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About
LLMs are useful.
Production isn't a playground.
We're building the boring, defensible layer that lets AI agents help operate real infrastructure — without becoming the next 3 a.m. incident.
Why this exists
Giving an LLM shell access is reckless. Giving it a catalog is sensible.
The first wave of LLM-for-ops tools handed agents a terminal and hoped for the best. That works on a personal laptop. It does not work on the cluster that processes your customers' payments.
Every mature ops team eventually arrives at the same answer: a finite, versioned catalog of operations. Runbooks. Playbooks. The well-trodden paths. Humans use them. CI uses them. Our claim is simple — your LLMs should use them too, and only those.
emisar is what we wished existed when our teams started letting AI agents touch production. A versioned catalog. A policy engine. An audit trail your security team accepts. Nothing more, nothing less.
What we believe
Our priors.
Least privilege, always
The LLM is the least-trusted participant. The policy engine is the source of truth, not the model.
Auditability is non-negotiable
If a thing happens in production, it needs a searchable record in the cloud and a tamper-evident journal on the host.
Boring is a feature
We pick the dull, defensible technology. Postgres. YAML. JSONL. Outbound TLS. No clever distributed systems your oncall has to learn.
A note from the founder
I spent a decade as a CTO, full-stack engineer, SRE and DevOps. I've been paged at 3 a.m. because someone — sometimes me — ran the wrong command on the wrong cluster. I've also watched LLMs solve, in seconds, problems that used to take an oncall an hour of greps and tails.
Both of those things are true. The job of emisar is to keep them true at the same time: let the runner help, but never let it become the cause of the next outage.
If that resonates — try it free, or email me with your war story. I read every message.
— Andrew, founder
Free forever for 3 runners.
Install on one host, point your LLM at it, see exactly what it tried to do — before you decide whether to keep it.