Your Infrastructure, Run by AI Agents

An Autonomous Operations Platform uses AI agents to perform infrastructure tasks that teams currently do manually — provisioning, incident response, remediation, cost optimization, and compliance enforcement. Unlike monitoring tools that surface problems for humans to fix, StackGen agents take action autonomously: they build infrastructure from intent, heal degraded services, enforce guardrails, and optimize resources continuously. The goal is to shift your SREs and Platform Engineers from reactive toil to proactive engineering.

Most AIOps and observability platforms stop at detection — they correlate alerts, surface anomalies, and create tickets for humans to act on. StackGen goes beyond detection to autonomous action. Our agents don't just tell you a node is over-provisioned or a deployment drifted from its desired state — they remediate it. Think of the difference as the gap between a dashboard that shows you have 400 alerts and an agent that resolves 390 of them before your team sees them.

You control the autonomy level. Every StackGen agent operates within guardrails your team defines — from fully autonomous execution for well-understood operations (like right-sizing non-production resources or remediating known drift) to human-in-the-loop approval for sensitive changes (like production deployments or IAM policy updates). Most customers start with recommend-and-approve mode and expand autonomy as trust builds. The platform logs every decision and action for full auditability, which matters for SOC 2, HIPAA, and other compliance frameworks.

StackGen doesn't replace your existing toolchain — it operates on top of it. Our agents work with Terraform, Pulumi, Helm, ArgoCD, Prometheus, Grafana, and the tools your team already uses. The difference is who's driving. Today, your engineers write the HCL, watch the pipelines, tune the alert thresholds, and right-size the instances. StackGen agents handle that operational work so your team focuses on architecture, reliability strategy, and platform capabilities that actually move the business forward.

Most teams start with a single high-toil workflow — the one that burns the most engineering hours with the least strategic value. Common starting points include infrastructure drift remediation, alert noise reduction, cloud cost right-sizing, or automated incident response for known failure patterns. A typical pilot runs 4–6 weeks on a non-production or low-risk environment, and teams usually see measurable toil reduction within the first two weeks. From there, customers expand across workflows and environments as confidence in the agents grows.