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EOSOptimizeYour data, live

Spend less on the models you already have

Declare what your organization already has access to and the work you actually run; EOS prices every option against that workload, ranks them, says which it would not use and why, and keeps the choice with the person who made it. EOS calls no model and invents no price: every figure here is one your organization entered or one arithmetic derived from it.

Checking the estate API...
  1. 1Sign inidentity and organization
  2. 2Catalogwhat you already have
  3. 3Workloadthe work you run
  4. 4Planpriced and ranked
  5. 5Decidea named person, on the record
  6. 6Measurewhat actually happened

1 · Sign in and choose your organization

2 · Your inference catalog Choose an organization first.

One row per model your organization already has access to, with the rates from your own contract or invoice. Rates are per million tokens. A cached-input rate is optional; when you leave it empty, a repeated prompt is priced at the full input rate and the plan says so.

3 · The workload you actually run Declare at least one model first.

Marking a workload exact does not change the arithmetic; it makes the plan say plainly where a small-tier option would need a sample check before you trust it.

4 · The plan Save a workload first.

How the two layers feed each other

Activity in the spatial layer produces records; EOS reconciles them, keeps the evidence and routes the decision; what EOS settles is meant to return to the spatial layer as a capability people can use. Each stop below states what it is today, not what it could become.

Spatial layerActivity produces records People act in a realm and systems record it. The realm and its door exist; what reaches EOS today is an export a person uploads, not a live feed. Partial EOSReconcile and evidence Two exports of the same purchase orders, matched, compared against your tolerance, every contested figure kept with both source rows, their hashes and the person who ingested them. Built EOSDecide and measure A named person decides with a note, on the record, and precedent shows what this organization decided before. The optimizer prices the models you already have and records what a month actually cost. Built Spatial layerCapability returns What EOS settles is meant to come back as something people can use in the house of products. The door is open; the return path is not built. Entry

Read this literally: two stops are built and verified in a browser against the real API, one is partial, one is a door. Nothing here claims a live connection between the two layers, because none is deployed.

Boundary: EOS does not call a model, does not read your provider account, and does not discover prices. It prices what you declare, ranks it, and keeps the decision. A recommendation is a proposal until a person with the right role adopts it, and a saving is a claim about the future until a month is recorded here.

The cash flow impact simulator: terms, MOQ and lead time, modeled on your inputs →