Why do we exist?

Stage 1

Rise of eCommerce Revolution

Large. Clunky. Expensive. If those three words don’t explain the current landscape of Automated Dimensioning solutions, we don’t know what will. Of course, the current range of Automated dimensioning solutions in the market was perfect for the 30,000-100,000 sq.ft warehouses and the huge distribution centers built by the Fortune 500s. But that was stage 1 of the e-commerce revolution.

Stage 2

Role Of Fulfillment Centers in the eCommerce Industry

Stage 2 entails the creation of Order fulfillment centers and Micro Fulfillment centers, which are just 3,000 – 10,000 sq.ft big. There is no space for conveyors here. The order volume here ranges from 300 – 2,500 per shipping station. More and more D2C brands and mom-and-pop stores use these kinds of warehouses to ship across the world. But Automated dimensioning solutions are still stuck in the era of bigness. They are more focused on shipping 25,000 parcels an hour. But this new group needs a new kind of solution.

Stage 3

Assemble & deploy in <15 mins

Quick. Plug and play. In-expensive. And this is where vMeasure comes into play. vMeasure built by VisAI labs is a range of computer vision-enabled Automated dimensioning systems explicitly built for the Order fulfillment and Micro fulfillment centers for their receiving stations and shipping stations to capture parcel dimensions for shipping and master data management purposes.
Our goal is simple. We want to create a range of Automated Dimensioners which is as simple and easy to use as a label printer for Warehouses,
order fulfillment centers, Shippers, and Carriers.
We achieved it by creating the world’s first and only Dimensioning as a service and incorporating additional domain-specific features and cloud based Intelligent Dimensioning Platform – the vMeasure Forge that can make dimensioning a seamless activity.
vMeasure Range of Automated package Dimensioners is built by VisAI Labs – the Edge AI and Computer Vision specialists who focus on bringing computer vision and Machine learning applications into the real world.