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The AI Platform for Visual Data

Ingest and Activate

Reliably Ingest Multi-Gen Multi-Format Data
Rapidly Move Tape Data to Cloud Archive
Track All Data in a Global Data Catalog
Managed Service or SaaS

Edge-to-Cloud Data Platform

Avoid Unnecessary Data Movement
Improve Efficiency via Smart Pipelines
Increase Productivity with Anywhere Access
Track Trace End to End Through Inference

Explore and Select

Speed up Data Selection
Avoid Wastages in Labelling
Accelerate Learning Convergence
Improve Model Accuracy

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GTC talk: Accelerate Autonomous Vehicle Development with NVIDIA DRIVE on Microsoft Azure

One of the Top-5 Talks at GTC’22

 

This session demonstrates how Microsoft Azure’s HPC/AI Infrastructure and services can accelerate and operationalize end-to-end development of ADAS systems. We will walkthrough AVOps on Microsoft Azure partnering with Akridata.

– Adithya Ranga, Senior Program Manager, Microsoft Corporation
– Kunal Vasavada, Senior Director of Platform Engineering & Solutions, Akridata

          

 

WATCH THE REPLAY
READ OUR BLOG
Akridata Closes $15 Million in Series A Financing Round
“Real-world AI is all about data and solving AI’s data problem is what Akridata was formed to do. We are delighted by the level of interest from the investment community and look forward to scaling Akridata to help take AI out of experimentation and into the broad marketplace.”
– Kumar Ganapathy, co-founder and CEO of Akridata
Read The News
Akridata Launches World’s First Edge Data Platform for Data-Centric AI
Decentralized Software Accelerates Access to Relevant AI Data, Handles Ingest, Catalog, and Exploration of Complex AI Data, and Enables Traceable AI Across Industries
READ THE PRESS RELEASE
Akridata Joins Exascale Day Celebrations to Drive Awareness of the Challenges and Advances in Data-Centric AI
Massive AI Data at the Edge Brings Exascale-Class Data Problems to Board Rooms
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Akridata is a software blanket on resources from device to cloud that reduces cost and complexity

Akridata
Ingestor

Simplify AI data operations, ingest and organize streams of data, including from tape, from edge to cloud, and with a decentralized catalog and global access. 

Akridata
Platform

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
Explorer

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.

Featured Customers and Partners

WATCH THE VIDEO "Why Akridata"

Why Akridata

Improved Productivity

By automating the manual, time consuming data management tasks, Akridata allows data scientists to spend more time building better AI models faster, and less time on labor-intensive tasks like finding, cleaning, and reorganizing huge amounts of data. Add to that better IT efficiency and lower costs and the result is a 2x improvement in data scientist productivity.

Benefits:

Access the right data in minutes or hours vs. hours or days

Free up time for critical tasks

Efficiently handle growing data volumes at scale

More Accurate AI Models

Akridata pre-processes, catalogs, and prioritizes unstructured data at the edge to get relevant data more quickly, which helps train AI models more accurately. Only Akridata can browse, search, and access specific data regardless of where it resides (edge, core, cloud) and regardless of its geography, storage tier, version, etc. — undeterred by constantly changing data relevancy or evolving data pipelines.

Benefits:

Train and iterate AI models faster

Improved accuracy, improved safety

Access at scale, anytime, anywhere

Lower Costs

Akridata lowers costs by enabling more efficient reuse of existing infrastructure and software assets, avoiding unnecessary costs in data storage and transfer, and improving data scientist productivity. We call this “smart processing at the edge” because data science teams can immediately focus on the 1%-10% of data that is of value which significantly reduces the time and cost required to access, identify, process, transfer, and store data.

Benefits:

Avoid moving large amounts of data to the cloud

Reduce spend on storage/compute

Decrease bandwidth and latency

Flexibility

Akridata allows organizations to extend their existing infrastructure with an Edge to Core to Cloud AI Data Ops platform that retains your hardware investments, processes, and applications. The Akridata platform is also completely customizable to support your unique requirements.

Benefits:

Frictionless deployment

Leverage existing investments

Fully customizable

Data Protection and Compliance

Data tracking is necessary for debugging models and forensic analysis of data. Akridata treats data as code, which gives it the unique ability to track and trace data lineage/versioning from source to AI model to production use in the field. Tracking data lineage provides support for enforcing and verifying regulatory compliance with incidence management and data privacy regulations such as GDPR (EU), CCPA (California) as well as industry standards like HIPAA, FACTA, and GLBA.

