Akridata Named a Vendor to Watch in the IDC MarketScape for Worldwide Data Labeling Software Learn More
Discover the power of the
Edge Data Platform
Decentralised structure & scalable process to
Deliver Smart Pipelines
Relevant Data
Lower Costs
Smart Pipelines
Simplify AI data operations, ingest and organize streams of data flowing from edge to core to cloud, and with a decentralized catalog and global access.
Relevant Data
Locate the most relevant data in minutes, not days. Easily build smart pipelines to collect, organize, transform, track, and access just the right data, no matter where it is.
Lower Cost
Save on IT costs because smart data processing at the edge, core, and cloud saves you time, tracks and protects your data, and increases the efficiency of your infrastructure.
Akridata Platform Edge to Core to Cloud Data Fabric
Benefits
Following are the benefits of Akridata solution
- Modernize data ops for AI
- Boost productivity for data scientists and ML teams
- Lower CapEx and OpEx for IT departments and site operators
Industries
The Akridata solution is used in diverse areas like
- Autonomous and assisted driving
- Smart cities, medical imaging, genomic analysis
- Cashier-less retail, and manufacturing
Got Edge Data?
End-to-end
Data is everywhere
According to Gartner, 75% of enterprise-generated data will be created and processed at the edge, outside a traditional centralized data center or cloud. It is an end-to-end problem and opportunity, where data is generated and used by globally scattered edge devices and services.
Exascale
Data is massive
Advanced AI and Autonomy need massive amounts of curated data. Most disruptive AI use cases involve visual sensors which produce tens of terabytes per day resulting in explosive volumes. Need for a solution to efficiently process, store and access data at scale for AI use cases.
Productivity
Data is everywhere
Complexity means cost, and a continuous flow of decentralized opaque data amplifies the problems. Today, 60% of a data scientist’s time is wasted because it is too difficult and too time-consuming to ingest, pre-process, categorize, and catalog the data.