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Infrastructure system

Local AI Orchestration

A local AI platform that gives planning, focused execution and independent review explicit jobs and visible receipts.

My contribution
Platform architecture · workflow design · operational evidence
Timeframe
Phased platform program
Status
Ongoing
THE WORK IN ONE LINE

A task connects to a bounded capability and a retained result. The case separates qualified and planned capabilities.

PythonLangGraphOpenClawOllamaTyped state

01 / The problem

Make a multi-tool workflow inspectable.

Local AI systems often accumulate models and scripts faster than operational trust. The goal was to make capability, routing, evidence, and safety explicit across a modular platform.

02 / What I built

Miguel used typed state, deterministic selection rules, an action boundary, and receipt-oriented QA to make multi-step work observable. The public replay is sanitized and does not connect to the private platform.

Sanitized architecture replay

Explore the control plane

No live models, services, addresses, or private topology.

FROM SOURCE TO SOMETHING USEFULExplore a layer
One connected system.

Data + code + design

Checked values

Validate the calculation before it becomes a claim. A useful answer separates what is known from what still needs review.

Implemented capability

Planning

Implemented

Turns an objective into explicit, bounded steps before tools are used.

01Goal decomposition
02Dependency ordering
03Stop conditions
Observable proof

Typed plans and checkpoint artifacts

Replay timeline

Source-grounded brief

00:00 / 00:20
Planning
Objective received

Create a private, source-grounded analytical brief.

04 / Result & scope

What changed. What comes next.

Sanitized architecture, capability-ledger, routing, and QA artifacts from the local AI platform workspace.

Typed handoffs

Designed explicit state and capability boundaries between planning, execution, and review.

Evidence and replay

Captured receipts and QA artifacts so runs can be inspected after completion.

Local-first routing

Separated task intent from provider choice to support private, swappable runtimes.

01

Choose the job before the model

Typed workflow contracts describe what a task needs before choosing a compatible provider or runtime. This separates product intent from model inventory.

02

Prove what actually ran

Action receipts and review artifacts connect requests to results. A listed capability is different from an activated tool, and the interface keeps that distinction visible.

03

Current scope

The retained platform checkpoint qualified an earlier runtime phase. Office, audio and media host surfaces remain activation-disabled, and full natural-language specialist routing is still in progress.

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