Jul 16, 2025
Introducing Galileo's Agent Reliability Platform: Ship Reliable AI Agents
Conor Bronsdon
Head of Developer Awareness
Conor Bronsdon
Head of Developer Awareness
Building a single agent that actually works is hard. It's not easy to figure out all the failure modes across all the different paths the agent can take. When you have thousands of these agents, how do you ensure they'll be reliable at scale?
That's precisely why we're excited to announce Galileo's free Agent Reliability Platform today, the industry's first comprehensive solution purpose-built to enable trustworthy multi-agent systems.
Agents Are Breaking at Scale
AI agents are transforming how we build applications and have the potential to reshape our economy. From customer support bots handling complex multi-turn conversations to financial agents processing transactions worth millions, agents are taking on increasingly critical business functions.
But here's the challenge: traditional debugging tools weren't built for agents.
When your RAG system fails, you debug a pipeline. When your agent fails, you're debugging an autonomous system that made decisions across multiple tools, reasoned through complex scenarios, and potentially interacted with other agents. The failure modes are exponentially more complicated.
And the stakes are higher. One bad action can expose sensitive data, cost real money, or damage customer relationships. Yet most teams are flying blind, hoping their agents work reliably in production.
Three Core Problems, Three Breakthrough Innovations
1. Observability: Reimagined for Agents
The Problem: Observability in the era of agents is broken. A simple trace view does not cut when you need to untangle the complexities of robust multi-agent systems.
Our Solution: The Galileo Graph Engine
We had to completely rethink the base user experience of observability for multi-agent systems and ensure that it was orchestration system agnostic.
Our Graph Engine can trace different complex agentic paths and seamlessly map multi-agent workflows. Combined with our comprehensive suite of metrics, Graph Engine gives you a holistic view of where things are going wrong.
Key Features:
Framework-agnostic: Works with CrewAI, LangGraph, OpenAI's Agent SDK, LlamaIndex, and more
Graph View: See every branch, decision, and tool call at a glance
Timeline View: Identify execution bottlenecks and performance issues
Conversation View: Debug from your user's perspective
2. Failure Mode Analysis: Automatic Insights
The Problem: Complex agents fail in subtle ways that are notoriously difficult to diagnose. No developer wants to hunt for a needle in a haystack of spans and traces.
Our Solution: The Galileo Insights Engine
Our Insights Engine ingests your logs and metrics, then leverages bespoke evaluation reasoning models to identify failure modes and deliver immediate, actionable insights.
Insights Engine provides specific recommendations for improvement tied directly to the exact span, trace, or component that needs attention. The engine also learns from your specific agent patterns and workflows, providing increasingly relevant recommendations over time. Plus, provide human feedback to further tune the insights to your needs.
Key Capabilities:
Root Cause Analysis: Links errors to exact traces in complex multi-agent systems
Multi-Agent Coordination: Understands how agents interact and where handoffs fail
Tool Usage Optimization: Identifies inefficient tool selection patterns
Actionable Recommendations: Not just what's wrong, but how to fix it
3. Real-Time Guardrails: Protection at Scale
The Problem: When an agent makes a mistake, the consequences can harm your user experience and your brand.
Our Solution: Luna-2 Small Language Models
Our new family of small language models, Luna-2, are purposefully built for real-time guardrails at enterprise scale. Whether you want to evaluate against our suite of out-of-the-box agent metrics or create custom metrics, Luna-2 enables real-time guardrails with millisecond latencies at a fraction of the cost of larger models.
Luna-2 is already helping large enterprises protect their hundreds of agents and process hundreds of millions of queries daily through dozens of guardrails.
Luna-2 Advantages:
20+ sophisticated metrics running simultaneously
Sub-200ms latency even at 100% sampling rates
97% cheaper than traditional LLM-based solutions
Custom metrics fine-tuned for your specific use cases
Real Impact: What Our Customers and Partners Are Saying
MongoDB: "Galileo’s platform helps you build reliable AI systems that enable companies to grow, and ensure developers' trust," said Mikiko Chandrasekhar, Staff Developer Advocate.
Outshift by Cisco: "What Galileo is doing with their Luna-2 small language models is amazing. This is a key step to having total, live in-production evaluations and guardrailing of your AI system," said Giovanna Carofiglio, Distinguished Engineer & Senior Director at Outshift by Cisco.
