News

AvePoint Offers Foundation for Building AI Data Models with New Opus Product

• By Kurt Mackie
• 10/11/2023

AvePoint Opus is a new artificial intelligence (Al)-based "information lifecycle management" solution, announced this week.

Opus, in conjunction with AvePoint's Maestro product, promises to help organizations automate data classification and records management processes, and ensure that data retention requirements get met. These products are for organizations with a need to address various record keeping and data compliance complexities, such as government and business entities.

Opus works with Office 365 data such as OneDrive files and Teams chats, but other "data estates" are supported, such as Google Docs and Salesforce. It also works with Microsoft Dynamics 365 CRM and SharePoint data. AvePoint, a long-time Microsoft partner, enables support for various "legacy" enterprise content management systems, too.

AvePoint already uses machine learning solutions for government release management systems and remote proctoring for educational organizations. Its new AI-based Opus product essentially is the "evolution of our cloud records product," explained Dr. Tianyi Jiang, AvePoint's cofounder and CEO, while AvePoint's Maestro does the automated training and content tagging.

Opus' automated records management capabilities can reduce the compliance risks associated with having over-retained data or even deleting data. It can help optimize cloud storage costs, too, AvePoint contends.

However, Opus also will be a foundational layer as organizations build out their own data models for generative AI, Jiang contended.

"Opus is for any company that wants to leverage better data infrastructure so that they can be ready for AI," Jiang said, in a Monday call. "Opus fits into that paradigm. It is no longer just for companies that have dedicated record managers, or companies in regulated industries. It's for companies that actually want to build proprietary AI models and do impactful work."

That foundational layer is needed because using generative AI in its raw form just gives organizations the equivalent of a "smart summer intern" lacking company and industry knowledge, Jiang added.

"We know that in any proper AI project, 80 percent of the workload is actually data management, data processing and data aggregation," Jiang said. "Otherwise, you have a trash-in, trash-out problem when you're building your proprietary data model."

New Jersey-based AvePoint supports organizations having "nuanced and industry-specific capabilities" in both hybrid and multicloud scenarios. Also served are organizations that can't use cloud services directly, or that "want the air gap between their backup data and production in another cloud or another on-prem environment for business continuity purposes," Jiang explained.

Jiang, who has doctorate degrees in machine learning and AI, shared more on what it'll take for organizations to leverage AI in this AvePoint post.

More on the Opus information lifecycle management product is further described at this AvePoint landing page.