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Enterprise Data Management Provider TIBCO has joined a popular group of software developers that make the use of AL and ML easier to understand and deploy for non-data science-trained, line-of-business employees at companies that run it on a regular basis use.
The company in Palo Alto, California, today announced the release of TIBCO ModelOps, which enables businesses to deploy AI models faster and to scale to keep pace with the pace of their sales activity. This addition to TIBCO’s analytics portfolio helps users build their models and scale cloud-based analytical model management, deployment, monitoring and management.
ModelOps is format agnostic and supports all common model formats, including API-based models in any cloud service or on-site, Mark Palmer, TIBCO SVP of engineering, told VentureBeat.
“The way we approach it is that we use low-code / no-code tools, cloud-based architecture; we accept any AI model, which is quite important because some of the platforms prefer their own author environments, ”said Palmer.
Building AI models that are effective can be time consuming and tedious. ModelOps addresses the need for speed in the implementation of AI and draws on TIBCO’s 25 years of experience in data science, data visualization and business intelligence. It helps AI teams confront common deployment hurdles, such as applying application analysis, identifying and mitigating bias, and transparency and manageability of an algorithm’s behavior within business-critical applications.
The open-standard platform enables businesses to deploy and manage model pipelines directly in production environments, Palmer said.
“While 92% of businesses in 2021 generally spent more on data science compared to previous years, only 12.1% deployed it on a scale,” Palmer said. “We have designed a system that places self-service access to computer science firmly in the hands of teams, including business users. It enables decision-making teams to choose the algorithm they want, work from any cloud service and run it safely, securely and on a scale. It’s a bold move to enable business users to take AI out of the lab and on the go.
ModelOps fits right in with 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,” InSoo Ryu, technical leader, SK Hynix said in a media advisory . “This is the right platform to scale our computer science efforts with a more controlled, process-oriented approach to computer science operationalization.”
A recent survey of its clients confirmed to TIBCO that it is no longer uncommon for organizations to manage hundreds – even thousands – of analytical models and workflows, Palmer said. ModelOps allows any authorized business user, data scientist, analyst or IT user to manage and deploy thousands of models in production with full management and management 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), Talent and several more, according to Gartner Research.
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