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I’d recommend OPNsense over PFsense due to multiple shady moves by netgate (the parent company of pfsense), including moving to closed-source:

• pfsense is falsely open-source: https://news.ycombinator.com/item?id=26476030
• pfsense botched/rushed their wireguard implementation: https://forum.endeavouros.com/t/migration-from-pfsense-to-opnsense-drama-about-wireguard/12798
• pfsense squatted on competitor domain and used underhanded/defamatory practices: https://opnsense.org/opnsense-com/

If you don’t mind the drama, both PFsense and OPNsense are perfectly competent router OSes.

Regarding hardware:

• OPNsense also sells rack-mountable server hosts.
• OP may not actually need a rack-mounted server – I have several machines just sitting on a 2u rack-mounted shelf. My opnsense install runs on a cheap protectli box, and there’s enough room for a handful of raspberry pis and their power bricks on the shelf next to it.

It’s not just every tech company, it’s every company. And it’s terrifying - it’s like giving people who don’t know how to ride a bike a 1000hp motorcycle! The industry does not have guardrails in place and the public consciousness “chatGPT can do it” without any thought to checking the output is horrifying.

I don’t think fine tuning works the way you think it does; one does not generally fine tune to “add facts”. This might be useful: https://nextword.substack.com/p/rag-vs-finetuning-llms-what-to-use

I’d advocate for using the RAG pattern to do the lookups for the new facts. If needed, you can fine tune the model on top to output for your specific domain or format.