Autonomous vehicles and robotics

Autonomous Vehicle (AV) and Robotics companies are pushing the boundaries of AI. They are under immense pressure to drive model performance ever higher, whether to ensure safety for everyone on the road or to increase manufacturing yields, quality, and profitability.

The challenge

AVs capture raw data from a mix of 360-degree and thermal cameras as well as LiDAR and RADAR sensors, generating terabytes of data per hour which is then sent to the cloud. Data at this scale puts a strain on the entire AI pipeline from both a cost and time perspective.

For AV and robotics companies, all data is hot data which must be quickly ingested, analyzed, and acted upon. These data costs consume ever more of the AI innovation budget and crowd out investment in compute, tooling, and people.

How Granica helps

Granica increases the efficiency and utility of your AI-related data and your downstream AI pipeline stages, enabling you to free up significant money, resources, and time which you can reinvest to improve AI performance and outcomes.

Granica Crunch for AV/Robotics data

Granica Crunch reduces the storage cost associated with AI data without archival and/or deletion. Its advanced, patented ML-powered data reduction algorithms are specifically optimized for the LiDAR, RADAR, and camera data prevalent in the AV and robotics industries.

How Crunch helps AI/ML Engineers

• Optimizes S3/GCS object storage costs, so you can allocate more resources to data quality and model performance
• Supports a wide range of data types unique to AV systems
• Elastically scales up and down to support dynamic workloads

How Crunch helps AI Product Owners and FP&A

• No upfront capital outlay — Crunch doesn't cost budget, it frees up budget
• Ongoing, predictable savings enable accurate forecasting and planning

Typical data reduction rates

DRR varies based on customer-specific data. Estimate your savings to evaluate the DRR for your specific data.