Building AI-enabled Edge Solutions

Deploy AI models developed and trained in the cloud and enable Distributed Cloud Intelligence.

Akira AI - Bringing AI at the Edge

Building Edge AI-based solutions for facilitating faster processing, computation, and effective data storage.

  • Edge Deployment Strategy
  • AI-Enabled Digital Twins
  • Deploy Machine Learning models using existing data

Powerful Solutions & Features from Data Engineering Platform

Akira AI Platform enables you to Automate the infrastructure to train and deploy Deep Learning Models on Public Cloud as well as On-Premises.

  • Deploy any model in minutes
  • Advanced Monitoring
  • Autoscale to match any demand
  • Empower your data scientists
  • Optimized GPU usage

Enabling Low-latency Edge Computing

With Edge AI-enabled Solutions enterprises can run AI models at the edge that assists in making decisions quickly without relying on network connectivity.

Enhanced Performance

Gain real-time visibility into the performance of all deployed models and facilitate the model’s predictive performance.

Reduced network traffic

With AI at the Edge, limited data is transferred from local devices to the data center, i.e., transferring only required information, thereby decreasing network bandwidth issues.

Edge Deployed Digital Twin

Digital Twin at the Edge can help Enterprises to lower Analytics latency and help to facilitate faster execution of processes.

All in One Place

Multi-Platform Integration Solutions

Akira AI provides Integrations with leading Libraries, Platforms, and Tools..

  • 10+

    Data Sources & Connectors
  • 10+

    Programming Languages
  • 6+

    Popular Framework
  • 6+

    Intelligence & Analysis Tools

Blog & Use Cases on Data Engineering

Read our Thought Leadership Driven content on Best Practices, Implementation and Use Cases of AI For Engineering.

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  • Use Cases arrow_right_alt

Blog
Blog

Influential and Informative Deep Learning and AI Blogs

Here Jenkins shall be used in order to create a continuous integration pipeline for NodeJs applications.

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Documentation
Blog

Build and Deploy Continuous Delivery Pipeline with Jenkins

Automate analytical model building, using algorithms that iteratively learn from your data.

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Use Cases
Use Cases

Provide Envied Customer Engagement

Deploy applications that process massive amounts of events in real time.

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Documentation
Use Cases

Deliver Better Analytics Recommendations

Automate analytical model building, using algorithms that iteratively learn from your data.

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