🧠 AIOps · Agentic
AIOps that actually fixes things
Most AIOps tools dashboard the noise. Argos triages alerts, correlates signals across 40+ sources, and opens the PR or runbook to fix it — autonomously when you allow it.
Why traditional AIOps disappoints
Problem 1
Anomaly detection without action
You get a "score" but no next step. Argos chains tools across logs/metrics/git/cloud to close the loop.
Problem 2
Black-box ML you can't audit
Argos is agentic with explicit tool calls — every decision is logged with prompts, outputs and reasoning.
Problem 3
US-only SaaS
Argonix is EU-hosted (Hetzner Frankfurt) or self-hostable on your Kubernetes — full sovereignty.
How Argos delivers real AIOps
- ✓Multi-signal correlation: alerts + traces + logs + git commits + cloud events in one investigation.
- ✓Tool-using agent: 50 connectors, 800+ tools (kubectl, terraform plan, GitHub PR, Datadog query, AWS APIs…).
- ✓Suggest → review → apply: human-in-the-loop for production, full-auto for staging/dev.
- ✓Postmortem drafts auto-generated with timeline, root cause hypothesis and remediation plan.
- ✓Custom LLM: BYO Mistral, vLLM, Bedrock, Azure OpenAI on Enterprise.
Capabilities
Signal correlation
Argos pulls related logs, traces, metrics and recent deploys for any alert.
Auto-remediation
GitOps-native PRs (Terraform/K8s) when high confidence + low blast radius.
Slack/Teams native
Argos lives in the war room — answers, executes, summarises.
Postmortem in 5 min
Full timeline, contributing factors, action items pre-filled.