TIBCO ModelOps Significantly Improves Efficiency and Flexibility Across the Enterprise with Impactful AI
New Solution Empowers the Enterprise to Embrace AI with Confidence and Speed
TIBCO Software Inc., a global leader in enterprise data, empowers its customers to connect, unify, and confidently predict business outcomes, solving the world’s most complex data-driven challenges. Today, TIBCO announced the release of TIBCO® ModelOps, which enables businesses to deploy AI models faster, from anywhere to everywhere, safely and at scale. This addition to the company’s game-changing analytics portfolio helps customers simplify and scale cloud-based analytic model management, deployment, monitoring, and governance.
Latest Aithority Insights: Detecting, Addressing and Debunking the Hidden AI Biases
“While 92% of firms spent more overall on data science in 2021 compared to previous years, only 12.1% deployed it at scale1. To help organizations realize the value of their AI deployments, we’ve designed a system that puts self-service access to data science firmly in the hands of teams, including business users,” said Mark Palmer, senior vice president, engineering, TIBCO. “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 step to enabling business users to take AI out of the lab and out on the road.”
TIBCO ModelOps addresses the requirement for speed in deploying AI, and draws from TIBCO’s leadership in data science, data visualization, and business intelligence. This aids AI teams in confronting critical deployment hurdles like ease-of-applying analytics to applications, identification and mitigation of bias, and transparency and manageability of an algorithm’s behavior within business-critical applications. The solution enables businesses to deploy and manage model pipelines into production environments efficiently, and in robust ways. The TIBCO ModelOps solution is format-agnostic, supporting all common model formats, including API-based models in any cloud service or on-premises. TIBCO ModelOps makes it easy to add governed models to TIBCO Spotfire®, TIBCO® Data Virtualization, and TIBCO® Streaming, with more to follow. Users looking to employ TIBCO ModelOps in existing environments can take advantage of its format-agnostic and open-standards approach.
AI and ML News: AI: Continuing the Chase for Brain-Level Efficiency
The launch of TIBCO ModelOps is the culmination of TIBCO’s extensive work with customers and partners throughout the design and beta program of TIBCO ModelOps. “As the world’s second-largest memory chipmaker, we have aggressive growth goals as we expand our fabrication capacity. Optimizing the yield of our processes, predicting when problems are about to occur, and fixing them before they occur, is a huge competitive advantage for us,” said InSoo Ryu, technical leader, SK Hynix. “The ability to quickly deploy, measure, and adjust models of any kind – machine learning models, python code, rules and more – is essential to our success. TIBCO ModelOps is the right platform to scale our data science efforts with a more governed, process-oriented approach to data science operationalization.”
A recent survey of TIBCO customers confirmed that it’s no longer uncommon for organizations to manage hundreds – even thousands – of analytic models and workflows. TIBCO ModelOps allows any authorized business user, data scientist, analyst, or IT user to manage and deploy thousands of models in production with complete governance and management capabilities. Users are able to deploy in the cloud or on-premises, highlighting model performance through built-in, customizable dashboards powered by Spotfire®. With TIBCO ModelOps, clients can now move past the worry of unintended negative consequences of failed automation because of complex or poorly managed AI or rules-based models, making it safer to automate based on validated and secure AI models.
AI ML in Marketing: AI and Big Data Analysis Used to Find Brands’ Emotional Connection
[To share your insights with us, please write to email@example.com]