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Explainable AI Principles and ModelOps Solutions

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.

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Cloud-Native Agnostic Platform

Prevent vendor lock-in and enable seamless AI infrastructure deployment and management

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Principles for Explainable AI Development

Explainable AI promotes promote responsible AI Adoption, and embedding ethical principles into AI-based applications

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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.

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Build, Deploy and Manage Explainable AI Applications at Scale

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End-to-End Machine Learning Orchestration

Minimize the complexity of the AI lifecycle, enable Automated Pipeline Orchestration, and build AutoML capabilities.

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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.

Explainable AI Offerings

Explainable AI reveals the direction and scope of explainability that XenonStack incorporates into our AI solutions

Operationalize Explainable AI with trust and confidence

Bring your AI models into production and ensure that AI models are interpretable and explainable

Model Visualization Solutions Enabling Explainability for ML

Helping Organizations to build a Framework for Explainability

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Enterprise Technology

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Banking and Finance Sector

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Healthcare

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Education

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Transportation

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Key Enablers

Enablers for Accelerating Digital Transformation

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Enterprise AI

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Big Data Engineering

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Data Visualization

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Introduction In the recent time generative AI has become a revolutionary technology which has impacted all sectors of existence, such as software development, healthcare, transport and navigation and...

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What is IoT Analytics Platform? IoT analytics is a valuable application designed to decipher the extensive data generated by interconnected IoT devices. Coined by Kevin Ashton, a cofounder of the...

Introduction To Generative AI in Log Analytics Log data is a goldmine of information, constituting a significant aspect of big data. The sheer volume and diversity of logs generated by systems,...

The Future of Augmented Analytics and Its Advantages In the year 2022, the global augmented analytics market achieved a valuation milestone, reaching USD 15.84 billion. Projections indicate a notable...

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Introduction to Microservices Testing Microservices testing is a strategy used to ensure the functionality and performance of individual services within a microservices architecture. This approach...

Infrastructure as Code (IaC) tools that promote the best practices are necessary to make the process of building and configuring the infrastructure more competitive and effective, reducing the costs...

Introduction In the ever-evolving world of software development, DevOps teams are always looking for innovative ways to make their work more efficient and deliver top-notch software faster. In this...

Introduction to Data Visualization Data Visualization is a method of translating raw data into visual forms like charts, graphs, and maps. It has quickly become famous for publishing information on...

What is user Experience Testing? User experience testing is having actual people engage with a website, app, or other product you've created and analyzing their behaviours and reactions. It is a...

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Clutch Review for Big Data and Cloud Consulting XenonStack Joins Clutch’s Research of Best Big Data and Cloud Consulting Companies. Read more about the review XenonStack Big Data Analytics Consulting...

Introduction The transition to 5G is not just a small step forward; it's a groundbreaking move that revolutionizes the entire spectrum of wireless communication. While much has been said about public...

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Introduction Large Language Models, or LLMs, have emerged as powerful tools for the industry that have the potential to transform a variety of sectors. They can make inventive create text, interpret...

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Introduction to Cloud Native Applications Applications that are developed and deployed using cloud-based technologies are known as Cloud-Native Applications. They are hosted and managed in the cloud....

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Artificial Intelligence Insights and Use Cases

Benefits of Generative AI in Energy Sector

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Benefits of Generative AI in Energy Sector

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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

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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.