Mezmo honored with Open Agentic AI Innovation Award presented by the Agentic AI Foundation. Oct 26, 2026, 08:20 ET SAN FRANCISCO, Oct. 23, 2026 /PRNewswire/ - Mezmo, the company behind AURA, the open-source agent harness for production SRE workflows, today announced that it has received the Open Agentic AI Innovation Award from the Agentic AI Foundation (AAIF). The award recognizes Mezmo's work on AURA, an Apache 2.0 open-source harness built to address a problem the company encountered firsthand: how to give agents meaningful access to production while keeping their actions within boundaries defined by the operator. As organizations move agents from experimentation into production, that challenge is becoming increasingly important. The question is no longer simply whether an agent can reason about an original problem, but whether teams can safely delegate meaningful production work without giving up control over how that work is performed. Mezmo's experience operating at petabyte telemetry scale helped expose the limitations of general-purpose agent approaches. As its SRE team experimented with agents for incident response, investigations could overwhelm model context, consume expensive tokens on routine work, require repeated approvals, and create pressure to give agents broader permissions than operators were comfortable granting. AURA was built around a different model. Probabilistic reasoning happens inside deterministic boundaries defined by the operator. Teams control which tools and systems an agent can access, where human approval is required, and what evidence must be preserved. Those controls sit outside the model, so the agent cannot expand its own permissions through prompting or reasoning. For SRE teams, that means an agent can start from an alert, investigate logs and metrics, connect an issue to a deployment or code change, and recommend or take action within those boundaries. The evidence behind its decisions and its execution history remain available so operators can understand what happened, why it happened, and what the agent did next. "We are honored to receive the Open Agentic AI Innovation Award," said Tucker Callaway, CEO of Mezmo. "We built AURA because making an agent smarter does not make it safe to operate in production. Production requires a system around the model that controls its authority, manages its context, preserves evidence, and gives operators the final say where it matters. We believe that foundation should be open, inspectable, and owned by the teams running it." AURA is open source by design rather than a proprietary agent tied to a single model or service. Organizations can run it in their own environments, inspect and extend its behavior, choose their own models, and define the boundaries within which agent operates. This creates a path toward increasing autonomy deliberately. Teams can begin with investigation and recommendations, introduce human-gated actions, and expand agent authority as workflows become better understood and trusted. The AAIF recognition follows Mezmo's recent selection as a 2026 Tech Ascension Award winner in the "AI-powered Enterprise Agent Solution of the Year" category, further recognizing the company's work to make production agents more open, governable, and practical for enterprise teams. About Mezmo Mezmo helps SRE teams run agents they can trust in production. Teams move past the demo-to-production gap by pairing AURA, Mezmo's open-source SRE agent harness (Apache 2.0), with a platform that governs workflows, curates operational context, and persists memory so agents stay trusted, auditable, and repeatable. With AURA running on their own infrastructure, teams define, run, and scale governed SRE workflows across their existing tools and models, starting with incident investigation and expanding into root cause analysis, remediation guidance, post-incident learning, reliability, performance, cost optimization, and proactive fault detection. About the Agentic AI Foundation (AAIF) The Agentic AI Foundation (AAIF) is a neutral, open, and collaborative foundation dedicated to advancing the public interest through the standardization and development of agentic AI technologies. SOURCE Mezmo

Mezmo launches the world's fastest and most accurate AI SRE at KubeCon. News provided by. SAN FRANCISCO, Oct. 14, 2025 /PRNewswire/ - Mezmo, the active telemetry platform for AI agents, today launches the world's fastest and most accurate AI SRE (Site Reliability Engineering) agent for root cause analysis (RCA) ahead of KubeCon, North America. The company's secret sauce is context engineering, which supercharges AI agents with unmatched speed and precision. "We've built the fastest and most performant AI SRE in the world - a clear standard deviation above the industry standard currently," said Tucker Callaway, CEO of Mezmo. "We're launching out of the box with a root cause analysis agent for Kubernetes that will set a new industry standard for speed and accuracy." Recent LLM benchmarking exposes the limitations of competitive SRE agents. Even top-tier models like Claude Sonnet 4, OpenAI GPT-4.1, o3, Gemini 2.5, and GPT-5 struggle with basic observability tasks. The key to the speed and performance of Mezmo is context engineering. The company states existing models are fundamentally solid, but they lack the adequate context to do the job efficiently. When Mezmo's context-driven approach was benchmarked against conventional methods, the results were dramatic: * 90%+ cost reduction: From $1-$6 per incident down to $0.06 * First-try accuracy: Root cause analysis with much less prompting * Token efficiency: 27K tokens instead of 500K+ Mezmo's AI SRE Agent solves Kubernetes-related issues out of the box: Deployment Failures: By analyzing enriched Kubernetes logs and events to identify which config changes, secrets, or code updates caused deployments to fail. Pod CrashLoops and Image Pull Failures: By correlating log anomalies with pod lifecycle events to pinpoint causes of repeated restarts (CrashLoopBackOff) or failed container image pulls. Resource and Scheduling Issues: By detecting pods stuck in pending or unknown states, surfacing node resource exhaustion (CPU, memory, disk), and highlighting scheduling conflicts. Configuration and Secret Errors: By surfacing missing or invalid ConfigMaps, Secrets, or environment variables, tied directly to the workloads and pods that failed. Application-Level Failures: By clustering and analyzing application logs within Kubernetes workloads to reveal upstream/downstream dependencies, misbehaving services, or cascading failures. Even for engineering teams already building their own AI SRE agents, they can still leverage Mezmo's active telemetry and data pipelines to significantly improve model performance through superior contextual data. For a deeper understanding of how context engineering improves AI SRE results, read this recent blog from Mezmo. KubeCon attendees can also stop by booth 952 at KubeCon, North America, November 10-13 in Atlanta, Georgia. "Mezmo has significantly accelerated our engineering team's performance," said Michael Dillon, Senior Software Engineering Manager at Rescale, a leading digital engineering platform built for the AI era. "With Mezmo's AI SRE agent, we are able to quickly resolve complex issues that otherwise could stretch into months, including having identified the likely root cause of one persistent issue in just 45 minutes. Our engineers now resolve daily log analysis tasks in under five minutes. This efficiency gain gives us back valuable engineering days, allowing us to focus on innovation and advancing our platform." About Mezmo Mezmo's Active Telemetry platform delivers live, high-context observability that cuts the noise, slashes cost, and powers fast iteration, by tapping into logs, metrics, and traces - and acting on them the moment they're created. The company has raised $110 Million in total funding with customers including AuditBoard, Lime, and Sysdig. SOURCE Mezmo