Automate the boring,
operate at scale, with AI on tap
Visual workflows, scheduled jobs and reusable runbooks — plus AI log triage and a bring-your-own-LLM toolkit, so you can wire up agents, scripts and approvals without writing pipeline code or sending data anywhere it doesn't already live.
What X-Operation does
Pragmatic features built for real-world teams.
Visual Workflow Builder
Drag-and-drop steps with approval gates, branches and retries.
Runbook Library
Curated, parameterised runbooks for common ops tasks; one-click execute.
Scheduled Jobs
Cron-style schedules with alerting on missed or failed runs.
Agent Fleet
Lightweight agents on Linux/Windows targets, controlled from a single console.
Audit Trail
Every step recorded with who/what/when, retained for compliance.
Integrations
Webhooks, REST, SSH and shell out-of-the-box; bring your own with a small SDK.
AI on top of every runbook
LLM features that don't ship your data anywhere it doesn't already live.
AI log triage · Live
Clusters 50,000 log lines into a handful of actionable groups, then asks an LLM to explain each one's likely cause and suggested next action. Shipped today in /admin/log-analyzer.
Bring your own LLM · Live
Two env vars (LLM_BASE_URL, LLM_MODEL) point the platform at OpenAI, Anthropic, DeepSeek, or a local llama-cpp / Ollama endpoint. Regulated buyers can run the whole stack air-gapped.
AI-explained run failures · Coming next
When a workflow fails, an LLM reads the structured step logs and gives you a one-paragraph explanation of what went wrong and what to try next.
Your data stays on your servers
Two env vars (LLM_BASE_URL, LLM_MODEL) wire the platform to any OpenAI-compatible endpoint — local llama-cpp / Ollama, or a remote OpenAI / Anthropic / DeepSeek API. Run X-Operation fully air-gapped and the only thing that ever leaves your network is what you choose to send.
Ready to try X-Operation?
Spin up a demo in minutes; bring your own data when you're ready.