Benefits:

Retrieve data anywhere, anytime

Track data lineage and provenance for each data object in the system

Visual Awareness is Critical for Real-World Autonomous Products

Autonomous devices, unattended services, and sophisticated automation are transforming businesses and entire industries. As a result, advanced AI and automation are rapidly moving towards autonomy. 

To meet the functional, social, and compliance requirements of autonomy, you need, foremost, an end-to-end data infrastructure that is built for AI.  

You also need to use all of your products “senses” including visual data. 

Edge Data

In the Autonomous world, Edge, Core, and Cloud form must form a single seamless end-to-end infrastructure, cooperating on data processing, data communications, and data storage.

Deep Learning

Unattended services, even in mildly complex situations, require advanced AI models generated by Deep Learning. They require massive data with rich data formats from complex sensors.

Continuous Improvement

Autonomy means continuous improvement, ability to learn new objectives, respond to new scope, or manage new services. This generates a continuous data flow for continuous learning and continuous feedback from deployments.

Watch the Video "The Autonomous World"

Industries

Automotive

Numerous, data-rich sensors in autonomous vehicles generate data at the alarming rate of 4-8 terabytes per hour, or even more in some cases. Akridata gives organizations the ability to intelligently ingest, transfer, store, and immediately access relevant data at massive scale — regardless of where the data resides at that moment, while also keeping up with the constantly changing nature of data relevancy.

Healthcare

One of the most promising areas of health innovation is the application of AI in medical imaging for uses like diagnosis, annotation, or redaction. The accuracy of AI models directly impact patient safety and adoption of AI solutions by radiologists. Akridata enables builders of these AI models to find the right data, access it securely, and iterate quickly to improve their models.

Smart Retail

Making sense of the growing volumes of data ranging from online customer behaviors to intelligent retail locations create new challenges for retailers looking to optimize operations and enhance the customer experience. Akridata automates the manual, time consuming data management tasks so data scientists can immediately focus on the 1%-10% of data that is of value.

Smart Cities

Whether it’s security surveillance or traffic management, maintaining citizens’ safety and privacy is a critical challenge for urban leaders. Not only does Akridata allow data teams to quickly focus in on the most relevant data, it also significantly reduces the time and cost required to transfer, store, and access data.

About Akridata

Akridata was started by a team of serial entrepreneurs with the vision to solve a unique set of problems around visual data in the life cycle of AI training.

The team collectively brings years of experience ranging from deep engineering, fundamental research, and business experience and has a track record of building and scaling startups.

Akridata offers an ensemble of products that can be consumed as a single platform or as a standalone that collectively help the customers in data exploration, ingestion and training pipelines for AI, Deep Learning and Computer Vision.

READ THE AKRIDATA FOUNDERS' STORY

Leadership

Kumar
Kumar Ganapathy
CEO, Co-Founder

Founder/CEO, Virident (acq. WD)
Founder, VxTel (acq. Intel)
75 patents, 10 papers
PhD UIUC, IIT Madras

Vijay
Vijay Karamcheti
CTO, Co-Founder

Founder/CTO, Virident (acq. WD)
Scientist, Google
Prof. Computer Science, NYU
90+ patents, 75 papers
PhD UIUC, IIT Kanpur

Sanjay
Sanjay Pichaiah
VP, Data Exploration Business

Founder, Trupeco (analytics)
Director, Mitsui Investments
Bear Stearns, Engineering, Level One (acq. Intel)
CSU, Cornell

Sanjay
Sunil Samel
VP, Business Development

VP Strategic Alliances, Virident (acq. WD)
VP BD, Virsec
Founder, CoWare (acq. Synopsys)
IIT Varanasi, U. of Antwerp (Belgium)

Ajith
Ajith Kumar
Director, Software Engineering
Sr. Manager, Advanced Technology, WD
Principal Engineer, Virident (acq. WD)
Systems Software, HPE
20+ patents
JSS University, Mysuru
John_Wilson-300x355-bw
John Wilson
VP, Sales
Automotive OEM Sales Director, Ansys
Automotive Sales Director, NI
MSEE ASU, BA MSU
READ THE AKRIDATA FOUNDERS' STORY

Investors

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