Agent Metrics + Leaderboard v2
To accompany today's platform launch, we're also releasing the v2 of our AI Agent Leaderboard. The leaderboard leverages our Action Completion and Tool Selection Quality agent metrics to evaluate models across domain-specific enterprise tasks covering banking, healthcare, insurance, investments, and telecoms.
This isn't just academic benchmarking. These are the real-world scenarios your agents face in production, measured with the same metrics now available in our platform.
→ Explore the Live Leaderboard
The Market Moment
The timing couldn't be more critical. Capgemini research shows:
10% of organizations already use AI agents
50%+ plan implementation in 2025
82% plan integration within three years
Yet Gartner predicts 40% of agentic AI projects will be canceled by the end of 2027 due to reliability issues.
With our Agent Reliability platform, your project doesn’t have to be one of them.
Get Started Today
We are very excited to announce that all of these features are available starting today. You can start for free at galileo.ai.
This is just the start. We are obsessed with this critical problem of agent reliability, and stay tuned for much more from us over the coming months.
What You Can Do Right Now:
Try the Platform: Sign up free at galileo.ai
Explore Agent Metrics: Check out our updated Agent Leaderboard
Learn More: Read about our Insights Engine and Luna-2 models
Get Support: Contact our team for enterprise implementation
Ready to ship reliable agents? Join thousands of developers already building with confidence using Galileo's Agent Reliability Platform.
Building a single agent that actually works is hard. It's not easy to figure out all the failure modes across all the different paths the agent can take. When you have thousands of these agents, how do you ensure they'll be reliable at scale?
That's precisely why we're excited to announce Galileo's free Agent Reliability Platform today, the industry's first comprehensive solution purpose-built to enable trustworthy multi-agent systems.
Agents Are Breaking at Scale
AI agents are transforming how we build applications and have the potential to reshape our economy. From customer support bots handling complex multi-turn conversations to financial agents processing transactions worth millions, agents are taking on increasingly critical business functions.
But here's the challenge: traditional debugging tools weren't built for agents.
When your RAG system fails, you debug a pipeline. When your agent fails, you're debugging an autonomous system that made decisions across multiple tools, reasoned through complex scenarios, and potentially interacted with other agents. The failure modes are exponentially more complicated.
And the stakes are higher. One bad action can expose sensitive data, cost real money, or damage customer relationships. Yet most teams are flying blind, hoping their agents work reliably in production.
Three Core Problems, Three Breakthrough Innovations
1. Observability: Reimagined for Agents
The Problem: Observability in the era of agents is broken. A simple trace view does not cut when you need to untangle the complexities of robust multi-agent systems.
Our Solution: The Galileo Graph Engine
We had to completely rethink the base user experience of observability for multi-agent systems and ensure that it was orchestration system agnostic.
Our Graph Engine can trace different complex agentic paths and seamlessly map multi-agent workflows. Combined with our comprehensive suite of metrics, Graph Engine gives you a holistic view of where things are going wrong.
Key Features:
Framework-agnostic: Works with CrewAI, LangGraph, OpenAI's Agent SDK, LlamaIndex, and more
Graph View: See every branch, decision, and tool call at a glance
Timeline View: Identify execution bottlenecks and performance issues
Conversation View: Debug from your user's perspective
2. Failure Mode Analysis: Automatic Insights
The Problem: Complex agents fail in subtle ways that are notoriously difficult to diagnose. No developer wants to hunt for a needle in a haystack of spans and traces.
Our Solution: The Galileo Insights Engine
Our Insights Engine ingests your logs and metrics, then leverages bespoke evaluation reasoning models to identify failure modes and deliver immediate, actionable insights.
Insights Engine provides specific recommendations for improvement tied directly to the exact span, trace, or component that needs attention. The engine also learns from your specific agent patterns and workflows, providing increasingly relevant recommendations over time. Plus, provide human feedback to further tune the insights to your needs.
Key Capabilities:
Root Cause Analysis: Links errors to exact traces in complex multi-agent systems
Multi-Agent Coordination: Understands how agents interact and where handoffs fail
Tool Usage Optimization: Identifies inefficient tool selection patterns
Actionable Recommendations: Not just what's wrong, but how to fix it
3. Real-Time Guardrails: Protection at Scale
The Problem: When an agent makes a mistake, the consequences can harm your user experience and your brand.
Our Solution: Luna-2 Small Language Models
Our new family of small language models, Luna-2, are purposefully built for real-time guardrails at enterprise scale. Whether you want to evaluate against our suite of out-of-the-box agent metrics or create custom metrics, Luna-2 enables real-time guardrails with millisecond latencies at a fraction of the cost of larger models.
