Open-weight LLMs deployed inside your network, on GPUs you control, behind an OpenAI-compatible endpoint. Scroll to run the clock through a sample schedule.
The 72 hours begin once we have access to your environment and the prerequisites are in place. Not before.
Deliverable: confirmed start. Fixed price $4,900.
We pick from the models we deploy and load it onto your GPUs. Nothing is sent to a third-party API.
Sample logweights fetched ok checksum verified ok loaded on GPU 0 in your network
Deliverable: the model, running on your hardware.
The model is quantized and tuned to run on the GPUs you control, so the pilot reflects what production would cost you.
Deliverable: a model sized to your GPUs.
Your applications talk to it the way they talk to OpenAI today.
client = OpenAI( base_url="https://llm.yourcompany.internal/v1", # inside your network api_key="your-key", )
Same SDK. Change the base URL.
Sample pingPOST /v1/chat/completions
served from inside your networkDeliverable: a working OpenAI-compatible endpoint.
The model is measured on your own material, so the decision rests on your results and not on a public leaderboard.
Deliverable: reference evaluation on your data.
You leave with a measured result on your data and a scoped plan for production. The pilot costs $4,900, fixed.
Next rung: production deployment from $25,000
The last hours produce a written result on your data and a check of the network boundary. The traces here are demo telemetry that show the format, not your numbers.
external endpoints0
Scan complete. 4 internal nodes.
The 72 hours begin once access and prerequisites are in place, so the schedule above is never spent waiting on us or on you.
Tell us the model, the data and the GPUs you have. An engineer from Limassol or Auckland scopes the 72-hour pilot with you.
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