◉ how our platform solves this · aiops/infra
scale the platform. we hold the line.
The work is the point — but the watch drags behind every piece of it: the prep, the formatting, the checks before anything goes out, the same steps run again and again. It’s the work around the work, and it never finishes.
◉ the answer
Agentic workflows run detect → correlate → remediate on your own infrastructure — against your own models — with a human on the gate for anything that acts, and the record written as it goes.
◉ how we solve it · our process
- Chat — you state the goal in plain language; we shape the work with you.
- Flows — it becomes a repeatable workflow, on rails and fully auditable.
- Missions & Fleets — coordinated across as many instances as the job needs.
- Synth · Brainbow · Code Mode · Exec — the right tool spun up for each step: a throwaway utility, a driven browser, code run against your real systems.
- your ground, your gate — every step on your infrastructure, a human approving anything that acts.
◉ the mechanism · what actually happens
One request, walked end to end — every step on your infrastructure, against your own models, with a human on the gate.
- ChatMode
You state the goal in plain language — “detect the drift, correlate the cause, stage the fix.” ChatMode plans the work and dispatches its built-in agents — planning, data-query, validation, synthesis — to decompose it into pull, analyze, act, assemble. No prompt engineering, no scripts.
- SmartModelRouter
Each step is routed to a model that fits it — a fast model to classify a flood of alerts, a long-context model to read a drift report, a strong reasoner to judge whether an anomaly is real or noise — across the providers you register. Bring your own models and run them on your own infrastructure; the telemetry, topology, and config stays inside your network.
- MCP tools · OBO credentials
Agents reach Kubernetes, AWS, Azure, GCP, Prometheus, and infra-health checks as MCP tools, each call running under your own identity. The platform forwards your scoped credentials per call — no shared token, no pooled service account, no secret pasted into a prompt. Every call is logged.
- Tool Synthesis · Code Execution
Sources never agree on format. Code Execution writes a one-shot Python tool on the fly to correlate signals across systems and stage a remediation — credentials injected at runtime, run in a hardened sandbox, then discarded. No tool is registered, nothing persists.
- AgenticWorkflows · cluster health
The detect → correlate → remediate flow becomes a flow of named agents — repeatable, auditable, on rails — reading off the same live cluster-health view the watch does: nodes ready, pod count and phase, the pressure that decides whether to scale or stage a fix. And there’s more behind sign-up: drift and config-compliance sweeps, multi-cloud capacity forecasting, and the auto-remediation runbooks — the many ways the platform runs this, with more revealed after you sign in.
- HITL approval
Nothing acts until you say so. The human-in-the-loop gate is real architecture, not a setting — any step that would change live infrastructure stops and waits for a person; if no one approves, it times out and is denied. You review the plan and the scope, and approve before anything happens.
- @agentic-work/llm-sdk · build on it, don’t wait for it
The internal platform service you keep deferring — the gateway, the adapter, the self-serve tool — Code Mode drafts against your repo, wired to your own provider through the zero-telemetry SDK, and proves it with tests under your review. You stay on the platform design; the agent runs the scaffolding you’d otherwise staff a quarter for, and none of it leaves your network.
- Audit trail · DLP · RBAC
Every model call, every tool call, every approval is written to an append-only audit log — once a decision is recorded it’s frozen, so the trail is tamper-evident. DLP keeps sensitive material inside your network, and role-based access scopes who can do what. It’s a record you can stand behind.
The toil ran itself, it acted only on your nod, and the record is already written — and that’s one flow. Drift and config-compliance sweeps, multi-cloud capacity forecasting, and the auto-remediation runbooks are waiting behind sign-up.
◉ go deeper
Run it on your own infrastructure — or with us.
Talk to us to see the platform on your stack — governance, fleet, support, and the enterprise capabilities. Or self-host the platform in your own environment and run the whole thing today.
The platform self-hosts in your own environment — chat, flows, and the ops MCPs. Fleet, Mission, CodeMode, governance and support come with the enterprise platform. Designed for FedRAMP-High deployment.