Rendered.ai
About
About Rendered.ai
Rendered.ai lets engineering teams construct synthetic-data workflows from configurable scenes, objects, sensors and rendering components. The platform supports electro-optical, infrared, synthetic-aperture radar, multispectral, hyperspectral and X-ray imagery, generating labelled datasets in conditions that may be rare, hazardous or expensive to capture physically.
Users can vary geometry, materials, weather, illumination and sensor parameters, then compare the resulting datasets and model performance through repeatable experiments. Rendered.ai provides a cloud development environment, an extensible framework and managed synthetic-data services, allowing customers to build their own channels or commission complete datasets and computer-vision validation programmes.
Supply
Supply chain relationships
- NVIDIA
Inbound - Compute & Control - Rendered.ai integrated NVIDIA Omniverse Replicator into its cloud synthetic-data service through an Omniverse channel
Source
Funding
- 2021-10-05 - Seed - $6M - Rendered.ai raises $6M seed round for synthetic-data platform
Rendered.ai closed $6 million in seed funding led by Space Capital to expand staffing and operations for its synthetic-data platform-as-a-service. - source: rendered.ai
Investors
- Congruent Ventures - Participant - VC - 1 funding event - first seen 2021-10-05
- Space Capital - Lead - VC - 1 funding event - first seen 2021-10-05
- Tectonic Ventures - Participant - VC - 1 funding event - first seen 2021-10-05
- Uncorrelated Ventures - Participant - VC - 1 funding event - first seen 2021-10-05
- Union Labs - Participant - Angel / Individual - 1 funding event - first seen 2021-10-05
Team
- Ario Sanchez - Chief Executive Officer - Leads Rendered.ai and its platform for generating and managing synthetic computer-vision data.
- Nathan Kundtz - Co-founder & Executive Chairman - Co-founded Rendered.ai and supports corporate and product strategy as executive chairman.
- Duane Harkness - Co-founder & Chief Architect - Co-founded Rendered.ai and leads architecture for its synthetic-data platform.
- Ethan Sharratt - Co-founder & Director of Engineering - Co-founded Rendered.ai and leads engineering delivery for its synthetic-data platform.
Timeline
Events
- 2023-06-13 - Capability - Rendered.ai integrates NVIDIA Omniverse Replicator for synthetic data generation
NVIDIA described Rendered.ai using RTX-accelerated Omniverse Replicator capabilities including ray tracing, domain randomization and multi-sensor simulation. The integration brought synthetic-data generation into Rendered.ai?s collaborative cloud web interface for computer-vision teams. Rendered.ai planned to demonstrate the Omniverse Replicator integration at CVPR 2023 in Vancouver.
Source - 2021-10-05 - Funding - Rendered.ai raises $6M seed round for synthetic-data platform
The $6 million seed round was led by Space Capital, with Tectonic Ventures, Congruent Ventures, Union Labs and Uncorrelated Ventures participating. Rendered.ai described its platform as simulation-based engineered data for industries including autonomous vehicles, robotics, life sciences and satellite technology. The capital was tied to staffing and operations scale-up for its synthetic-data platform-as-a-service.
Source
Relations
Relationships
- NVIDIA
Omniverse Replicator Integration - Rendered.ai integrated NVIDIA Omniverse Replicator into its synthetic-data generation platform.
Context
Comparable profiles
- Wuwen Zhike
stack adjacency - Simulation Training Stack
- Parallel Domain
stack adjacency - Industrial Synthetic Data · Model Validation For Robotics
- Arrive AI
stack adjacency - Simulation Training Stack
- Cognata
stack adjacency - Simulation Training Stack
Context tags
- Industrial synthetic data - Capability - Official company material supports the industrial synthetic data context.
- Model validation for robotics - Capability - Official company material supports the model validation for robotics context.
- Simulation Training Stack - Stack Layer - Official company material supports the simulation training stack context.