Loom

Large-scale Orchestration Of Models — a Go framework for data pipelines powered by AI models.

Define how records are classified, filtered, and summarized. Loom handles concurrency, provider rate limits, retries, model escalation, and caching, with explicit budgets and permissions for each task.

Use it for workflows such as triaging support tickets, summarizing document collections, or running several agents that share model capacity and results.

Website · Watch the demo · Documentation

Quickstart

You'll need Go 1.24 or later and Git.

git clone https://github.com/zionrubin/loom.git
cd loom
go run ./examples/triage

This example uses a deterministic mock model: no API key or paid model calls. Go may download dependencies on the first run; the example itself runs offline.

It classifies five support tickets, keeps the three urgent ones, and produces a briefing. The terminal shows model-call events, the briefing, and a per-stage report of tasks, tokens, cost, and cache hits.

To see completed work reused, run it twice with the same state directory:

LOOM_STATE=./state go run ./examples/triage
LOOM_STATE=./state go run ./examples/triage

The second run replays cached results with zero model calls. Read the complete example to see the pipeline and model setup.

How it works

A pipeline starts with records and connects stages such as Infer, Filter, and ReduceAI. Loom turns those stages into tasks, schedules their execution, and returns the output with a run report.

• Control spending: estimate calls and cost before a run, then apply token and dollar budgets during execution.
• Handle model failures: retry transient errors and escalate invalid output to stronger models using your validation rules.
• Reuse completed work: persist task results so unchanged work can be replayed across runs and process restarts.
• Declare access: task envelopes specify permitted models, tools, secrets, network hosts, and sandbox profiles; deployment policies constrain them.
• Scale when needed: run concurrent pipelines in a fleet, process streams, or distribute tasks across worker processes.

Loom is a Go library. The default executor runs locally; an envelope is an access declaration, not an OS sandbox. See the architecture and isolation model for execution boundaries.

Where to go next

I want to…	Start here
Try another workflow or a real model	Runnable examples
Watch tasks execute in a browser	Live visualization
Build a pipeline visually	Loom Studio
Find a specific capability	Documentation guide
Understand or contribute to the internals	Architecture · Development reference