The Groundlight Hub is a plug-and-play computer vision appliance that gives businesses of all sizes easy access to customized computer vision applications so they can solve problems in security, facilities maintenance, and manufacturing quality
Building on its successful developer products, Groundlight introduces the Groundlight Hub to easily integrate its artificial intelligence with cameras and alerting for business applications. Groundlight’s natural language interface and human escalation technology enable AI computer vision to work reliably for new applications on day one, ensuring false alerts are minimized, and notifications are reliable and actionable.
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“We’ve spent 10 years looking for a way to automate the inspection of camera installations. Groundlight Hub verifies camera health daily for a fraction of the cost of manual checks, ensuring our technicians are always in the right place at the right time”
The Groundlight Hub lets you ask a question and get a reliable answer, such as “Is the warehouse door open?”, “Is the aisle blocked?”, or “Is the red light illuminated?” Groundlight accomplishes this by giving small businesses the quality of a custom AI model trained for every camera, coupled with 24/7 human oversight for trust and reliability. As a result, the Groundlight Hub can help facilities automate their work and reduce unplanned downtime, eliminating the need for employees to walk around with clipboards, checking for things like blocked fire extinguishers, doors left open, or other operational concerns.
“With rising inflation, labor shortages, and the increasing costs of unplanned downtime, small businesses struggle to maintain their productivity,” says Avi Geiger, CEO and co-founder of Groundlight AI. “Innovative small businesses are keen to try using AI to automate their workflows, but the technology is typically too complex and unattainable for them.” Groundlight enables automated visual monitoring for safety, maintenance, and quality control at a fraction the cost of human labor.
When business operators plan to improve efficiency and reduce mistakes, they usually think about hiring or assigning an employee to keep an eye on the situation. Hiring new employees is slow, and reliable people are expensive. Despite the hype around AI with GPTs and LLMs, humans are the go-to solution for problems in the physical world. Even when it’s obvious that an AI camera system is capable of solving the problem, few applications justify hiring expensive consultants to build a custom vision model. Businesses that pursue this route quickly learn that traditional custom-built models only know what they’re trained to do, and cannot adapt to changes in the operating environment. This often leads to embarrassing failures, requiring expensive retraining, or just turning the system off.
Groundlight CTO and co-founder Leo Dirac says, “Unlike other computer vision solutions, we always keep humans in the loop to double-check the AI’s predictions, so you can trust Groundlight Hub to deliver accurate, actionable alerts, even in a changing environment. AI can be like your best employee on their best day, every day, all day long.”
“We’ve spent 10 years looking for a way to automate the inspection of camera installations. Groundlight Hub verifies camera health daily for a fraction of the cost of manual checks, ensuring our technicians are always in the right place at the right time,” says Jesse Morgan, Principal, 4wardmotion Solutions.
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The Groundlight Hub connects seamlessly with most new or existing networked cameras. Operators can choose from a growing menu of pre-built solutions, or define their own questions without writing code. Groundlight uses the latest Visual LLM technology to build and deploy customized AI models. Any time the system is unsure, it gets help from live 24/7 human monitors, using Groundlight’s Escalation Technology. Whenever Groundlight’s AI identifies a problem, it can double-check with a real person before sending an instant alert to your phone or email, or even pause automated equipment to wait for an operator.
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