DataForce

Leveraging Computer Vision Technology for Intelligent Inventory Management

“DataForce is a great company to work with! The team has been highly organized, responsive, and accommodating to changing requests and requirements. This has helped us model our dataset of 300+ liquor products to 90%-95% accuracy for detection, and we are working with the other metadata collected to solve specific use cases around workflow and sales analytics. DataForce delivered based on our requirements, and I am happy about that. ” 

– Ramesh Tirumala, CEO, Aapya Solutions

The Challenge

Our client, Aapya Solutions Inc., has developed an intelligent inventory system called Eyes on Shelves to ease the burden of real-time inventory management. For many retailers, inventory accuracy, real-time visibility of stock status on shelves, product loss, and planogram compliance common daily challenges—not to mention the cost involved to manually audit shelf status. With its existing computer vision capabilities and proprietary Vision-37 Inventory Intelligence Platform, Aapya was seeking a partner to help accelerate turnaround time and collect high-quality data to train the model in efforts to consistently provide 24/7/365 “eyes on the shelf” monitoring for its customer

Inspiration & Industry Foresight

“Based on my personal experience of not finding my favorite products on the shelf several times, I visited a variety of stores from grocers to liquor stores to convenience stores and decided to solve this challenge with emerging technology. We are at the right time and place to do exactly that.” 

 

– Ramesh Tirumala, CEO, Aapya Solutions

According to ScienceSoft, the global computer vision market is expected to reach $41.11 billion by 2030 at a compound annual growth rate (CAGR) of 16%.

Market growth is spurred by the increasing demand for computer-vision-based inventory counting solutions across various industries, from manufacturing and retail to healthcare and logistics. The main drivers for the popularity are the need for faster and more accurate inventory counting, optimized labor and equipment cost, and streamlined decision-making on stock replenishment.

With over 40,000 liquor stores in the United States alone, Aapya Solutions is focused on deploying its solution into not only the beverage industry, but adjacent verticals like gas stations, convenience stores, and beyond.

“We are always excited to work with companies like Aapya who are considered industry disruptors trying to innovate beyond the status quo. Projects like this require niche data collection and annotation services to remove these data bottlenecks, which excited us because we offer the most flexible and tailored solutions in the market. We saw an opportunity to work with a brilliant team in Aapya but also be part of a massive opportunity to improve the inventory management industry with AI.”

– Kris Perez, Director AI, DataForce

Solution

In addition, the customer asked us to segment another two wide-angle images of the same aisle segments and bottles, which resulted in an additional 468 segmentations with 1,404 attributes in total (three provided per segmentation in order to match initial scope).

Because of the need for high-quality data, DataForce performed sampling of 80% on collection and 84% on annotation, achieving a pass rate of 98% on collection and 97% in annotation (over 500 polygons/bound boxes and 5,000 attributes reviewed), resulting in a customer pass rate of 99.8%.

The project was completed in less than one month.

As the project progresses and the Vision-37 platform evolves with the real-time, high-quality insights it needs to operate with maximum efficiencies, Aapya’s focus will be to improve the guest experience by providing retailers results that will improve their top and bottom lines in tandem. DataForce is proud to serve as a partner to Aapya in delivering the curated data needed to provide much-needed insights on missing and misplaced products, easing inventory burdens for their clients. It is our goal to provide Aapya with the data necessary to continue refining the Vision-37 platform and processes to scale locally, regionally, and nationally.    

“The result of the DataForce and Aapya partnership puts us closer to winning a revenue stream from these early liquor store adapters by the end of 2023 and Q1 of 2024. We are super excited about the potential to scale this across other stores and meet our business goals by the end of 2024. We feel that Aapya in partnership with companies like DataForce can be the leading player in this space, as we have learned some key nuances with respect to computer vision, data collection, data prep, and cleansing along with the associated logistics.”

– Ramesh Tirumala, CEO, Aapya Solutions

N

Collection of photos of aisle segments as well as their corresponding individual bottle barcodes;

N

Provision of up to eight attributes per bottle;

N

Segmentation of each bottle and barcode using polygons and bounding boxes, respectively.

Photos Taken

Attributes

Segmentations

Benefits

As early adopters of this new computer vision technology, Aapya Solutions relies on feeding the model with high-quality data to expand capabilities and advance structural knowledge while prioritizing the protection of customer data as an emerging startup. When approaching DataForce, there was a need to build a data infrastructure by acquiring and annotating data at scale.

Starting near Aapya’s Tampa Bay-area headquarters, DataForce assisted in sourcing locally by building a custom data collection pipeline and quality assurance (QA) process, managing the data curation from a project management perspective.

To achieve this, DataForce enabled a full workflow through our proprietary platform, allowing for a seamless data flow from collection to annotation through delivery while maintaining data security. The full scope of work included:

  • Collection of photos of aisle segments as well as their corresponding individual bottle barcodes;
  • Provision of up to eight attributes per bottle;
  • Segmentation of each bottle and barcode using polygons and bounding boxes, respectively.

First, we leveraged our community to find a team member who could easily travel to the indicated liquor store over a span of three days to take photos of over 300 products and their barcodes.

The challenge was how to reduce collection and annotation time, as all attributes needed to match exactly between the different data types. To enable this, DataForce created a workflow using a system of three coordinates (aisle segment + shelf number + position in shelf). The team member was able to snap the photos directly into our cloud through DataForce Contribute, our mobile application, then provide those coordinates and the corresponding attributes (from brand to size) for only one photo type, without having to repeat attributes across the two photo types. This reduced not only the time to complete the task in both collection and annotation, but also the cost to the customer—all while improving quality and eliminating risks of extensive manual data entry.

Once images were collected, we provided segmentations by way of polygons (for bottles) and square bounding boxes (for barcodes) for all the bottles across all data types.

To support this, our expert technology team built a script-based solution that was able to read the coordinates, transpose the corresponding attributes across all photo types and respective segmentations for annotation, and build scripts to generate a YoloV8 format—a first for DataForce.

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