Qubrid AI Expands GPU Cloud and Previews Agentic Workbench for AI Agents

Qubrid AI unveils Version 3 of its AI GPU Cloud, featuring smarter model tuning, auto-stop deployment, and enhanced RAG UI—all designed to streamline AI workflows. The company also teased its upcoming Agentic Workbench, a new toolkit to simplify building autonomous AI agents. Along with App Studio and data provider integration, Qubrid is positioning itself as the go-to enterprise AI platform for 2025.
Qubrid AI Expands GPU Cloud and Previews Agentic Workbench for AI Agents
Image Credit: Qubrid AI

Qubrid AI, a leader in enterprise AI solutions, today announced a major update to its AI GPU Cloud Platform (V3), along with a robust roadmap featuring App Studio and the forthcoming Agentic Workbench – a transformative toolkit designed to simplify the creation and management of intelligent AI agents.


These updates reinforce Qubrid AI’s mission to democratize AI by enabling faster, smarter, and cost-effective AI development for enterprises, researchers, and developers. Users can access the new platform by visiting https://platform.qubrid.com

New Capabilities in AI GPU Cloud Platform V3:

  • New UI: A redesigned interface delivers an intuitive and seamless user experience, simplifying navigation and improving workflow management.
  • Model Tuning Page Optimization: Now directly accessible, this page allows users to select base models, upload datasets (CSV), configure parameters, and fine-tune models – all in a few clicks.
  • Chat History in RAG UI: Enhances the Retrieval-Augmented Generation experience by displaying past chat interaction – critical for debugging and context-aware improvements.
  • Auto Stop for Hugging Face Deployments: Enables users to automatically shut down deployed model containers after a defined duration, improving GPU utilization and reducing cost.

What’s Coming Next:

  • App Studio: A powerful, user-friendly workspace to design, prototype, and launch AI-powered applications within the Qubrid AI ecosystem.
  • Agentic Workbench: A toolkit purpose-built for developing and scaling AI agents that can autonomously perform tasks, make decisions, and adapt over time.
  • Data Provider Integration: Native integration into popular industry data providers solutions that allows easy access to proprietary data from GPU compute.

Empowering AI Innovation with Open Cloud Architecture

Qubrid AI’s Open Cloud architecture provides unmatched flexibility for Business Users, Product Managers, AI researchers and data scientists. By supporting popular open-source AI models and compatibility with Jupyter notebooks, the platform allows users to bring their own models, tools, and workflows while still benefiting from Qubrid’s high-performance GPU infrastructure.

No-Code Platform for Rapid AI Development

Qubrid AI’s no-code environment empowers both technical and non-technical users to build, train, and deploy models without writing a single line of code. With drag-and-drop interfaces, pre-configured templates, and guided workflows, users can go from idea to production-ready AI solutions in record time, dramatically shortening the innovation cycle with AI.

A Message from Qubrid AI’s CTO

“Our mission is to make advanced AI accessible, scalable, and enterprise-ready,” said Ujjwal Rajbhandari, Chief Technology Officer at Qubrid AI. “With this latest cloud release, we’re not just improving the user experience; we’re giving businesses the power to operationalize AI faster and more intelligently. From smarter resource management to frictionless model tuning and future-ready agentic tooling, we’re building the foundation for enterprise AI at scale.”

About Qubrid AI

Qubrid AI is a leading enterprise artificial intelligence (AI) company that empowers AI developers and engineers to solve complex real-world problems through its advanced AI cloud platform and turnkey on-prem appliances. For more information, visit http://www.qubrid.com/

Media Contact – Crystal Bellin
Email: digital@qubrid.com


Recent Content

Huawei’s new AI chip, the Ascend 910D, has raised concerns about Nvidia’s China business, but analysts say it lacks the global performance, ecosystem, and efficiency to compete with Nvidia’s H100 GPU. Built on 7nm technology with limited software support, Huawei’s chip may gain local traction but poses no major international threat—yet.
COAI has endorsed MeitY’s move to address spam and scam communication from OTT apps. While telecom operators follow strict UCC rules, OTT platforms remain loosely regulated. COAI is advocating for uniform cybersecurity standards and clear regulatory roles to ensure user safety, particularly with emerging threats like steganography.
The Open Compute Project (OCP) has launched a centralized AI portal offering infrastructure tools, white papers, deployment blueprints, and open hardware standards. Designed to support scalable AI data centers, the portal features contributions from Meta, NVIDIA, and more, driving open innovation in AI cluster deployments.
In 2025, data centers are at the forefront of AI innovation, balancing the explosive growth of AI workloads with urgent sustainability goals. This article explores how brownfield and greenfield developments help operators manage demand, support low-latency AI services, and drive toward net-zero carbon targets.
There’s immense pressure for companies in every industry to adopt AI, but not everyone has the in-house expertise, tools, or resources to understand where and how to deploy AI responsibly. Bloomberg hopes this taxonomy – when combined with red teaming and guardrail systems – helps to responsibly enable the financial industry to develop safe and reliable GenAI systems, be compliant with evolving regulatory standards and expectations, as well as strengthen trust among clients.
A focus on efficiency and cost-cutting, often driven by “bean counters” and “time and motion” experts, stifles innovation and leads to job losses, mirroring the current AI discourse. Overemphasis on efficiency, like the race to the bottom, can ultimately harms everyone except the initial beneficiaries. For example, distributed energy where building new infrastructure and expanding into new sectors, like solar, generates jobs in manufacturing, installation, and new industries. Instead of solely fearing job displacement, we should prioritize investment in innovation, education, entrepreneurship, and just transition policies to create a future where progress benefits all through job creation. I advocate for strategic investment to build the future, instead of just shrinking the present.
Whitepaper
Explore RADCOM's whitepaper 'Unleashing the Power of 5G Analytics' to understand how telecom operators can drive cost savings and revenue with 5G. Learn about NWDAF's role in network efficiency, innovative use cases, and analytics monetization strategies. Download now for key insights into optimizing 5G network performance....
Radcom Logo

It seems we can't find what you're looking for.

Download Magazine

With Subscription

Subscribe To Our Newsletter

Scroll to Top