Explainable AI Offerings
Explainable AI reveals the direction and scope of explainability that XenonStack incorporates into our AI solutions
XenonStack Recommends
Improve prediction accuracy with Explainable AI
Explainable AI (XAI) solutions aid in characterizing model accuracy, fairness, transparency, and outcomes in AI-powered decision making. AI explainability also assists a company in taking a responsible approach to AI development.
Cloud-Native Agnostic Platform
Prevent vendor lock-in and enable seamless AI infrastructure deployment and management
Principles for Explainable AI Development
Explainable AI promotes promote responsible AI Adoption, and embedding ethical principles into AI-based applications
AI-enabled Security Solutions
Manage regulatory and compliance requirements, and Mitigate security threats in Real-Time
Explainable Machine Learning (XML) for Model Monitoring
Monitoring, XAI, and other MLOps components must be implemented from the start of the project to allow your team and stakeholders to make better design decisions and catch issues that arise, such as model bias, that KPIs alone can never detect. All industrial-grade Machine Learning (ML) or Artificial Intelligence (AI) systems must have XML or XAI in conjunction with model tracking, versioning, and source control that enable ML teams to understand model behavior across widely varying inputs better, make better decisions, reduce the mean time to resolution when challenges inevitably arise, and mitigate potential risks to the organization or end user.
Build, Deploy and Manage Explainable AI Applications at Scale
End-to-End Machine Learning Orchestration
Minimize the complexity of the AI lifecycle, enable Automated Pipeline Orchestration, and build AutoML capabilities.
Learn more about Machine Learning Pipeline Deployment and Architecture
With Automated Model Containerization Solutions, Companies can reduce the Complexity of Manual Orchestration and govern machine learning models in production.
Automated Monitoring solutions empower Enterprises to understand and Proactively identify Performance and Operational Issues.
Akira AI enables Enterprises to efficiently streamline Machine learning cycles with solutions for automated deployment and administration of machine learning models.
ModelOps solutions to help control and manage the model's usage continuously and metrics including infrastructure monitoring.
Googler Vertex Explainable AI Offers
Vertex Explainable AI provides feature-based and example-based explanations to help users understand how models make decisions.
Amazon SageMaker Clarify Model Explainability
Amazon SageMaker Clarify contains tools to assist in explaining how machine learning (ML) models create predictions.
Azure Explainable Solutions Model Visualization
Enable visualizations to help you see patterns in data and explanations.
Operationalize Explainable AI with trust and confidence
Bring your AI models into production and ensure that AI models are interpretable and explainable
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Cloud-Native Agnostic Platform
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Principles for Explainable AI Development
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AI-enabled Security Solutions
Model Visualization Solutions Enabling Explainability for ML
Helping Organizations to build a Framework for Explainability
Enterprise Technology
Banking and Finance Sector
Healthcare
Education
Transportation
Retail
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Key Enablers
Enablers for Accelerating Digital Transformation
Enterprise AI
Big Data Engineering
Data Science
DevOps
Data Visualization
Serverless
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Introduction to Edge AI Edge AI is a combination of artificial intelligence and edge computing. Locally, algorithms are processed on the machines on the manufacturing line or a nearby server. The...
Introduction to AI and its Ethics Artificial intelligence (AI) is the digital technology that has a major impact on humanity's development. All tech giants are trying to develop cutting-edge AI...
What is IoT Analytics Platform? IoT analytics is an application that helps to understand the huge volume of data generated connected IoT devices. In other words, ‘Internet of Things’ is coined by...
Introduction Before we get started, let us understand some basics. Software testing plays an important role in the life cycle of software development. It is imperative to identify bugs and errors...
Introduction to Snowflake Data Warehouse It is a cloud-based Analytical data warehouse provided as Software-as-a-service. It is ready to use a solution that the user requires to just use it directly...
Overview of Edge AI in Manufacturing Indusrty The manufacturing industry, which deals with machines and automation systems, is one of the major sectors contributing to the global economy. According...
Overview of Predictive Maintenance Predictive maintenance is critical in diverse application areas, such as the manufacturing industry, information, technology, aerospace, heavy-machinery industry,...
Introduction to Internet of Things (IoT) Internet of Things, IoT from its name; it can be guessed that it is referred to as the Internet of everything. It can be regarded as the latest technology...
