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OpenText Aviator Delivers Generative AI Use Cases Beyond CX

OpenText Aviator Delivers Generative AI Use Cases Beyond CX

The News: OpenText Corp. announced in early August opentext.ai, a new strategic approach to advancing how customers can solve complex problems by applying AI and large language models (LLMs) with its OpenText Information Management software. As part of this strategy, the company formally launched OpenText Aviator, a family of “practical and trusted” generative AI capabilities within the company’s Information Management Cloud Editions, which include Content Aviator, Business Network Aviator, IT Operations Advisor, DevOps Aviator, Cybersecurity Aviator, and Experience Aviator. These tools allow organizations to reap the benefits of generative AI beyond content and customer experience (CX) use cases, which have dominated many vendors’ roadmaps.

For the full Press Release announcing OpenText Aviator, please click here.

OpenText Aviator Delivers Generative AI Use Cases Beyond CX

Analyst Take: OpenText Corp. announced its new opentext.ai strategy in early August, which is focused on applying AI and LLMs within the company’s OpenText Information Management software to solve complex problems, via a suite of solutions named OpenText Aviator. According to OpenText, its Aviator product line is a key part of the company’s strategy of making AI a key priority for the company in FY 2024.

One of the key strategic elements that sets OpenText apart from other enterprise software vendors is its comprehensive approach to deploying generative AI, focusing not only on front-end, worker productivity enhancements, including content and CX use cases, but also focusing on addressing more complex back-office processes and infrastructure, encompassing business connectivity, IT operations, DevOps, and cybersecurity. OpenText management believes that generative AI is well suited to impact a variety of functional and corporate areas, and its Aviator suite of capabilities reflects that vision.

Driving Improvements Across Back-Office Use Cases and Systems

Many of the initial use cases for generative AI are incorporated into OpenText Aviator, such as Content Aviator, which is deployed within OpenText Core Content, allowing users to interact with knowledge systems via conversational search experience, letting them more efficiently and easily access stored knowledge, interact and manage structured and unstructured data at scale, and easily automate intelligent workspaces. In addition, OpenText Experience Aviator, which is deployed within OpenText Exstream, is designed to help transform customer communications and elevate digital experiences through advanced LLMs and generative AI for personalized content creation.

That said, the other tools within the OpenText Aviator family are particularly interesting, as they address the back-office processes and systems that are often critical for driving efficiency, scalability, and profitability, but have traditionally been more challenging to interact with through traditional interfaces and processes. OpenText announced the following tools, which will integrate generative AI:

  • OpenText Business Network Aviator: within OpenText Business Network Cloud Foundation, revolutionize business connectivity, identify anomalies in trading data, automate data mapping that enables exchange, and support intelligent decisions.
  • OpenText IT Operations Aviator: within OpenText SMAX, automate the full IT Operations value chain, redefine Level 1 Business Support across IT, HR, and Sales, and discover intelligent automation using generative AI.
  • OpenText DevOps Aviator: within OpenText ValueEdge, elevate developers around the world, enhance all aspects of application delivery, and get actionable insights into digital value stream KPIs.
  • OpenText Cybersecurity Aviator: within OpenText BrightCloud, gain contextual threat intelligence via API cloud services and react to threats in real time.

By leveraging generative AI across these departments and use cases, organizations can unlock cost savings and improve efficiencies. Generative AI tools make it easier to capture, classify, and assess data that can be used to automate routine processes, and generate new insights quickly. Because the OpenText Aviator tools are grounded with company- and process-specific data, the risk of hallucination, toxic, or inaccurate results is minimized, thereby helping to drive ROI.

Poly-Model Approach to Provide Flexibility to Customers

OpenText Aviator is using what it is calling a poly-model approach to deploying LLMs on a company’s secure, private data. The company will allow customers to apply LLM features within apps or through cloud API services, and connections across multi-cloud environments, enabling better analytics, search, and decision-making. The company has announced that customers will be able to run LLMs privately with OpenText, using vetted LLMs on your data, and will allow multiple LLMs to be used, based on the specific use case and desired outcomes.

Pricing Based on Delivering More Value

On the company’s FY 2023 earnings call, OpenText said its six OpenText Aviator products will be available for sale by Q2 2024. On the earnings call, CEO Mark J. Barrenechea discussed the strategy around its pricing model, which will encompass both a per-user, per month approach, with pricing likely within the $10-$30 range (falling in line with competitor offerings from Microsoft), as well as making some products available on a consumption model. This is a smart approach, as it allows OpenText to capture both light and heavy users of the technology, while balancing uptake and adoption against profitability and costs.

In addition, OpenText will also deliver to private cloud customers a new Professional Service offering to help set up a private LLM, using out-of-the-box Aviator features or customers’ own private cloud environment for their information. The offering is designed to provide company-specific guidance on incorporating generative AI using the data layers they operate in, matching those up with the right models, engineering the right way to extract that data, and then operationalizing the entire process.

Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.

Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.

Other Insights from The Futurum Group

OpenText Reports Strong Q4 and FY 2023 Earnings, Driven by Cloud and ARR Growth

OpenText Further Invests in Europe to Fuel Continued Growth

OpenText FY Q3 2023 Earnings Rise to $1.24 Billion, Up 41% YoY

Author Information

Keith has over 25 years of experience in research, marketing, and consulting-based fields.

He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.

In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.

He is a member of the Association of Independent Information Professionals (AIIP).

Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.

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