There is a silent technical revolution happening in Autonomy
We enable car manufacturers to unlock 95% of roadways for Self Driving
GO HYPERSPECLIMITED MAP COVERAGE BOTTLENECKS INDUSTRY
Right now 97% of roadways are inaccessible to autonomous vehicles because of the limited coverage of high definition maps. Right now cities like Pheonix, Mountain View and San Francisco are mapped with a very limited footprint. 97% of the road network is untouched and autonomous vehicles don’t function outside the boundaries of the HD map.
PRE-CODED CONTEXT LIMITS VEHICLES
The vehicles lack the ability to see, think and act for themselves, but instead rely on high definition maps to inherit pre-encoded context about the environment. This architecture is unable to cope with stale map information or unplanned obstructions.
NO FUNCTIONALITY WITHOUT HD MAPS
This means that outside the boundaries of these high definition maps, the autonomous vehicle will simply not function.
MAPPING SUPPLIERS STRUGGLING TO SCALE
Existing mapping suppliers are struggling to scale up their operations due to the high costs and slow turn around times.
We Unlock 95% of Roadways to Autonomy
Car manufacturers can unlock 95% of roadways, compress their product development roadmap and reduce operational overhead in production by enabling the vehicles with our next generation vision pipeline.
VISION SDK
Enable the autonomous vehicles to drive like humans do on complex urban roads with real time map creation that has the same fidelity and resolution of a HD map.
SLAM PIPELINE
Leverage Aerial to Ground Cross View Localization and Structure from Motion SLAM to position and navigate autonomous vehicles ubquitously on 95% of roadways.
HARDWARE ACCELERATION
Use edge optimized hardware that removes unnecessary data serialization or compression, while reducing latency and accelerating image processing on low power hardware.
VALIDATION INFRASTRUCTURE
Systematically test and validate the Vision SDK or the SLAM Pipeline on our synthetic test data prior to deployment on real vehicles. This saves time and money during the R&D stage.
TECHNICAL DOCUMENT
Our proprietary and patented Vision SDK compresses technology roadmaps
Learn how car manufacturers are benefitting by working with Hyperspec AI to accelerate their product roadmaps.
JOIN WAITLIST
CASE STUDY
From Idea to Product
Hyperspec AI collected large portions of London UK driving data to create a training data set for it’s AI / ML pipelines.
CAMERA
Industry’s first fisheye vision pipeline for a 360 perspective
VISION SDK
AI / ML models optimized to deal with heavy distortion
EDGE HARDWARE
Low latency, low power, computing powerhouse
SLAM PIPELINE
Aerial 2 Ground and SFM SLAM Pipeline for Ubquitous Localization
SLAM KPIs
Autonomous Vehicles are unblocked to travel on 95% of roadways because of their ability to precisely position and navigate themselves without prior High Definition Maps.
Real World Driving Data
Synthetic Driving Data
Drift Rate
Vision SDK KPIs
Autonomous Vehicles can also level up their Vision capabilities to construct a real time high resolution map for motion planning.
OBJECT CLASSES
PROCESSING BUDGET
LATENCY
Meet The Hyperions
Hyperspec AI is a Silicon Valley based UC Berkeley, SkyDeck ’19 and a Techstars Space ’21 cohort company that is comprised of top talent in computer vision, simulations and artificial intelligence which is backed by an industry leading advisory board.
ABOUT USLatest News
The future of the world is going to be built on advancements in AI, ML, and real time perception. Our proprietary and patent protected vision SDK and SLAM algorithms enable car manufacturers to save hundreds of millions in operational costs.
Product Guide
Self driving cars are going to drive the next industrial revolution by freeing up valuable human resources and by democratizing mobility & accessibility. The technology is quite promising and has[…]
Read more
Scene Segmentation
The scene segmentation module is used to semantically describe the pixels in image data. It is useful for things like free space detection, object recognition, cross-view localization, image filtering based[…]
Read more