Luna-2 is already helping large enterprises protect their hundreds of agents and process hundreds of millions of queries daily through dozens of guardrails.
Luna-2 Advantages:
20+ sophisticated metrics running simultaneously
Sub-200ms latency even at 100% sampling rates
97% cheaper than traditional LLM-based solutions
Custom metrics fine-tuned for your specific use cases
Real Impact: What Our Customers and Partners Are Saying
MongoDB: "Galileo’s platform helps you build reliable AI systems that enable companies to grow, and ensure developers' trust," said Mikiko Chandrasekhar, Staff Developer Advocate.
Outshift by Cisco: "What Galileo is doing with their Luna-2 small language models is amazing. This is a key step to having total, live in-production evaluations and guardrailing of your AI system," said Giovanna Carofiglio, Distinguished Engineer & Senior Director at Outshift by Cisco.
Agent Metrics + Leaderboard v2
To accompany today's platform launch, we're also releasing the v2 of our AI Agent Leaderboard. The leaderboard leverages our Action Completion and Tool Selection Quality agent metrics to evaluate models across domain-specific enterprise tasks covering banking, healthcare, insurance, investments, and telecoms.
This isn't just academic benchmarking. These are the real-world scenarios your agents face in production, measured with the same metrics now available in our platform.
→ Explore the Live Leaderboard
The Market Moment
The timing couldn't be more critical. Capgemini research shows:
10% of organizations already use AI agents
50%+ plan implementation in 2025
82% plan integration within three years
Yet Gartner predicts 40% of agentic AI projects will be canceled by the end of 2027 due to reliability issues.
With our Agent Reliability platform, your project doesn’t have to be one of them.
Get Started Today
We are very excited to announce that all of these features are available starting today. You can start for free at galileo.ai.
This is just the start. We are obsessed with this critical problem of agent reliability, and stay tuned for much more from us over the coming months.
What You Can Do Right Now:
Try the Platform: Sign up free at galileo.ai
Explore Agent Metrics: Check out our updated Agent Leaderboard
Learn More: Read about our Insights Engine and Luna-2 models
Get Support: Contact our team for enterprise implementation
Ready to ship reliable agents? Join thousands of developers already building with confidence using Galileo's Agent Reliability Platform.
Building a single agent that actually works is hard. It's not easy to figure out all the failure modes across all the different paths the agent can take. When you have thousands of these agents, how do you ensure they'll be reliable at scale?
That's precisely why we're excited to announce Galileo's free Agent Reliability Platform today, the industry's first comprehensive solution purpose-built to enable trustworthy multi-agent systems.
Agents Are Breaking at Scale
AI agents are transforming how we build applications and have the potential to reshape our economy. From customer support bots handling complex multi-turn conversations to financial agents processing transactions worth millions, agents are taking on increasingly critical business functions.
But here's the challenge: traditional debugging tools weren't built for agents.
When your RAG system fails, you debug a pipeline. When your agent fails, you're debugging an autonomous system that made decisions across multiple tools, reasoned through complex scenarios, and potentially interacted with other agents. The failure modes are exponentially more complicated.
And the stakes are higher. One bad action can expose sensitive data, cost real money, or damage customer relationships. Yet most teams are flying blind, hoping their agents work reliably in production.
Three Core Problems, Three Breakthrough Innovations
1. Observability: Reimagined for Agents
The Problem: Observability in the era of agents is broken. A simple trace view does not cut when you need to untangle the complexities of robust multi-agent systems.
Our Solution: The Galileo Graph Engine
We had to completely rethink the base user experience of observability for multi-agent systems and ensure that it was orchestration system agnostic.
Our Graph Engine can trace different complex agentic paths and seamlessly map multi-agent workflows. Combined with our comprehensive suite of metrics, Graph Engine gives you a holistic view of where things are going wrong.
Key Features:
Framework-agnostic: Works with CrewAI, LangGraph, OpenAI's Agent SDK, LlamaIndex, and more
Graph View: See every branch, decision, and tool call at a glance
Timeline View: Identify execution bottlenecks and performance issues
Conversation View: Debug from your user's perspective
2. Failure Mode Analysis: Automatic Insights
The Problem: Complex agents fail in subtle ways that are notoriously difficult to diagnose. No developer wants to hunt for a needle in a haystack of spans and traces.
Our Solution: The Galileo Insights Engine
Our Insights Engine ingests your logs and metrics, then leverages bespoke evaluation reasoning models to identify failure modes and deliver immediate, actionable insights.
