While working at her family’s business in India, Priyansha Bagaria uncovered an issue: the insulation tape the company manufactured frequently had defects, upsetting customers.
She decided to develop AI software that would alert workers of anomalies in the tape during production, ensuring that substandard products were removed before ever being sold.
The tool is still operational and motivated Bagaria to launch Loopr, a startup that offers manufacturing firms edge-based software to aid production and compliance. The Seattle-based company recently raised more than $1 million and partnered with Microsoft.
Bagaria previously worked as chief revenue officer at InViz AI, a machine learning development company based in India, where she helped acquire customers in North America. She launched Loopr in the summer of 2021.
Bagaria teamed up with Chief Product Officer Kevin Hannegan, who founded the automated business intelligence platform Presalytics.io, and Chief Data Officer Anirban Konar, who previously held AI leadership roles at IT giant Cognizant.
Bagaria, who hails from a small town in India, is passionate about women empowerment. Part of Loopr’s mission is to provide tech-based opportunities for women from disadvantaged backgrounds through its Data Annotation team.
Bagaria said the startup trains disenfranchised women in data labeling processes, then hires them as contractors when the company has a large customer project.
Loopr’s AI-powered edge applications have a variety of use cases ranging from defect scanning, maintenance prediction and inventory management. The startup offers a software platform that captures this process data, generates analytics, and oversees and improves application performance.
The 15-person company also sells natural language processing software that scans and extracts text from compliance paperwork, streamlining filing requirements for workers.
Bagaria cited a medical manufacturing company as an example of how Loopr’s technology can increase production efficiency. Previously, a technician had to spend 10 hours a day inspecting tiny endoscopic surgical parts for quality control, which caused fatigue and errors, she said.
With Loopr’s tech, anomalies can be detected at a micron level, allowing for quicker defect identification and increased production throughput, she added.
Asked how Loopr plans to scale, Bagaria said that more than 90% of its AI applications can be white-labeled and repeated. The startup also sells a pre-packaged version of its software to some businesses. She said the company intentionally targets manufacturers in similar industries.
“They all have the same pain points,” she said. “Once you build that model, the work is pretty much the same.”
Bagaria said one of the obstacles so far is that many companies in the manufacturing space have been slow to implement technology into their workflow. The pandemic helped to accelerate adoption, she added, as more companies looked to digitize and automate processes to enhance production processes.
Loopr is vying for market share with established robotic automation leaders such as UiPath, in addition to a surge of emerging startups developing no-code solutions for industrial clients. Profet AI, a startup based in Taiwan, recently raised $4 million and intends to target semiconductor, chemical, textile, and electronic manufacturers.
Bagaria said Microsoft has been a “really good” partner for the startup but is not an investor. She declined to provide specific details about how the partnership works.
The Redmond-based tech giant has made it a strategic goal to onboard more startups onto its cloud platform, highlighted in recent months by its partnership with San Francisco-based artificial intelligence powerhouse OpenAI.
