FR-Start — Startup Incorporation Advisor
Fahrenheit Research · Runs 100% locally via
Ollama · 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
1ollama pull gemma3:12b
2ollama create fr-start -f Modelfile
3ollama 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. This repo distributes only the knowledge corpus, Modelfile, and tooling.
