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Infrastructure system

Local AI Orchestration

A modular, backend-neutral orchestration layer for planning, routing, execution evidence, QA, safety, and local-first model use.

Role
Platform architecture · workflow design · operational evidence
Timeframe
Phased platform program
Status
Ongoing
Publication
Sanitized public case study
PythonLangGraphOpenClawOllamaTyped state

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.

The challenge

Make complex work decision-ready.

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.

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.

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.

Behind the build

System decisions that shaped the outcome

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

01

Provider-neutral control plane

Intent and capability requirements are evaluated before choosing a compatible runtime, keeping application logic independent from any one local model server.

02

Evidence is a product surface

Plans, actions, outputs, reviews, and exceptions create a review trail rather than disappearing into an opaque chat transcript.

03

Honest capability states

Completed, experimental, and planned capabilities are labeled separately. The explorer does not imply universal production activation.

Continue exploring

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