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Domino’s Spring 2025 Release Supercharges Enterprise AI Delivery with Speed, Scale, and Trust

(PRNewsfoto/Domino Data Lab)

Domino Data Lab, provider of the leading Enterprise AI Platform trusted by the world’s largest AI-enabled enterprises, today announced its Spring 2025 Release — a major platform update that helps enterprises ship trusted AI products faster. The release introduces a unified system for productivity, governance, and delivery—turning fragmented initiatives into an AI factory for trusted, repeatable outcomes. It also announced Zero-to-AI, a new service offering designed to catalyze proven AI cultural change within enterprises.

Also Read: The Role of AI in Automated Dental Treatment Planning: From Diagnosis to Prosthetics

AI Delivery Is an ROI Bottleneck

AI implementations are scaling fast, but business impact still lags. While 88% of organizations say they’re better at moving models to production, nearly 60% of them expect less than 50% ROI, according to Domino’s 2025 REVelate report.

“Getting models into production is no longer the hard part, it’s realizing business value at scale,” said Heidi Lanford, co-founder at NavAlytix and former CDO at Fitch Group. “That requires a system that connects experimentation to governed, repeatable delivery. Domino provides that foundation.”

This shift in focus—from deployment to scaled, governed impact—requires new infrastructure and discipline across the AI lifecycle.

“We’re redefining the AI lifecycle to make it faster, safer, and more efficient,” said Nick Elprin, co-founder and CEO of Domino Data Lab. “Our Spring 2025 Release gives enterprises an AI factory for turning experimentation into impact — with built-in governance and automation to deliver AI products at scale.”

With these challenges in mind, Domino’s Spring 2025 Release introduces new capabilities that reset every stage of the AI lifecycle — from experimentation to compliance to enterprise-scale deployment.

From Friction to Flow: How Domino Is Resetting the AI Lifecycle

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Boost Productivity Without Burdening IT: Data science teams lose time to restrictive tools and infrastructure overhead. Domino’s Spring Release removes these barriers with new capabilities that accelerate development, increase reuse, and deliver business value—without adding burden to IT. Teams can now:

  • Accelerate development by connecting local tools to Domino workspaces—combining the flexibility of familiar environments with scalable compute, reproducibility, and enterprise-grade governance.
  • Deliver instantly on the last mile of AI with interactive apps that bridge the gap between technical work and decision-making, so business teams act faster on AI-enabled insights without sacrificing governance or control.

Built-In Governance, Not Bolt-On Bureaucracy: Typical AI governance often slows AI delivery and creates manual overhead. Domino’s Spring Release changes that—enhancing the governance built into everyday workflows to accelerate the governance lifecycle, reduce risk, and scale with confidence. With this release, organizations can:

  • Cut audit prep time by 70% with automated checks that track policy compliance in real time—using the right metrics, on the right artifacts, without manual effort.
  • Accelerate model validation and review with structured findings and conditional approvals that streamline collaboration, flag risks, and ensure full traceability in Domino.
  • Empower risk management teams to create and manage governance policies through an intuitive, visual builder interface that bridges risk and data science stakeholders to build governance that goes beyond good intentions.
  • Automate policy enforcement by blocking premature model operation with new Gated Deployment capability.

Control Costs While Scaling AI Delivery: The Spring Release strengthens Domino’s value for IT and infrastructure teams by helping align AI workloads with performance, data locality, and cost objectives. Enhancements include:

  • A new Cost Center Dashboard to track compute costs by user, project, or workload. Along with Domino’s budget alerts, this new capability helps teams prevent waste and justify infrastructure spend.
  • Domino Volumes for NetApp ONTAP, now generally available, gives data scientists on-demand access to enterprise data—while IT retains control with trusted ONTAP governance and hybrid infrastructure management.
  • Domino is now a part of the NVIDIA Enterprise AI Factory validated design, providing IT teams confidence to scale Domino’s own AI factory architecture with NVIDIA-optimized, full-stack infrastructure.

Several Spring Release capabilities — including Domino Apps and enhanced compliance workflows — debuted at Domino’s life sciences–focused RevX event on May 20. In one life sciences use case, teams can use these latest platform capabilities to accelerate clinical trial recruitment by predicting patient eligibility from large, multi-source datasets. Such innovations can serve as a blueprint for scaling AI-driven breakthroughs across industries.

Also Read: Unpacking Personalisation in the Age of Predictive and Gen AI

Zero to AI: Accelerating the Path from Use Case to Impact
Domino also announced Zero to AI, a new service offering that helps enterprises industrialize AI by fast-tracking high-impact use cases from pilot to production. It combines Domino’s architectural expertise, implementation support, and training, to deliver customers scalable, audit-ready AI solutions. With Zero-to-AI, customers get:

  • Application of Domino’s proven approach to deliver production-ready AI in record time—creating reusable foundations for future projects.
  • Template-first development inspired by software engineering best practices, with modular pipelines, reusable code, and UIs that accelerate delivery.
  • Audit-ready architecture with versioned, testable components that ensure every deployment is scalable and compliant.

[To share your insights with us, please write to psen@itechseries.com]

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