Rendered.Ai
Company Name : Rendered.Ai
AI Category : Synthetic Data
Address : 4311 11th Ave. Northeast, Suite 512, Seattle, Washington, USA- 98105
Website : https://rendered.ai/#slide-out-widget-area
Email : support@rendered.ai
Helping Customers Overcome Data Bias, Gaps, and Costs for AI/ML Training Rendered.ai was established after the realization that many industries were about to explode with massive investments in hardware-intensive imagery collection and analysis. Without the ability to access data during the design and development process, organizations are unable to validate analysis pipelines and business models before launching expensive hardware, sometimes literally, into the market. From space-based satellite imaging to manufacturing and security inspection, computer vision hardware and applications are proliferating across every industry. Relying on collected data alone carries risks and costs due to dataset biases and real data is simply not available for new sensors and platforms. Simulating sensor behavior and data output is a well-established technique used during the design and inception process for new equipment, but historically was not done at a scale sufficient to generate annotated data for the purpose of training computer vision algorithms. Rendered.ai was founded to connect simulation with data generation for computer vision and the team quickly demonstrated the potential for using simulated data to train Artificial Intelligence and Machine Learning systems with customers in the geospatial industry. Along the way, the team observed that simulated, or synthetic, data required an iterative workflow best supported by a platform that could encompass simulation tools, compute management, and domain-specific content. The Rendered.ai platform as a service has been in production since late 2021 and is helping customers across multiple industries and countries to reduce bias and overcome cost and availability issues when training algorithms to solve critical problems.
Helping Customers Overcome Data Bias, Gaps, and Costs for AI/ML Training
Rendered.ai was established after the realization that many industries were about to explode with massive investments in hardware-intensive imagery collection and analysis. Without the ability to access data during the design and development process, organizations are unable to validate analysis pipelines and business models before launching expensive hardware, sometimes literally, into the market. From space-based satellite imaging to manufacturing and security inspection, computer vision hardware and applications are proliferating across every industry. Relying on collected data alone carries risks and costs due to dataset biases and real data is simply not available for new sensors and platforms.
Simulating sensor behavior and data output is a well-established technique used during the design and inception process for new equipment, but historically was not done at a scale sufficient to generate annotated data for the purpose of training computer vision algorithms.
Rendered.ai was founded to connect simulation with data generation for computer vision and the team quickly demonstrated the potential for using simulated data to train Artificial Intelligence and Machine Learning systems with customers in the geospatial industry. Along the way, the team observed that simulated, or synthetic, data required an iterative workflow best supported by a platform that could encompass simulation tools, compute management, and domain-specific content.
The Rendered.ai platform as a service has been in production since late 2021 and is helping customers across multiple industries and countries to reduce bias and overcome cost and availability issues when training algorithms to solve critical problems.