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Fleet.

Fleet is the execution layer of AEGOS — the engine room that turns approved plans into real output. It decides what to run, finds the right machine or tool, claims the resources safely, does the work, and records the result as evidence.

What it is The engine room of AEGOS

If Core is the rules, Fleet is the hands. It coordinates real compute — GPUs, models and tools — across the portfolio, turning a single decision into a finished, verified result. Every job is described by what it needs, routed to whatever can do it, and tracked from start to finish.

Decide what to run Allocate feasibility Reserve claim + lease Execute do the work Record as evidence
How work flows Decision to evidence, every time
01 · Decide

Choose what to run

A lightweight decision engine selects the next job and why — within the bounds Core allows.

02 · Allocate

Check feasibility

Fleet works out whether the job can run, and where — without committing anything yet.

03 · Reserve

Claim resources safely

It atomically reserves what it needs with a lease, so two jobs never fight over the same capacity.

04 · Execute

Do the real work

A worker runs the job — generating an image, running a model, producing a real asset.

05 · Record

Log it as evidence

The result is recorded with how it was made — measured, not assumed — and the reservation is released.

Built on Principles that keep it honest
Routing

Capability-based

Work is described by what it needs, not wired to specific hardware. Add a machine and Fleet can use it.

State

One source of truth

A single authoritative state, so what the system believes always matches what's actually happening.

Workers

Pluggable & replaceable

The units that do the work are swappable — nothing is locked to a single vendor, model or tool.

Evidence

Recorded by default

Every output captures how it was produced, separating measured results from simulated ones.

Real compute Not a toy

Fleet runs real AI workloads across real hardware — GPU nodes, including an RTX 5090, generating images, audio and more. The very same pipeline that drafts a product's hero image is the one that scales to production work.

GPU-backed
Real models, real output
Routed
By capability, not hardware
Recorded
Every result is evidence
Inside Fleet The pieces, in depth
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