| --- |
| license: gemma |
| base_model: google/gemma-3-12b-it |
| language: [en] |
| tags: [legal, tax, incorporation, startup, ollama, gemma3] |
| --- |
| |
| # FR-Start — Startup Incorporation Advisor |
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| **Fahrenheit Research** · Runs 100% locally via [Ollama](https://ollama.com) · No API, no cloud, no data leaves your machine. |
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| 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: |
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| - 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 |
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| ## Architecture |
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| 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. |
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| ## Use |
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|
| ```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?" |
| ``` |
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| 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. |
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| ## Limitations |
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| - **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. |
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| 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. |
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|
