---
license: gemma
base_model: google/gemma-3-12b-it
language: [en]
tags: [legal, tax, incorporation, startup, ollama, gemma3]
---

# FR-Start — Startup Incorporation Advisor

**Fahrenheit Research** · Runs 100% locally via [Ollama](https://ollama.com) · No API, no cloud, no data leaves your machine.

FR-Start tells startup founders **where to incorporate and why**, across the **United States, India, the UAE, Singapore, and the United Kingdom**. It runs a structured intake, then applies a fixed decision priority — investors > market access > founder tax residency > compliance cost > tax — grounded in a curated, dated knowledge corpus covering:

- corporate & indirect tax, entity types with pros/cons
- compliance load, setup cost/time, banking friction
- hiring & payroll costs, founder personal tax, exit & M&A treatment
- grants & incentives, cross-border rules (flips, PE/POEM, withholding, transfer pricing, FEMA)
- step-by-step incorporation playbooks per jurisdiction

## Architecture

This is a **knowledge-augmented model**, not a fine-tune: the base model is **Gemma 3 12B (12 billion parameters)**, and all regulatory facts live in an auditable Markdown corpus fused into the model's system layer at build time. Facts carry `as_of: 2026-08` dates (web-verified August 2026). Updating a tax rate is a one-line corpus edit + rebuild — no training run.

## Use

```bash
ollama pull gemma3:12b
ollama create fr-start -f Modelfile
ollama run fr-start "SaaS founder in Bangalore raising from US VCs — where do I incorporate?"
```

Needs ~10 GB RAM. The `corpus/` directory in this repo is the full knowledge base — edit it, bump the `as_of` dates, and re-run `ollama create` to refresh.

## Limitations

- **Not legal or tax advice.** Rates and rules change; every answer carries as-of dates and must be verified with a qualified professional before acting.
- Covers only the five listed jurisdictions.
- A 12B local model: reliable on corpus-grounded questions, thinner on novel multi-jurisdiction edge cases than frontier models.

Base model weights are Google's Gemma 3, used under the [Gemma Terms of Use](https://ai.google.dev/gemma/terms). This repo distributes only the knowledge corpus, Modelfile, and tooling.