Overview of Scala Application Scala is an object-oriented programming language. It provides support to functional programming. It also helps to remove bugs in complex applications. In this article,...
Overview Deploying software applications can be complex and challenging, particularly considering the vast number of deployment strategies available. Selecting the right strategy depends on the...
Introduction to DevSecOps and SecDevOps In earlier stages of software development, developers used to build software based on the client requirements and the time given for the development. Other...
Introduction to Business Intelligence Today's businesses increasingly rely on software to perform at peak efficiency and maximize revenue. Business Intelligence (BI) plays a key role in helping...
Introduction to Graph Analytics and Knowledge Graph Graph analytics is a new field of data analytics that helps businesses leverage their model by adopting a variety of its algorithms to identify the...
Introduction to Streaming Data Visualization Streaming Data Visualization gives users Real-Time Data Analytics to see the trends and patterns in the data to take action rapidly. It is the control of...
Overview of Serverless Computing In the past, when developers wanted to host any of their websites, there was the need for a physical data center where their server would run, which is very bulky and...
Introduction to Edge Computing with 5G Thanks to the Internet of Things (IoT), more and more devices are connected, including homes, heating systems, fitness trackers, and vehicles. Edge computing...
What is Java and Kotlin? Java is the native language used by Android, applications that communicate with the operating system and directly use the hardware uses it. This language allows the creation...
Overview In the interlinked world of today, when digital technologies penetrate every part of our lives, trust has become a crucial element in determining how we experience the digital world. Users...
What is Zero trust cyber-security? Zero Trust is a cybersecurity strategy that secures an organization by removing implicit trust and continuously validating every stage of digital interaction to...
What is Machine Learning? Machine learning is an area of computer science that allows computers to learn without having to be programmed directly. Machine learning is one of the most fascinating...
What is Cloud Native Observability? Control theory defines "observability" as the ability to determine the internal states and, accordingly, the behavior of a system only by examining its inputs and...
What is Cloud Governance? It is a set of rules. It applies specific policies or principles to the use of computing services. This model aims to secure applications and data even if located distantly....
Introduction to Cloud Native Network Functions A cloud-native network function (CNF) is a service that executes network functions in software rather than dedicated hardware. Because of the huge and...
Introduction to Product Management Roadmap As a product manager, you might be asked to create a roadmap. This document can take many forms, but it's essentially a plan that details the various stages...
Introduction to Product Development With new products hitting the market daily, the need to develop better products is increasing daily. Factors like industry, product type, features, and others come...
Introduction to Incident Management Tools Incident management tools are software applications that help organizations manage incidents, track and monitor incident response progress, and measure the...
Overview of Storage Class in Kubernetes To understand the concept of storage class in kubernetes, first, we need to understand the volume concept in Kubernetes. In simple terms, kubernetes volume is...
Introduction to Kubernetes We are rapidly moving towards the age of cloud computing, where every organization, small or big, has or wants its resources and data to be available, no matter what region...
What is Kubernetes Operators? Kubernetes is growing day by day, and now every organization is keen to adopt the containerization technology and it's gone so for that it can quickly deploy the ...
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Helping Enterprises develop Cloud Native and AI-First Capabilities
Enablers for Accelerating Digital Transformation
Artificial Intelligence Insights and Use Cases
Benefits of Generative AI in Energy Sector
Benefits of Generative AI in Energy Sector
The Role of Artificial Intelligence in Cyber Security Complete Guide
The Role of Artificial Intelligence in Cyber Security Complete Guide
Artificial Intelligence for Infrastructure Management and Automation
Artificial Intelligence for Infrastructure Management and Automation
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Deep learning
Neural Networks
Model Visualization
Artificial Intelligence
Deep learning
Assisting organizations to undertake necessary measures at the right time by scanning data faster.
Neural Networks
Analysing data using machine perception, classification, or labelling raw input.
Understand the work procedure of Model Visualization and how it quantifies its impact on the business.
Artificial Intelligence
Get detail information about how AI Adoption changes the way of working for all industries.
Leverage Continuous Intelligence Capabilities
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Automate actions to uncover the unknown
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Transform processes to move at market speed
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Accelerate business outcome with more accurate predictions in real time
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