Tenancy & API

Stand up your inference in an afternoon.

Internal team or outside company — set up a tenancy, mint a key, and point your existing OpenAI client at Lucair. We can run the local inference for you or stand up dedicated APIs, exactly as we did for our first client, RW Exprès.

Self-serve setup

Create a tenancy, generate scoped API keys, set quotas — internal or external, isolated by default.

Managed local inference

We host and operate the models on our GPUs; you consume them. No infra to run.

Dedicated APIs on request

Need a bespoke surface like RW Exprès? We stand up tenant-specific endpoints and routing.

Data stays home

Private content is embedded and served locally — it never leaves to a third party unless you allow it.

# Point any OpenAI client at Lucair
from openai import OpenAI
client = OpenAI(
    base_url="https://lucair.ai/v1",
    api_key="sk-luc-…your-tenant-key…",
)
r = client.chat.completions.create(
    model="auto",  # let Lucair route
    messages=[{"role":"user", "content":"Résume ce contrat."}],
)
# served by Luca V4 · local · 0.2×
print(r.choices[0].message.content)

Our first tenant — a French AI-seat product — runs its terminal chat and document RAG on Lucair, with Luca V4 as the Starter baseline and escalation only when a task earns it.