Cloud and AI operations · evidence, not assertion

Most tools report what they found. We also report what we could not see.

Conductor reads your cloud estate every hour with its own credentials, records what changed and what it cost, and marks the edges of its own knowledge. An inventory that does not say where it stopped looking reads as complete — and that is how a monitoring tool tells you confidently that there is nothing there.

Request an engagement See what it produces

Coverage — one hourly read la-north-2 · 11 collectors

compute	14	read
block storage	22	read
databases	3	read
load balancers	6	read
public addresses	9	read
security groups	17	read
audit trail	5630	read
identity	—	refused	403 — the key lacks iam:users:list
access keys	—	refused	403 — iam:credentials:listCredentials
billing	—	refused	403 — BSS ReadonlyAccess not granted

Three of those rows are the point. A tool that silently returned “no IAM users found” would be wrong in the most dangerous way available to it. Every refusal here names the exact permission that would fix it, so the gap is somebody’s next ten minutes rather than a false all-clear. Shape and figures from a real read; the estate is not identified.

What Conductor is

Two halves, and they answer different questions.

One reads the infrastructure you already run. The other sits between your team and the models you already pay for. They share a ledger, so the cost of running something and the cost of asking about it stop being separate conversations.

Running today, on a production estate

It reads your cloud

Every hour, with a read-only credential you issue and can revoke. No agent to install, no write access anywhere.

An inventory you did not assembleMachines, disks, databases, addresses, security groups — counted from the provider’s own API, not from a spreadsheet somebody maintains.
Findings with a number behind each oneA database reachable from the internet. A key nobody has rotated. An address billing monthly and routing nowhere. Each states the evidence it rests on.
An audit trail that outlives the provider’sHuawei keeps seven days of trace history. We read it hourly and keep it, so “who changed this, and when” is still answerable in March about something that happened in January.
The bill, projectedWhat this month is tracking to against last month — stated as a projection, with the reasons it might be wrong written next to it.

Built and deployed; no customer traffic yet

It sits in front of your models

An OpenAI-compatible endpoint. Your keys, your models, your account — a tenant that registers its own models is served from those and nothing else.

Trivial input never reaches a modelSomeone types “thanks”. That is a billed round trip to a frontier model everywhere else, and there is no product on the market that stops it.
Memory grounded in what we observedNot a cache that replays an old answer. What the hourly read found goes into the model’s context as reference, labelled as data, never as instruction.
A ledger that records what did not happenEvery request is written down whether or not a model was involved. Vendors report what you spent; nobody reports what you avoided.
Nothing risky runs unaskedReads run freely. Anything that changes a production system or moves money stops and waits for a person, and that tier can never be auto-approved.

Why this is still open

We checked every product that claims to close it.

Eighteen AI gateways, ten memory platforms, and the memory features now shipped by OpenAI, Anthropic, Google, AWS and Microsoft. Routing, budgets, key management and spend dashboards are solved and largely free — we do not sell those. Two things are not solved anywhere.

Nothing answers without calling a model

A filter can block a request before it reaches the model, but a block is a refusal, not an answer. Caches only help once a model has already answered. Routers send cheap questions to a cheaper model — still a call, still tokens, still latency.

0 of 18 gateways

Nothing remembers that a problem was solved

Every memory product retrieves context that goes into a prompt, and the prompt still goes to a model. They store statements. None stores an outcome: this was solved, this is what worked, and these are the conditions under which it still holds.

0 of 10 memory platforms

How we work

We start by measuring, not by selling you software.

Teams that deploy AI with an outside partner reach production roughly twice as often as teams doing it alone. The reason is not the software. It is that somebody does the unglamorous work of finding out what is actually happening first.

Diagnostic

FIXED FEE · 2–3 WEEKS

We point Conductor at your estate and your logs, and tell you two things: what is running that you are paying for and nobody owns, and what share of your AI spend answered a question you had already paid to answer. You keep the report either way.

Build

SCOPED FROM THE DIAGNOSTIC

We learn your products, your infrastructure and your workflows, then deploy Conductor against them — your models, your keys, your data, in your environment or ours.

Run

ONGOING

It improves with use, because every resolved task is recorded as resolved and every hourly read adds to what it knows about your estate. We report the ledger monthly: what ran, what it cost, and what it would have cost without us.

Where we actually are

We would rather you heard this from us.

Most companies in this position would show you logos and a savings percentage. We are early, and the honest version is more useful to you than an invented one — it is also the same standard we hold the product to.

Running

Conductor reads a production payments estate every hour and has done for weeks — inventory, findings, spend and audit history, with coverage stated on every run.

Built

The proxy, per-team spend caps, the risk-tier approval gate, the cost ledger and the memory layer are deployed and covered by an automated suite we run on every change.

Not yet

No published savings figure. Customer traffic has not run through the proxy, so any number we quoted would be modelled rather than measured. We will not do that.

Not yet

No customer logos, and no case study. You would be early, we will price like it, and you would be talking to the people who built it rather than to an account manager.

Request an engagement

Tell us what you are running and what it keeps forgetting. We are taking a small number of early engagements and we would rather they be a good fit than a big number.