Artificial intelligence platforms are primarily deployed in the retail sector to enhance customer experience, analyze buying behavior, boost RoI, and optimize supply chain management. For instance, Microsoft formed a partnership with Flipkart, where Flipkart would take advantage of cloud platform Microsoft Azure with AI capabilities to expedite the process of digital transformation as well as to provide better customer experience. Moreover, retail companies are focused towards increasing operational efficiency using artificial intelligence platform. The various capabilities offered by AI technology through a platform such as visual search, speech recognition, and text recognition are playing a significant role in predicting future as well as in the revenue generation process. For instance, visual search embedded in the AI platform helps users in finding products where the users can upload the image to search the required product. Apart from that, predictive models that are built using historic data are used to predict future behavior of the users. With these application areas, use of artificial intelligence platform is playing a crucial role in the retail sector, and retailers are deploying it to get the competitive advantage to sustain in the competition.
Artificial Intelligence Platform in Retail and eCommerce
IBM Watson suite enables organizations to combine AI into their applications, and also helps with data management in the cloud. It offers the PowerAI platform, which provides various AI capabilities. These capabilities negate the need for developing AI solutions. Moreover, the PowerAI platform provides AI-rich capabilities, such as deep learning, which allows organizations to fulfill the technological requirements. The IBM Power Systems software combined with the PowerAI platform allows enterprises to deploy PowerAI with deep learning capabilities for enhanced performance.
AWS Managed ML Platforms offers data scientists and developers a way to create models without investing in infrastructure management. Amazon ML removes the need to learn complex technologies and ML algorithms, along with visualization tools and wizards to help guide in the process of building ML models. Apache Spark on Amazon EMR is an open source distributed processing system, which focuses on big data workloads. It offers various features, such as enhancing the performance and enabling the quick development of applications, such as libraries, to help develop applications for various uses cases. Amazon Web Services also offers intelligent services to build application, such as Amazon Lex, Amazon Polly, and Amazon Rekognition. The services are used to turn text into speech, as well as, help study the images to recognize faces, objects, and scenes.
SAP Leonardo Machine Learning platform is created on SAP Cloud Platform and comprises the capabilities of ML to help organizations in finding connections and patterns in the data. It comprises services that offer the capabilities to learn from data as well as gain knowledge. Moreover, it allows taking advantage of the intelligent capabilities for developing enterprise applications and removes the need for data science skills in the process. The SAP Leonardo ML platform offers the basis to create and manage intelligent applications under a common infrastructure. Moreover, SAP offers SAP CoPilot, the virtual assistant designed to help customers. The virtual assistant analyzes the unstructured speech to offer users with relevant data.
Salesforce Einstein suite offers data modeling, preparation, and infrastructure processes, which can be embedded into predictive models and applications to benefit from capabilities. The Einstein platform services offer the basis to create AI-driven applications by making available, the capabilities of image recognition and NLP to the users. The Marketing Cloud Einstein allows the marketers to take benefits of tools, such as Predictive Scoring, Predictive Audiences, and Automated Send-time Optimization, to analyze the target audience, contents, and channels while designing campaigns. Furthermore, the Analytics Cloud Einstein helps in the discovery of future patterns for business processes and provides insights from a large chunk of data. These platforms remove the need to build algorithms and mathematical models. Moreover, by using Service Cloud Einstein, enterprises can achieve intelligent, automated, and predictive customer engagement experience. The Community Cloud Einstein offers customers a way to find the information and offers recommendations about the contents.
SAS Visual Data Mining and Machine Learning offers an innovative solution that combines the most advanced analytics, data prep, visualization, model assessment and model deployment in a single environment. It also supports programming from popular open source languages. This reliable, collective environment produces desired outcomes, helping improve organizational procedures and discover new opportunities for growth.
Oracle provides readymade AI cloud applications with intellectual features that drive better business outcomes. It offers a full suite of cloud services to build, deploy, and manage AI-powered solutions. It automate security patching, backups, and improve database query performance, which eliminate human error and repetitive manual tasks. so organizations can focus on higher-value activities.
DataRobot automated machine learning platform provides knowledge, experience, and best practices to deliver unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot allows users of all skill levels, from business people to analysts to data scientists, to build and deploy highly-accurate predictive models in a fraction of the time of traditional modeling methods.
Faculty Platform allows to manage and schedule model training and execution pipelines natively, and deploy models into staging and production with one simple workflow. It use a browser or command line interface that integrates with favourite IDE and version control systems for easy interface customisation.
Vital AI Development Kit (VDK) offers a suite of software to reorganize the flow of data across application architecture and integrate with analytical frameworks using the Vital Service API. The key tool is VitalSigns, which provides a consistent data model used by all software modules.
Msg.ai Artificial Intelligence respond quickly to issues that are repeatable, while enabling human agents to focus on high-impact work. It ensure a best experience to customers whenever there is a an issue, a question or a need. It can collaborates with human agents to offer high-quality resolutions to customer queries on email, mobile, and chat.
BigML offers robust engineered Machine Learning algorithms proven to solve problems by applying a single, standardized framework across company. It reduces the dependencies on many disparate libraries that increase complexity, maintenance costs, and technical debt in projects. BigML enables unlimited predictive applications across industries. It automatically adjusts resources to seamlessly meet computational needs in a cost-effective manner, while abstracting away infrastructure concerns from end-users.
Figure eight generates high-quality customized training data and automates business process with easy-to-deploy models. It offers products and services like self-driving cars, intelligent personal assistants, medical image labeling, content categorization, customer support ticket classification, social data insight, CRM data enrichment, product categorization, and search relevance.