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What is OpenText DevOps Aviator?

OpenText DevOps Aviator leverages both generative and agentic AI to significantly improve the software delivery lifecycle, allowing teams to accelerate the processes of application development, delivery, and automated testing. Its integration with the OpenText Core Software Delivery Platform and OpenText Software Delivery Management optimizes workflows, reduces defects, and provides real-time insights that enhance key performance indicators within the value stream. A sophisticated, context-aware AI assistant enables users to ask questions about features, defects, tasks, and tests, delivering precise answers while streamlining the creation of stories or tasks without requiring users to switch between different tools. Furthermore, AI-enhanced test conversion functionalities facilitate the transition from manual tests to automated workflows via codeless methods or Gherkin BDD, and it also generates test recommendations to improve coverage. By analyzing historical velocity data alongside AI-generated insights, the system can forecast delivery timelines for features and releases while raising alerts about potential risks before they can affect deadlines. This holistic strategy empowers teams to operate with greater efficiency and effectiveness throughout all phases of the development cycle, ultimately driving better project outcomes. Additionally, the platform's continuous learning capabilities ensure that it evolves and adapts to new challenges and requirements over time.

What is Autoheal?

Autoheal carefully tracks alerts, identifies possible root causes, and proposes solutions while functioning with human supervision. Furthermore, it completely automates the phase of postmortem analysis. At the heart of this operation is the Production Context Graph (PCG), which acts as a fluid and continuously updated model linking your infrastructure, application logic, production tools, and accumulated knowledge in real time. The PCG is developed through independent assessments of your observability, cloud, and code structures, and it is consistently refined by a Reinforcement Learning system as you interact with Autoheal. Built on this foundation is a Multi-Agent Platform, which comprises specialized agents collaborating with human operators to effectively and safely tackle production issues. For AI agents designed for production engineering to succeed in real enterprise environments, overcoming three critical challenges is paramount. The first is the Context Gap: can the AI effectively understand and operate within the various contexts of my organization? The second is the Trust Gap: is it possible to rely on the AI to adhere strictly to my organization’s security standards? Moreover, addressing these challenges is crucial for achieving seamless integration and dependable performance in intricate operational settings, ultimately ensuring that both human and AI collaboration can thrive harmoniously.

Media

Media

No images available

Integrations Supported

OpenText Aviator
OpenText Aviator Platform
OpenText Aviator Studio
OpenText Experience Aviator
OpenText Service Management Aviator

Integrations Supported

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
Windows
Mac
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Not specified

Company Facts

Organization Name

OpenText

Date Founded

1991

Company Location

Canada

Company Website

www.opentext.com/aviator-ai/devops-aviator

Company Facts

Organization Name

Autoheal

Date Founded

2025

Company Location

United States

Company Website

autoheal.ai/

Categories and Features

Agentic DevOps

Not specified

DevOps

Not specified

Categories and Features

Agentic DevOps

Not specified

DevOps

Not specified

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