Deepen AI launches Integrated Solutions for Enhanced Sensor Calibration and Data Annotation

Deepen AI, a Silicon Valley-based start-up specializing in safety-first data lifecycle tools and services for machine learning and AI in autonomous systems, announces new offerings that seamlessly combine the power of sensor calibration and data annotation. Large enterprises seeking to optimize their data labeling processes can now benefit from Deepen AI's proprietary advancements.

Calibration and annotation are integral components of the development and deployment of ADAS systems. They ensure that the sensors are accurately aligned and provide reliable data for decision-making algorithms, ultimately enhancing the safety and performance of automotive technologies.

Deepen AI's calibration tools correct sensor biases, align sensors, and significantly improve the reliability of labeled data, consequently enhancing the performance of machine learning models. Deepen Calibrate aims to help large organizations streamline their data labeling efforts, ultimately elevating the accuracy of their labeling processes.

Deepen Calibrate, simplifies the critical task of sensor data calibration, reducing the time spent from hours to minutes. By managing the complexities of the calibration process, Deepen Calibrate makes autonomous and vision systems safer, transforming a task typically reserved for Ph. Ph.D.-level engineers into an accessible process for everyone. The tool facilitates accurate localization, mapping, sensor fusion perception, and control in a fraction of the usual time.

Data labeling, especially for computer vision applications, can be laborious and time-consuming. Deepen AI's AI-powered tools and expert workforce revolutionize the data labeling process for large enterprises. The comprehensive suite of annotation tools, including AI-assisted labeling, reporting, task management, and quality assurance workflows, empowers enterprises to efficiently manage, track, and verify the quality of processed data.

"Together, calibration and annotation contribute to the overall accuracy and reliability of ADAS systems. By refining sensor data and training models effectively, these processes play a vital role in the system's ability to interpret its environment accurately, make informed decisions, and respond to various driving conditions. This enhances the safety and performance of ADAS technologies, making them more adaptive and reliable in real-world driving situations." stated Mohammad Musa, CEO and Co-Founder of Deepen AI. "With our calibration and annotation tools, customizable plans, and models, enterprises can leverage our years of experience to advance safety in ADAS systems”

Deepen AI actively engages in collaborative efforts within the industry to address safety challenges and share valuable insights. Deepen AI are co-founder of the Safety Pool initiative as well as an active member of the Autoware Foundation, underscoring their leadership and active role in shaping the future of safe and reliable autonomous and assisted driving systems.

Deepen AI's web-based secure tools are deployable on-premise or on the cloud, ensuring compliance with global standards like AICPA SOC2, ISO 27001:2013, and GDPR. Supporting 2D and 3D bounding boxes, semantic segmentation, polylines, scenario labeling, and key points annotation, these annotation tools are industry-agnostic.

In addition to serving large enterprises, Deepen AI's sensor calibration suite has garnered attention from startups and educational institutions. The suite, offering intrinsic and extrinsic calibrations for major sensor pairs, is customizable for various sensor calibration use cases.Deepen AI is currently collaborating with major OEMs and enterprises worldwide. For more information about Deepen AI's products and services, including the new sensor calibration package, visit www.deepen.ai. To schedule a demo, contact info@deepen.ai.