Galileo Optimizes Enterprise–Scale Agentic AI Stack with NVIDIA

The Enterprise AI Challenge

AI agents are swiftly evolving from experimental tools to vital components of business infrastructure. These smart systems are capable of automating intricate workflows, boosting productivity, and revealing new possibilities, provided they consistently adhere to the stringent standards necessary for mission-critical tasks.

Engineering teams across industries face the same core challenge: deploying AI agents that interact with real-world systems requires a level of reliability far beyond what's needed for traditional software. Getting agentic AI right demands both exceptional computational performance and sophisticated evaluation tools working together harmoniously.

The Performance-Reliability Gap

Enterprise-grade agents introduce new levels of complexity. They must make decisions across multiple steps, reason through complex scenarios, and interact with tools and services reliably. This is what makes them so powerful, but also what introduces significant risk when deployed into production environments.

Consider what's at stake: an AI agent making trade decisions in a financial institution or one handling sensitive customer data in healthcare. The potential consequences of hallucinations, reasoning errors, or selecting the wrong tools can be severe.

Bridging this performance-reliability gap requires a two-pronged approach:

1. Accelerated computing purpose-built for AI: Organizations need infrastructure that can handle the full spectrum of AI workloads, from pre-training and fine-tuning to inference.

2. Comprehensive evaluation and guardrails: Teams need to measure, validate, and protect their agents' behavior throughout development and in production.

The Optimal Stack: Galileo with NVIDIA

Galileo's integration in the new NVIDIA Enterprise AI Factory validated design creates a powerful solution for enterprise AI deployment. This full-stack design provides guidance for enterprises to build and deploy their own on-premises AI factory, with Galileo's reliability and evaluation capabilities serving as a critical component of this full-stack solution.

The NVIDIA Enterprise AI Factory validated design supports a wide range of AI-enabled enterprise applications, agentic and physical AI workflows, autonomous decision-making, and real-time data analysis. It features expertly designed NVIDIA Blackwell accelerated infrastructure tailored to enterprise needs, integrating specialized AI software to ensure seamless operation and robust performance. And it’s validated by NVIDIA IT, tapping into NVIDIA’s engineering know-how and partnering with Galileo to help enterprises achieve time-to-value and mitigate the risks of AI deployment.

NVIDIA Enterprise AI Factory: Purpose-Built for Agentic AI

NVIDIA Enterprise AI Factory is designed from the ground up to produce intelligence at scale. It unifies all stages of the AI lifecycle into a seamless, orchestrated pipeline; from data ingestion, to pre-training, fine-tuning, and long-thinking inference.

NVIDIA-Certified Servers with NVIDIA Blackwell accelerated computing provide the foundation for the AI Factory, which delivers unprecedented performance and security for AI workloads. The NVIDIA RTX PRO 6000 Blackwell Server Edition provides universal acceleration for agentic AI workflows, supporting everything from model fine-tuning to real-time inference with exceptional efficiency.

Galileo: De-Risking Agentic AI at Scale

Galileo creates a powerful combination that enables developers to build data flywheels and achieve the high degree of accuracy necessary to build reliable agentic AI.

Our platform enhances the NVIDIA Enterprise AI Factory with three core capabilities essential for production-ready agents:

1. Comprehensive Evaluation: Through Galileo’s integration with NVIDIA NeMo Evaluator, development teams can assess everything from an agent's reasoning capabilities to its tool selection accuracy and contextual awareness. These specialized metrics go far beyond traditional Large Language Model (LLM) evaluations, measuring the specific behaviors that matter for agentic systems.

2. Real-Time Observability: Galileo's observability tools provide deep visibility into agent behavior in production, tracking key performance indicators, and detecting anomalies as they emerge. This creates a continuous feedback loop that feeds directly into the AI data flywheel.

3. Protective Guardrails: Galileo Protect works with NVIDIA NeMo Guardrails to establish robust safety measures with minimal latency, safeguarding against everything from hallucinations to malicious inputs while maintaining compliance.

Creating a Data Flywheel for Continuous Improvement

Together, Galileo and NVIDIA implement a powerful AI data flywheel that creates a virtuous cycle of continuous improvement, all built on NVIDIA Enterprise AI Factory Stack:

1. Data Curation: NVIDIA NeMo Curator works with Galileo's Dataset Analysis tools to produce high-quality training data

2. Model Customization: Fine-tune models using NVIDIA NeMo Customizer while fixing problematic data identified by Galileo

3. Comprehensive Evaluation: Combine NVIDIA NeMo Evaluator benchmarks with Galileo's agentic metrics

4. Protective Guardrails: Implement low-latency guardrails through Galileo Protect and NVIDIA NeMo Guardrails

5. Deployment and Observation: Deploy on NVIDIA NIM with Galileo's agentic observability tools

This systematic approach transforms agent development from an uncertain art to a structured engineering discipline, allowing teams to confidently deploy.

The Real-World Impact

The benefits of this integrated approach are already being realized by organizations building critical agent applications:

• A 10x reduction in evaluation latency for critical agent behaviors

• Higher accuracy in tool selection and reasoning

• Significantly reduced risk of hallucinations and harmful outputs

• Faster time-to-value for agentic applications

For example, in a recent project with Outshift by Cisco, we applied this approach to enhance a Pull Request Coach Agent. The results were remarkable: evaluation latency dropped from 5-7 seconds to just 400ms, while accuracy improved to match or exceed much larger models.

Getting Started

For developers building agents on NVIDIA accelerated computing, integrating Galileo as your reliability platform is straightforward:

1. Set up evaluation: Begin by configuring comprehensive agent-specific evaluations through Galileo's integration with NeMo Evaluator

2. Implement observability: Deploy your agent with Galileo's observability tools to gain real-time insights into behavior

3. Add guardrails: Protect your agent from unwanted behavior with Galileo Protect's integration with NeMo Guardrails

Together, this stack provides the foundation for reliable, high-performance agentic AI that can truly transform your business operations.

Conclusion: De-Risking the Future of AI

NVIDIA Enterprise AI Factory validated design with Galileo's capabilities represents a transformative approach to building agentic AI systems that bridges the performance-reliability gap that has held back wider adoption of this powerful technology.

As AI agents become increasingly integral to business operations, organizations adopting this systematic, measurement-driven approach will be positioned to deploy confidently, knowing their systems have been thoroughly validated and are operating with appropriate guardrails.

To learn more about building reliable AI agents with Galileo and NVIDIA, visit galileo.ai and sign up to try the platform for free.