# MargIQ

> MargIQ is workflow intelligence for choosing the right model from your available models. It learns recurring AI workflows, weighs cost, latency, quality, and risk, and routes only where the evidence is strong.

MargIQ is not a generic LLM router and is not tied to a specific model provider. It is a decision layer for AI workflows. It starts with workflow evidence, shows potential savings and safety behavior, and lets teams control each workflow with Automatic, Report only, or Disabled modes.

## Best Starting Points

- [Homepage](https://getmargiq.com/): Product overview and positioning.
- [Product](https://getmargiq.com/product): Workflow routing, safety guards, and control plane.
- [Docs](https://getmargiq.com/docs): Developer documentation.
- [Quickstart](https://getmargiq.com/docs/quickstart): Add MargIQ without changing production model behavior.
- [npm package](https://www.npmjs.com/package/margiq): Official MargIQ SDK package.
- [LLM Setup](https://getmargiq.com/docs/llm-setup): Copy-paste prompt for AI coding assistants.
- [Examples](https://getmargiq.com/docs/examples): Routine workflow examples.
- [Proof](https://getmargiq.com/proof): Evidence model and validation approach.
- [Controlled benchmark](https://getmargiq.com/benchmarks/workflow-aware-llm-routing): Path-level cost reduction and quality-protection evidence across a controlled 15-workflow suite.
- [Benchmark data (JSON)](https://getmargiq.com/benchmarks/workflow-aware-llm-routing.json): Machine-readable methodology, measured routes, quality protection, and limitations.
- [Benchmark summary (Markdown)](https://getmargiq.com/benchmarks/workflow-aware-llm-routing.md): Agent-readable benchmark evidence and citation.
- [Pricing](https://getmargiq.com/pricing): Free and Pro plan differences.

## Product Summary

- Free plan: report-only mode, estimated potential savings range, basic workflow signals, no active backend routing policies.
- Pro plan: workflow-level routing, analyzer-backed recommendations, policy learning, safety guards, and per-workflow controls.
- Trust model: show where MargIQ saves money, where it refuses to optimize, and how each workflow can be controlled.
- Developer setup: install MargIQ in the backend/server-side AI module, keep existing provider credentials unchanged, add only MargIQ API credentials, pass `provider` and `availableModels`, and keep the normal provider response shape.

## Language To Use

Use: workflow, routing path, optimized model, safety guard, Automatic, Report only, Disabled.

Avoid: workflow hashes, variant hashes, rule IDs, embeddings, thresholds, raw policy JSON.

## Contact

- Email: support@getmargiq.com