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Production is increasing in speed, deployments are continuous, telemetry is expanding rapidly, and failure modes are becoming increasingly unpredictable. Engineering teams now face distributed infrastructure managed by siloed teams, outdated tribal knowledge, and observability tools that struggle to scale with system complexity. With the pressure to move fast and innovate rising while “keep-the-lights-on” budgets stay flat, it’s no longer viable to keep throwing valuable engineers at reliability problems.
Today marks a milestone in software engineering for managing production systems at scale. Our Agentic AI SRE is officially live in the new AI Agents and Tools category on AWS Marketplace, announced at the AWS Summit in New York. In just a few clicks, engineering teams can discover, procure, and deploy our autonomous observability and SRE solution using their existing AWS accounts, eliminating procurement friction and accelerating time-to-value.
At our recent Beyond the Build Executive Forum, Spiros Xanthos, founder & CEO of Resolve AI, shared a bold challenge: “Trust machines with agency.” He argued that real progress in reliability will come when AI can deeply understand systems, reason through incidents, and continuously learn the way our best engineers do. This is the foundation Resolve AI was built on, and now, it’s just a click away.
Understands Your Production Systems - Resolve AI builds a living, real-time knowledge graph that continuously maps the inner workings of your production systems, including containerized environments built on Kubernetes and Amazon EKS. It integrates source code, infrastructure resources, deployment configurations, telemetry streams, and change history into a single, cohesive view. It also captures and contextualizes tribal knowledge, surfacing the hidden dependencies and architectural nuances that often go unnoticed. This deep system understanding is especially critical in dynamic cloud-native environments where services shift, scale, and interact across layers. Whether you’re debugging microservices, tracing pod-level behavior, or correlating signals from distributed traces, Resolve AI interprets your environment with precision, keeping pace with every deployment, rollout, and recovery cycle.
Reasons Like Your Seasoned Engineer - Whether it's reacting to a live incident or prompted via chat in Slack, with local language support, Resolve AI doesn’t just react, it thinks. It constructs a troubleshooting plan from live telemetry and observed symptoms, reasoning through possible root causes based on environmental context, and executing targeted actions across your toolchain. At every step, it gathers supporting evidence, refines its strategy, and adapts based on new signals, just like your senior engineer would—the result: faster investigations, richer insights, dramatically reduced escalation, and more time back for building new capabilities.
Learns with Every Interaction - Every incident, every investigation, and every human interaction and input makes Resolve AI smarter for your production environment. Whether it’s explicit feedback, subtle behavioral signals, or nuanced corrections, the system builds intuition about your stack, how it fails, how engineers troubleshoot, and which edge cases truly matter. This learning propagates across your team’s entire operational environment, enabling Resolve AI to generalize intelligence for both recurring and novel incidents.
Agentic AI can’t be a bolt-on automation layer; it’s a paradigm shift in how modern systems are understood, managed, and evolved. With deployments accelerating, environments fragmenting, and failure patterns defying past assumptions, our Agentic AI SRE provides an entirely new reliability foundation that easily integrates with your existing observability tooling, one rooted in comprehensive understanding, in-depth reasoning, and continuous learning. And because your engineers spend less time on manual incident work, you’ll unlock dramatic gains in engineering velocity, helping to ship more features in each sprint.
“DataStax Astra delivers mission-critical services to Gen AI workloads. Diagnosing and resolving production incidents as quickly as possible is critical for our production and support engineers; every second matters to our customers’ businesses. Resolve AI's operational assistance capabilities promise not only to help our production and support engineers dramatically lower incident duration but also make them way more productive.” — Shankar Ramaswamy, Head of Engineering, DataStax - an IBM Company
By leveraging our Agentic AI SRE, engineering teams at customers like DataStax, an IBM Company, Blueground, and Tubi are already reporting:
Resolve AI is now available in AWS Marketplace for fast deployment and streamlined procurement. Check us out on the AWS Marketplace or contact us to learn more about Resolve AI for SRE.
Manveer Sahota
Product Marketing Manager
Manveer is a product marketer at Resolve AI who enjoys helping technology and business leaders make informed decisions through compelling and straightforward storytelling. Before joining Resolve AI, he led product marketing at Starburst and executive marketing at Databricks.
Resolve AI has launched with a $35M Seed round to automate software operations for engineers using agentic AI, reducing mean time to resolve incidents by 5x, and allowing engineers to focus on innovation by handling operational tasks autonomously.
Resolve AI, powered by advanced Agentic AI, has transformed how Blueground manages production engineering and software operations, seamlessly handling alerts, supporting root cause analysis, and alleviating the stress of on-call shifts.
This blog post explores how Agentic AI can transform software engineering by addressing the deep cognitive challenges engineers face during on-call incidents and daily development. It argues that today's observability tools overwhelm engineers with fragmented data but fail to provide real system understanding. By combining AI agents with dynamic knowledge graphs, Resolve AI aims to replicate engineering intuition at machine scale—enabling proactive, autonomous investigation, and delivering the kind of contextual awareness usually reserved for the most seasoned engineers.