Insights Engine provides specific recommendations for improvement tied directly to the exact span, trace, or component that needs attention. The engine also learns from your specific agent patterns and workflows, providing increasingly relevant recommendations over time. Plus, provide human feedback to further tune the insights to your needs.
Key Capabilities:
Root Cause Analysis: Links errors to exact traces in complex multi-agent systems
Multi-Agent Coordination: Understands how agents interact and where handoffs fail
Tool Usage Optimization: Identifies inefficient tool selection patterns
Actionable Recommendations: Not just what's wrong, but how to fix it
3. Real-Time Guardrails: Protection at Scale
The Problem: When an agent makes a mistake, the consequences can harm your user experience and your brand.
Our Solution: Luna-2 Small Language Models
Our new family of small language models, Luna-2, are purposefully built for real-time guardrails at enterprise scale. Whether you want to evaluate against our suite of out-of-the-box agent metrics or create custom metrics, Luna-2 enables real-time guardrails with millisecond latencies at a fraction of the cost of larger models.
Luna-2 is already helping large enterprises protect their hundreds of agents and process hundreds of millions of queries daily through dozens of guardrails.
Luna-2 Advantages:
20+ sophisticated metrics running simultaneously
Sub-200ms latency even at 100% sampling rates
97% cheaper than traditional LLM-based solutions
Custom metrics fine-tuned for your specific use cases
Real Impact: What Our Customers and Partners Are Saying
MongoDB: "Galileo’s platform helps you build reliable AI systems that enable companies to grow, and ensure developers' trust," said Mikiko Chandrasekhar, Staff Developer Advocate.
Outshift by Cisco: "What Galileo is doing with their Luna-2 small language models is amazing. This is a key step to having total, live in-production evaluations and guardrailing of your AI system," said Giovanna Carofiglio, Distinguished Engineer & Senior Director at Outshift by Cisco.
Agent Metrics + Leaderboard v2
To accompany today's platform launch, we're also releasing the v2 of our AI Agent Leaderboard. The leaderboard leverages our Action Completion and Tool Selection Quality agent metrics to evaluate models across domain-specific enterprise tasks covering banking, healthcare, insurance, investments, and telecoms.
This isn't just academic benchmarking. These are the real-world scenarios your agents face in production, measured with the same metrics now available in our platform.
→ Explore the Live Leaderboard
The Market Moment
The timing couldn't be more critical. Capgemini research shows:
10% of organizations already use AI agents
50%+ plan implementation in 2025
82% plan integration within three years
Yet Gartner predicts 40% of agentic AI projects will be canceled by the end of 2027 due to reliability issues.
With our Agent Reliability platform, your project doesn’t have to be one of them.
Get Started Today
We are very excited to announce that all of these features are available starting today. You can start for free at galileo.ai.
This is just the start. We are obsessed with this critical problem of agent reliability, and stay tuned for much more from us over the coming months.
What You Can Do Right Now:
Try the Platform: Sign up free at galileo.ai
Explore Agent Metrics: Check out our updated Agent Leaderboard
Learn More: Read about our Insights Engine and Luna-2 models
Get Support: Contact our team for enterprise implementation
Ready to ship reliable agents? Join thousands of developers already building with confidence using Galileo's Agent Reliability Platform.
Building a single agent that actually works is hard. It's not easy to figure out all the failure modes across all the different paths the agent can take. When you have thousands of these agents, how do you ensure they'll be reliable at scale?
That's precisely why we're excited to announce Galileo's free Agent Reliability Platform today, the industry's first comprehensive solution purpose-built to enable trustworthy multi-agent systems.
Agents Are Breaking at Scale
AI agents are transforming how we build applications and have the potential to reshape our economy. From customer support bots handling complex multi-turn conversations to financial agents processing transactions worth millions, agents are taking on increasingly critical business functions.
But here's the challenge: traditional debugging tools weren't built for agents.
When your RAG system fails, you debug a pipeline. When your agent fails, you're debugging an autonomous system that made decisions across multiple tools, reasoned through complex scenarios, and potentially interacted with other agents. The failure modes are exponentially more complicated.
And the stakes are higher. One bad action can expose sensitive data, cost real money, or damage customer relationships. Yet most teams are flying blind, hoping their agents work reliably in production.
Three Core Problems, Three Breakthrough Innovations
1. Observability: Reimagined for Agents
The Problem: Observability in the era of agents is broken. A simple trace view does not cut when you need to untangle the complexities of robust multi-agent systems.
