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.

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.

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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

Productionizing Machine Learning Models with Containers

With Automated Model Containerization Solutions, Companies can reduce the Complexity of Manual Orchestration and govern machine learning models in production.

ML Health Monitoring

Automated Monitoring solutions empower Enterprises to understand and Proactively identify Performance and Operational Issues.

Manage the Full Lifecycle of ML in Production

Akira AI enables Enterprises to efficiently streamline Machine learning cycles with solutions for automated deployment and administration of machine learning models.