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The AI Platform for
Visual Data

Powering our autonomous future
Ingesting and analyzing visual data from 47B+ devices across
the globe to empower data scientists and IT professionals to drive innovation.
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Akridata provides an end-to-end suite of products that support both the smart ingestion and smart exploration of visual data to reduce cost and complexity while accelerating business value.

Smart Ingestion + Smart Exploration for Visual Data

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Edge Data Platform

is the leading decentralized data management and tiering software optimized for Video, LIDAR, and domain-specific log and event data.
Simplify AI data operations, ingest and organize streams of data, including from legacy stores, from edge to cloud, and with a decentralized catalog and global access.

Data Explorer

is the first data-centric MLOps platform that helps data scientists explore, curate and use visual data at a large scale.
Reduce hours of work to minutes. Cut time spent on data selection and curation to accelerate your path to model accuracy.

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.

Industries

Automotive

Autonomous vehicles generate data at an average rate of 4-8 terabytes per hour. Akridata gives organizations the ability to ingest, transfer, store, and immediately access relevant data at a massive scale.

Healthcare

AI in medical imaging show incredible promise for uses like diagnosis, annotation, or redaction. Akridata enables data scientists to find the right data, access it securely, and iterate quickly to improve their models.

Retail

Data ranging from online customer behaviors to intelligent retail locations can help retailers optimize operations and enhance the customer experience. Akridata automates manual, time-consuming data management tasks so data scientists can immediately focus on the 1%-10% of data that is of greatest value

Smart Cities

Maintaining citizens’ safety and privacy is a critical challenge for urban leaders. Akridata allows data science teams to quickly focus on the most relevant data, but it also significantly reduces the time and cost required to transfer, store, and access data from connected cameras.

Manufacturing

With Industry 4.0 on the rise, manufacturers need advanced technology to stay one step ahead of the competition. By leveraging Akridata to find specific images, manufacturing teams can reduce the time of labor from hours to mere minutes, slash the costs and time needed for labeling, and accelerate the process to model accuracy.

Akridata delivers value to Data Specialist.

Data Scientists

IT Professionals

AI Experts

“Most academic datasets are far from the industry's needs. In our case, we have rather small objects in fairly big images. This is probably a common problem, but in academia it is kind of a niche.”
Helge Jacobsen,Senior Deep Learning Engineer at Veo
“Advanced AI models are increasingly created and run on the cloud, but need good quality data from edge devices. The high volume and complex nature of this data has created a new exascale-class problem. Akridata is addressing the problem by managing smart pipelines for ingesting, filtering, curating, tracking, and staging of AI data.”
Jon Jones,Director – Go-to-Market for AI/ML, EC2, and Autonomous Vehicles, AWS
“Data-Centric AI solutions such as Akridata’s Edge Data Platform fill that need and help customers to match the sophistication of their analytics and models with high-quality and relevant data.”
Kurt Niebuhr,Principal Program Manager, HPC/AI Ecosystem and Workload Incubation, at Microsoft Azure
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2X Productivity

  • 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

4X Efficiency

  • Train and iterate AI models faster
  • Improved accuracy, improved safety
  • Reduce manual sorting and labeling

4X Cost Reduction

  • Avoid moving large amounts of data to the cloud
  • Reduce spending on storage/compute
  • Decrease bandwidth and latency

10X Faster Access

  • Real-time edge data access
  • Access at scale, anytime, anywhere
  • Frictionless deployment with existing infrastructure

Akridata delivers value to Data Specialists

“Most academic datasets are far from the industry's needs. In our case, we have rather small objects in fairly big images. This is probably a common problem, but in academia it is kind of a niche.”
Helge Jacobsen,Senior Deep Learning Engineer at Veo
“Advanced AI models are increasingly created and run on the cloud, but need good quality data from edge devices. The high volume and complex nature of this data has created a new exascale-class problem. Akridata is addressing the problem by managing smart pipelines for ingesting, filtering, curating, tracking, and staging of AI data.”
Jon Jones,Director – Go-to-Market for AI/ML, EC2, and Autonomous Vehicles, AWS
“Data-Centric AI solutions such as Akridata’s Edge Data Platform fill that need and help customers to match the sophistication of their analytics and models with high-quality and relevant data.”
Kurt Niebuhr,Principal Program Manager, HPC/AI Ecosystem and Workload Incubation, at Microsoft Azure
“One of the biggest challenges for data scientists focused on visual data is the ability to visualize three-dimensional visual data in a two-dimensional format and gain in-depth understanding from them.”
Bikram Baruah,AI Technical Lead, Advanced Manufacturing Research Centre of The University of Sheffield
“Today we have models that are extremely good at mimicking the data that you train them to mimic, but they can only become as good as that data, not better. The data can always get a little better and cover more corner-cases while models can at best be perfect within the data distribution that they know about.”
Helge Jacobsen,Senior Deep Learning Engineer at Veo
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Data Scientists

IT Professionals

AI Experts

2X Productivity

  • 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

4X Efficiency

  • Train and iterate AI models faster
  • Improved accuracy, improved safety
  • Reduce manual sorting and labeling

4X Cost Reduction

  • Avoid moving large amounts of data to the cloud
  • Reduce spending on storage/compute
  • Decrease bandwidth and latency

10X Faster Access

  • Real-time edge data access
  • Access at scale, anytime, anywhere
  • Frictionless deployment with existing infrastructure

Trusted By Leaders in Technology

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