industries served, data security, and how to get started with Annolance.
Annolance offers a comprehensive range of annotation services, including bounding boxes, keypoints, polygons, segmentation masks, lines and splines, landmark annotation, text annotation, audio annotation, and temporal annotation. Each service is tailored to meet the specific needs of your AI and ML projects.
We employ a rigorous quality assurance process that includes multiple stages of review, both automated and manual. Our expert QA team meticulously checks each annotation for accuracy and consistency, ensuring the highest standards are met. Additionally, we use advanced review and quality control tools to maintain the reliability of our data.
Yes, Annolance is equipped to manage large-scale annotation projects efficiently. Our scalable solutions are designed to accommodate extensive datasets, ensuring timely delivery without compromising on quality. Whether you're a startup or a Fortune 500 company, we have the resources and infrastructure to meet your needs.
Annolance serves a wide range of industries, including autonomous vehicles, healthcare, retail, security, agriculture, geospatial analysis, and more. Our versatile annotation services are applicable to various fields that rely on precise and reliable data for their AI and ML models.
Annolance takes data security and confidentiality very seriously. We implement strict security measures, including data encryption, secure access controls, and confidentiality agreements with our staff. Our infrastructure is designed to safeguard your data throughout the annotation process.
To get started, you can contact us through our website's contact form, email, or phone. Our team will get in touch with you to discuss your project requirements, provide a detailed proposal, and guide you through the onboarding process. We look forward to partnering with you to achieve your AI and ML goals.