Today, we’re excited to announce the launch of Mezmo’s AI-powered Site Reliability Engineering (SRE) agent for root cause analysis (RCA)—a transformative leap forward for engineering and operations teams facing the relentless complexity of modern cloud-native systems.

Why an agentic SRE for root cause analysis? Addressing the Root of Modern Incidents

We're entering an era where incidents resolve themselves before engineers even know they exist. The old playbook—engineers drowning in logs, jumping between tools, and manually piecing together what went wrong—is over. Modern engineering teams don't have time for that. They're shipping faster, running more complex distributed systems, and dealing with telemetry volumes that double every quarter. The gap between how fast systems break and how fast teams can respond is widening. Instead of engineers hunting through noise, intelligent systems should surface root causes instantly, correlate across your entire stack automatically, and turn resolution from hours into seconds. The future isn't about better dashboards—it's about making the entire incident response workflow feel like magic.

Mezmo’s AI SRE for RCA is engineered to break this cycle. By leveraging agentic AI workflows, our solution rapidly analyzes telemetry data to pinpoint root causes, eliminate noise, and recommend actionable remediation steps. This happens within your existing developer ecosystem (your tools, IDEs, and environments), meaning there’s zero context switching. Whether you’re a platform engineer, SRE, or developer, Mezmo delivers the clarity and confidence you need to move from incident to insight in record time.

What Makes Mezmo’s Approach Different?

Active Telemetry, Not Passive Storage: Mezmo enables teams to filter out and refine telemetry data, delivering only the highest-value signals to both humans and AI agents. This proactive approach reduces costs and accelerates insight.

Context Engineering: Our platform ensures AI agents are fed with clean, trusted, and context-rich data—solving the core problem of “hallucinated” or flaky RCA results that plague generic LLM-based solutions.

Agentic Enablement: Mezmo is built for the new wave of AI SRE agents, providing real-time, stateful context so automations act fast, smart, and reliably.

How It Works: Intelligent, Context-Driven Root Cause Analysis

At the heart of Mezmo’s AI SRE is our MCP (Model Context Protocol) Server—a purpose-built, intelligent interface between your observability data and modern AI models. Unlike competitors who flood LLMs with raw data (driving up costs and confusion), Mezmo’s MCP Server deduplicates, clusters, and enriches telemetry before analysis. This means:

Prioritized context over prompts allows for accurate root cause analysis with a single, simple prompt:

• 90%+ cost reduction compared to prompt engineering. From $1-$6 per incident down to $0.06
• 95% improvement in Token efficiency (27K tokens instead of 500K+)
• 90% time reduction via agentic diagnosis (50 min to 5 min)

See our recent benchmarking data here.

Key Features and Capabilities

• Agentic RCA Workflows: Automated, multi-step analysis plans that traverse your infrastructure, validate findings, and converge on a defensible root cause.
• Noise-free, high-fidelity signals: Only the most relevant data is analyzed, reducing token usage and improving MTTR by up to 80%.
• Smart Data Processing: Deduplication and clustering of log data before AI analysis, cutting costs and improving speed.
• Structured Recommendations: Receive clear RCA summaries with technical details and step-by-step remediation guidance.
• IDE MCP Integration: Access root cause insights directly from your development environment, eliminating context switching and accelerating incident response.
• Third-party Integrations: Out-of-the-box support for PagerDuty, Slack, and more, with expanded ecosystem integrations coming soon.
• Scalability and Security: Designed to handle petabytes of data, with enterprise-grade security, multi-region deployment, and robust failover mechanisms

Launch Timeline and Availability

Mezmo’s AI SRE for root cause analysis is now available. Schedule a demo to learn more.

This Mezmo Log Analysis Ingestion Source takes your data sent to our Log Management endpoint logs.mezmo.com and redirects it into a Pipeline Source. This re-routes the data flow from Mezmo Log Management to your Pipeline. For more information, check out our documentation.

Mezmo Flow provides an easy onboarding experience focused on helping you gain an understanding of your data, and then recommending Processors based on common patterns and message types. With Mezmo Flow, you're four steps away from creating a telemetry data Pipeline that will substantially reduce the volume of telemetry data sent to your storage locations and observability tools, saving both on costs and the mental toil required to optimize your data for your observability requirements. For more information, check out the Mezmo Flow topic in our product documentation.

Mezmo is pleased to announce a new feature for the Mezmo Platform, the ability to search product documentation within the Mezmo Web App.

The in-app search is powered by Intercom, so to access the in-app search:

1. Log into the the Mezmo Web App.
2. Open the Intercom chat window.
3. Enter your search terms.

The in-app search will return results from all the Mezmo product guides, as well as product announcement.

Mezmo is pleased to announce the release of a new Destination for Mezmo Telemetry Pipelines, AWS SQS. Check out our docs for more information.

Mezmo is pleased to announce the release of a new Destination for Mezmo Telemetry Pipelines, AWS Kinesis Streams. Check out our docs for more information.

Mezmo is pleased to announce the release of a new Destination for Mezmo Telemetry Pipelines, AWS Kinesis Firehose. Check out our docs for more information.

Mezmo is pleased to announce the release of a new Destination for Mezmo Telemetry Pipelines, AWS Cloudwatch Logs. Check out our docs for more information.

Mezmo is pleased to announce the release of a new Destination for Mezmo Telemetry Pipelines, AWS Cloudwatch Metrics. Check out our docs for more information.

Mezmo is pleased to announce the release of Processor Groups for Mezmo Telemetry Pipelines. With this feature, you can create groupings for sets of Processors that are used for specific data optimization functionality, and then share them with other members of your organization. When used with features like Shared Sources, you can create re-usable, purpose-built Pipeline components for your teams to help them quickly build Telemetry Pipelines for every purpose. For more information, check out the Create Processor Group topic at docs.mezmo.com.