Deep Connect

SandLogic Introduces Speech-to-Text Accuracy Benchmark

SandLogic's CORE now supports Intel's OpenVINO

Customer who is into automotive component manufacturing wanted to build a multi-modal distress recognition system for passenger transportation industry.

Our customer who is into manufacturing of various automotive components wanted to build AI framework for their upcoming Camera line & they want to monitor Driver Behavior with respect to unsafe driving etc.

Our customer who is into manufacturing of various automotive components wanted to build AI framework for their upcoming Camera line & they want to monitor Driver Behavior with respect to unsafe driving etc.

Customer wanted us to build an end-to-end model that enables marking and tracking a person `or group of persons on a live video stream or multiple streams.

Customer wanted us to build an end-to-end model for recognizing faces that can run both on Cloud and Devices powered by Qualcomm S603 & S605 chipsets.

The customer wants the AI engine to take the images of the pallets during various stages of the inbound, put-away and outbound processes, and detect the labels of interest, decode the values of the labels (bar and QR codes) and provides it to the inventory management system.

The customer is in the Cold storage and Warehousing business and would like to resolve the pain points during handling of the inbound pallets.