TIBCO gets started with new AI model implementation platform

Enterprise data management provider TIBCO has joined a trending group of software developers using AL and ML easier to understand and implement for non-data science-trained, line-of-business employees at companies that use it regularly.

The Palo Alto, California-based company today announced the release of: TIBCO ModelOps, which enables companies to deploy AI models faster and at scale to keep up with the pace of their sales activities. This addition to TIBCO’s analytics portfolio helps users build their models and scale for cloud-based analytic model management, implementation, monitoring and governance.

ModelOps is format agnostic and supports all common model formats, including API-based models in any cloud service or on-premises, Mark Palmer, TIBCO SVP of engineering, told VentureBeat.

“The way we approach this is that we low code/no code tooling, cloud-based architecture; we accept any AI model, which is quite important as some platforms prefer their own authoring environments,” Palmer said.

Building AI models that are effective can be time consuming and tedious. ModelOps responds to the need for speed in deploying AI and draws on TIBCO’s 25 years of experience in data science, data visualization and business intelligence. This helps AI teams address common implementation hurdles, such as applying analytics to applications, identifying and mitigating bias, and transparency and manageability of an algorithm’s behavior across mission-critical applications.

The open-standard platform allows companies to deploy and manage model pipelines directly in production environments, Palmer said.

“While 92% of companies overall spent more on data science in 2021 compared to previous years, only 12.1% implemented it at scale,” Palmer said. “We designed a system that puts self-service access to data science firmly in the hands of teams, including business users. This allows decision-making teams to choose the algorithm they want, work from any cloud service, and run it safely, securely, and at scale. This is a bold move to empower business users to take AI out of the lab and onto the road.”

ModelOps is a perfect fit for the company’s users to add managed models to other TIBCO tools, including Spotfire, Data Virtualization and Streaming, Palmer said.

“The ability to quickly deploy, measure and adapt models of any kind – machine learning models, Python code, rules and more – is essential to our success,” said InSoo Ryu, technical leader, SK Hynix in a media opinion. “This is the right platform to scale our data science efforts with a more controlled, process-oriented approach to data science operationalization.”

A recent survey of its customers confirmed to TIBCO that it’s no longer uncommon for organizations to manage hundreds — even thousands — of analytic models and workflows, Palmer said. With ModelOps, any authorized business user, data scientist, analyst, or IT user can manage and deploy thousands of models in production with full management and control capabilities. Users can deploy in the cloud or on-premises, he said.

TIBCO competes in a market that includes Microsoft, IBM, Informatica, Oracle, Denodo, SAP, Amazon Web Services (AWS), Talend and many more, according to Gartner research†