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Logmetry

What AI native actually means

Most estates are configured in consoles and cannot be read as a whole, by a person or by anything else. Holding the estate as code is not a delivery preference, it is the thing that makes AI on your operations possible.

Agentic remediation, end to end

On an estate held as code the Agent closes the loop itself: it investigates the alert on the Lake, writes the correction, and opens a pull request that a person approves before the merge updates the estate.

The loop starts where your team already lives: an alert fires from the SIEM, the APM, or the metric store, and the Agent picks it up the moment it does. It investigates on the Lake, where the full-fidelity history is enriched and correlated, and it reaches back into the platforms over MCP when their context helps. Everything it finds, the hypothesis, the evidence, and what it checked, lands in the ServiceNow ticket your service desk already opened, because that ticket is your current flow and the Agent joins it instead of replacing it.

Then comes the part no console can offer. When the fault sits in configuration, in a routing decision, in an alert rule, or in the infrastructure itself, those are all files in your repositories, so the Agent does not stop at a diagnosis. When it is confident, it writes the correction and opens a pull request linked into that same ticket, the same way your engineers ship changes. When it is not confident, it does not touch the code: the findings still land in the ticket, and a person takes it from there. Either way the human is the gate: a person approves the diff, the pipeline tests it, and the merge is what updates the estate.

And then the loop closes. The corrected estate runs until the next alert, every fix is a commit with an author and a reason, and the playbooks sharpen with every pass. This is why everything as code is not a delivery preference: it is the difference between an assistant that describes your problems and an Agent that fixes them.

What a readable estate can do

An estate held as code can be asked, edited, audited, and worked by agents, and each of those is a file operation rather than a console feature.

01 · Ask

What is running, why it is configured this way, what changed this morning. The answer comes out of the files rather than out of whoever set it up, so it survives that person leaving and it does not begin with learning a query language. People who do not write code get answers too.

02 · Edit

What used to be a click in a console is a few lines in a file. You describe the change to a coding agent, it makes the edit, and it goes through the same pipeline as everything else: reviewed, tested and validated before it ships. Safe by process rather than by care.

03 · History

Every change is a commit with an author, a date and a reason. When something breaks, the change that broke it is findable, whether it landed this morning or two quarters ago. That is the question a dashboard has never once answered.

04 · Tickets

Much of the service desk queue is requests, not incidents: onboard this source, add an alert, raise a threshold. The Agent picks the ticket up, writes the change into the repository that rule lives in, and opens a pull request. Somebody reviews and merges, and the pipeline ships it.

What the Agent can reach

The readable estate spans the stack, the knowledge, and the infrastructure, because all three are files in the same repositories.

The Stack

Collection, routing and enrichment, the Lake, and the alert rules and dashboards on every destination, including the platforms you keep.

The Knowledge

Runbooks, service ownership, and the notes explaining how the parts relate, kept as files beside the code they describe rather than in a wiki nobody opens.

The Estate

The infrastructure itself declared as code, so a resource that is wrong is a file that is wrong, and correcting it is the same motion as everything above.

Your platforms sell a version of this too. Theirs is an assistant living inside their own console, so it reasons about what that console holds and stops at its edge. The same idea over an estate you hold as code reaches the collection layer, the destinations, the Lake and the infrastructure underneath, because every part of it is readable. That is what AI native means here, and it is why the phases run in the order they do.

AI on a Lake, on open table formats

The direction of travel is AI working directly against telemetry held in open table formats, because open storage is what keeps years of history readable by every model you will ever run.

AI on ground you ownThe agent reads its working memory from the Lake, on open table formats you own. The playbooks, the environment context, and the history stay put, and the model underneath is a part you swap: a frontier model, open weights run in house, or whatever ships next, with a cheap model for the endless work and a strong one for the investigations that earn it.THE LAKE, READABLEOpen table formats, yoursYOUR AGENTReads your historyThe playbooks, the context, andthe history stay. Only themodel underneath changes.THE MODEL, SWAPPEDA FRONTIER MODELOPEN WEIGHTS, IN HOUSEWHATEVER SHIPS NEXTA cheap model for the endlesswork, a strong one for theinvestigations that earn it.
What AI native actually means. The intelligence stands on ground you own, and the model is a replaceable part: the playbooks, context, and history stay while the model underneath changes.

The Lake built in Phase 01 is partitioned the way investigations move, so it serves compliance, audit and the agents at once. Every model you point at it, today's or the one you swap in later, reads the same clean, enriched history. That is the foundation the market's AI features will stand on, and owning it is the difference between renting intelligence and running it.

Asked about AI native

What does AI native actually mean here?

That the estate is readable. Most estates are configured in consoles and cannot be read as a whole by a person or by anything else. Held as code, the collection layer, the destinations, the Lake and the infrastructure underneath are all reachable by the same Agent, which is what the platform assistants cannot do.

How is this different from the AI our platforms sell?

Their assistant lives inside their own console, reasons about what that console holds, and stops at its edge. The same idea over an estate you hold as code reaches everything, because every part of it is a file. That difference is architectural, not a feature gap that closes next quarter.

Where does the Lake fit in?

AI on your telemetry is only as good as the data it reaches. The Lake holds full-fidelity history, enriched and partitioned for retrieval, on open table formats, which is the direction the whole market is moving for exactly this reason: open storage is what keeps the data readable by every model you will ever run.

Which model does this run on?

Whichever you choose, and that choice is a configuration knob rather than an architecture decision. Frontier or open weight, in your cloud. Every capability on this page reads the same foundation, so swapping the model later rebuilds nothing.

Start with the review

You share your diagrams, we review them with you, and you leave with your version of the Logmetry Blueprint drawn on your stack. No system access, no obligation.