Finetune any open-weight model on your internal knowledge - and run it at whatever scale you have, from a single box to a datacenter. No data sent to a vendor, no per-seat bill, no model changing under you.
Your documents, code, and tickets are turned into a specialized model - the durable value is the pipeline that turns messy data into a working expert.
The finetuned weights and adapters are files you own. They stay private to your team - nothing leaves unless you decide it should.
You don't start from zero. Begin from a strong open-weight model - Qwen, Llama, Mistral and more - then add the parts only your company knows.
Once trained, it runs on your hardware. Ask it a million questions; the cost is your own electricity, not a meter.
At any scale
The same pipeline finetunes a model of any size. You pick the base that fits your hardware and your budget.
A compact model on the card you already have. Fast, cheap, private - specialization where a small model gains the most.
A mid-size model on a modest server. More capacity, serving a whole team locally.
A large model on serious hardware or a GPU cluster. The same pipeline, tuned for maximum capability.
You start from a public open-weight model - but anything trained on your data is yours to hold back.
Same mechanism, different needs.
Finetune on your handbook, codebase, and past tickets so new hires get correct answers from day one.
Health, legal, finance - data that legally can't leave the building can still power a capable assistant.
Underserved language or a narrow domain the big models ignore? Make a model fluent in exactly your world.
When a stronger open-weight model comes out, we help you move your specialization onto it - re-running the pipeline on the newer base, on your schedule. No vendor migration, no renegotiation, nothing left stranded. Your edge stays private; your model keeps improving.
Private by default, finetuned from your data, running on your own infrastructure - at any scale.
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