An artificial intelligence tech company based in Costa Mesa, California, Veritone has launched the latest version 3.0 of its operating system, specifically designed with unique capabilities to deploy enterprise artificial intelligence (AI) and machine learning (ML).

The company has introduced multiple sets of new features and enhancements in its aiWARE operating system. The newly launched aiWARE 3.0 version comes with upgraded performance, improved app support, workflow development, and integration enhancements.

The latest operating system, aiWARE 3.0 version, is specifically designed for AI, ML, and IT developers to quickly receive custom and turnkey AI and ML solutions without any assistance from machine learning expertise.

“As enterprises begin to use multiple AI models and systems to extract and understand growing data volumes, the need for enterprise AI platforms is increasing,” says Founder of Deep Analysis and Co-Author of Practical Artificial Intelligence: An Enterprise Playbook, Alan Pelz-Sharpe. “Veritone aiWARE has the potential to open up new possibilities to use AI in a coordinated manner across enterprises, along with expanded applications for digital transformation.”

With a simplified and cost-effective installation and administration process, the latest OS version helps to reduce DevOps requirements whether the customer’s deployment solution takes place in the cloud or on-premises.

The company stated that the scalability of the OS has increased, whether from a single laptop, CPU, or cloud-scale deployment. The enhancements include reduced job input/output latency (near-real-time) and multi-threaded processing control for multiple tasks within a job while avoiding blocking tasks that clog the processing pipeline.

With the new aiWARE OS Notification Center, the aiWARE 3.0 exposes OS and application-level events in a single location and format that enables better visibility of a task’s completion or any changes made, new data available, and messages received.

The Flow Center of aiWARE OS permits users to manage, browse, and open Automate Studio flows and templates from the operating system. As any aiWARE application can call the Automate Studio flows, it can add applications with different AI engines and system integrations and potential aiWARE use cases across the enterprise.

The following are some of the Automate Studio low-code workflow and integration tool improvements:

  • Production debugging, flow version control, and easy flow access from any aiWARE application make developing and deploying flows easier.
  • Faster AI model performance within Automate Studio enables in-process use cases requiring event-driven, near-real-time, intelligent automation.
  • Ease of application integration can trigger cognitive flows from applications by pushing data to an HTTP endpoint, whether in test or production.
  • A new set of GraphQL APIs allows developers more granular control over the lifecycle of their flows, whether to configure, create, run, or debug.