Solutions & Accelerators

HSC’s Distributed Virtualization Test Framework allows a tester to design his network using GUI based orchestration tool. The GUI based orchestration tool also supports the provisioning of service function chains to define an end to end network service. The framework translates the user provided configuration to OpenStack templates and deploys the network on the infrastructure. The framework supports an easy-to-integrate SDK whose APIs can be called from any proprietary application code base under test.

MQTT (Message Queueing Telemetry Transport) protocol is a widely used transport protocol in the IoT space. HSC’s MQTT Simulator harnesses this protocol to create multiple connections and send message payloads to the IoT service. Not only does it help to handle the payload gracefully but also helps uncover the stability issues before the product or service is introduced in the market.

The Pub-Sub Framework and SDK is used to share live data among independent network entities or service endpoints in near-Realtime. This accelerator is well-suited for sharing internal state, counters and similar monitoring points among virtual network functions running in context of VMs or containers. Using an optional SDN controlled, OVS or OVS-DPDK based virtual data bus, this solution promises real-time data sharing in a distributed deployment. Inter-VM Data is shared over OVS bridge or DPDK compliant OVS bridge using the OVS-DPDK provided para-virtualized virtio PMD.

In today's scenario many networked applications runs on our smartphone. These applications interact with network components over public internet. For some of the applications like video applications, performance and hence the user experience depends upon the performance of the network connectivity.

HSC's Big Data Pipeline for analytics is a high speed distributed architecture that is ideal to use as a core enabler for any system that requires high speed processing and real-time analytics of millions of transactions without data loss. In-fact, some of HSC's solutions, such as OTT Video Delivery, QoE and WiFi Analytics all leverage HSC's Big Data Pipeline.

HSC's AI Chatbot framework allows a developer to quickly create contextual conversations that use NLP to engage with the end customer. Implemented as a wrapper that can connect to multiple chatbot engines, it allows a product developer to write code in a way that the backend engine can be replaced without affecting the core product.

HSC's Mobile Loyalty framework is a Ionic based mobile framework that can be used as an accelerator for developing loyalty apps for retail and hospitality verticals.

HSC's Image and Video Analytics accelerator makes it very simple to perform advanced classifications/identifications of images and videos from cameras or offline video files. Based on APIs, it abstracts out the details of how analytics are done and offers a very simple mechanism to integrate advanced image and video analytics into the customer's application.

HSC's WATAF (Web Application Test Automation Framework) and restTF (Web Services Test Automation Framework) makes the process of web automation much easier and seamless than any off the shelf framework.

HSC's Test Management and Automation Framework (TEMAF)is a powerful and versatile test management and execution framework

HSC's Mobile Application Test Automation Framework (MATAF) is a powerful framework to completely automate mobile deployment and testing.

HSC's Connected Car & Fleet Management Video Analytics is a powerful platform for custom traffic, video and driver analytics, developed using HSC's Video analytics accelerator. This platform is intended for B2B customers and drastically reduces time to analyze videos for infractions.Developed specifically for customers that need fleet/vehicle analytics (such as rental car agencies, taxi/cab services, logistics, etc.), the system comprises of the following key components: Core API layer A powerful API layer that provides simple REST APIs for advanced infraction detections. Cloud Portal A rich UI that is developed on top of the APIs that provides easy reports  Advanced Machine Learning Models ​A flexible machine learning powered layer that has the ability to chain multiple models to detect advanced outcomes Sample Models implemented: Pedestrian Obstruction  Seat-belt less driving Overloaded vehicles Traffic Density Analysis Red light moving violationsSample Views   Pure CSS