Our Solution: The Galileo Graph Engine
We had to completely rethink the base user experience of observability for multi-agent systems and ensure that it was orchestration system agnostic.
Our Graph Engine can trace different complex agentic paths and seamlessly map multi-agent workflows. Combined with our comprehensive suite of metrics, Graph Engine gives you a holistic view of where things are going wrong.
Key Features:
Framework-agnostic: Works with CrewAI, LangGraph, OpenAI's Agent SDK, LlamaIndex, and more
Graph View: See every branch, decision, and tool call at a glance
Timeline View: Identify execution bottlenecks and performance issues
Conversation View: Debug from your user's perspective
2. Failure Mode Analysis: Automatic Insights
The Problem: Complex agents fail in subtle ways that are notoriously difficult to diagnose. No developer wants to hunt for a needle in a haystack of spans and traces.
Our Solution: The Galileo Insights Engine
Our Insights Engine ingests your logs and metrics, then leverages bespoke evaluation reasoning models to identify failure modes and deliver immediate, actionable insights.
Insights Engine provides specific recommendations for improvement tied directly to the exact span, trace, or component that needs attention. The engine also learns from your specific agent patterns and workflows, providing increasingly relevant recommendations over time. Plus, provide human feedback to further tune the insights to your needs.
Key Capabilities:
Root Cause Analysis: Links errors to exact traces in complex multi-agent systems
Multi-Agent Coordination: Understands how agents interact and where handoffs fail
Tool Usage Optimization: Identifies inefficient tool selection patterns
Actionable Recommendations: Not just what's wrong, but how to fix it
3. Real-Time Guardrails: Protection at Scale
The Problem: When an agent makes a mistake, the consequences can harm your user experience and your brand.
Our Solution: Luna-2 Small Language Models
Our new family of small language models, Luna-2, are purposefully built for real-time guardrails at enterprise scale. Whether you want to evaluate against our suite of out-of-the-box agent metrics or create custom metrics, Luna-2 enables real-time guardrails with millisecond latencies at a fraction of the cost of larger models.
Luna-2 is already helping large enterprises protect their hundreds of agents and process hundreds of millions of queries daily through dozens of guardrails.
Luna-2 Advantages:
20+ sophisticated metrics running simultaneously
Sub-200ms latency even at 100% sampling rates
97% cheaper than traditional LLM-based solutions
Custom metrics fine-tuned for your specific use cases
Real Impact: What Our Customers and Partners Are Saying
MongoDB: "Galileo’s platform helps you build reliable AI systems that enable companies to grow, and ensure developers' trust," said Mikiko Chandrasekhar, Staff Developer Advocate.
Outshift by Cisco: "What Galileo is doing with their Luna-2 small language models is amazing. This is a key step to having total, live in-production evaluations and guardrailing of your AI system," said Giovanna Carofiglio, Distinguished Engineer & Senior Director at Outshift by Cisco.
Agent Metrics + Leaderboard v2
To accompany today's platform launch, we're also releasing the v2 of our AI Agent Leaderboard. The leaderboard leverages our Action Completion and Tool Selection Quality agent metrics to evaluate models across domain-specific enterprise tasks covering banking, healthcare, insurance, investments, and telecoms.
This isn't just academic benchmarking. These are the real-world scenarios your agents face in production, measured with the same metrics now available in our platform.
→ Explore the Live Leaderboard
The Market Moment
The timing couldn't be more critical. Capgemini research shows:
10% of organizations already use AI agents
50%+ plan implementation in 2025
82% plan integration within three years
Yet Gartner predicts 40% of agentic AI projects will be canceled by the end of 2027 due to reliability issues.
With our Agent Reliability platform, your project doesn’t have to be one of them.
Get Started Today
We are very excited to announce that all of these features are available starting today. You can start for free at galileo.ai.
This is just the start. We are obsessed with this critical problem of agent reliability, and stay tuned for much more from us over the coming months.
What You Can Do Right Now:
Try the Platform: Sign up free at galileo.ai
Explore Agent Metrics: Check out our updated Agent Leaderboard
Learn More: Read about our Insights Engine and Luna-2 models
Get Support: Contact our team for enterprise implementation
Ready to ship reliable agents? Join thousands of developers already building with confidence using Galileo's Agent Reliability Platform.
Conor Bronsdon
Conor Bronsdon
Conor Bronsdon
Conor Bronsdon