Utilize the power of AI to transform business for human interaction.
“Alexa, what is TensorIoT?”
“TensorIoT develops innovative solutions to transfer, transform and extract data tailored to your company needs with personalized interaction through AI technologies.”
Successfully handoff Lex Language Model and Lambda code developement teams. Replace and Interactive Voice Response (IVR) system with Lex bot to optimize routing calls.
Enable scale capabilities of a conversational interface and enhanced customer experience.
Conversational AI meets ML
Artificial Intelligence goes hand in hand with Machine Learning. Chatbots are evolving in capability and complexity. Creating a bot today requires a team of content owners, engineers and data scientists to work together.
How TensorIoT Harnesses the Power of ML
Make the most of your data by learning valuable insight or creating an interactive digital experience for your users. TensorIoT knows that no two clients are alike, so we look to blend analytics, design and engineering to meet the current and future needs of our customers. We bring our deep expertise, drive and passion to solve your unique needs. Some of our offerings include:
Accurately predict outliers.
Applications range from intrusion detection (identifying strange patterns in network traffic that could signal a hack) to system health monitoring (spotting a malignant tumor in an MRI scan), and from fraud detection in credit card transactions to fault detection in operating environments.
Built using MXNet in Amazon Sagemaker, our domain specific supervised and unsupervised models may be retrained with your data.
Detect and Localize objects.
Fast and accurate systems for object detection and localization are necessary for autonomous vehicles, smart video surveillance, aerial image analysis, facial detection and various people counting applications.
SSD and Faster R-CNN based models built in Amazon Sagemaker to rapidly re-train using your specific data.
Improve customer experience and CTR.
Applications range from multiple classification, regression, and ranking use-cases. This may be added into real-time bidding systems or intergrated into the customer workflow on websites and apps.
The model uses XGBoost to run a real-time predictor and return a scored prediction result.