ColibriCode

What we manage

  • Private LLM hosting

    Open-weight models deployed on dedicated GPU infrastructure, isolated per client.

  • RAG pipelines

    AI that answers from your documents, databases and knowledge base, with source citations.

  • Model gateway

    One secure endpoint across private and public models, with usage quotas per team.

  • Monitoring and evaluation

    Latency, accuracy, cost per request and alerts.

  • Model updates

    Tested upgrades as better models are released, without breaking your apps; plus AI cost optimization through model routing, caching and hard spending caps.

Why run AI with us

  • Your data stays yours.

    Private deployments keep prompts and documents out of public model training.

  • Predictable spend.

    Hard spending caps and monthly cost reports, not surprise invoices.

  • Engineers who run GPUs every day.

    We operate high-performance AI serving for our own products.

  • No lock-in.

    Standard, portable architecture on Google Cloud, Azure, AWS or on-premises.

Private LLM vs. public AI API

CriteriaPublic AI APIPrivate LLM with ColibriCode
Data controlSent to a third-party providerStays in an isolated environment
Cost at high volumeGrows with every requestFlatter, capacity-based
CustomizationLimitedFine-tuning on your data possible
Best forPilots, low volumeRegulated data, steady volume

Frequently asked questions

What is private LLM hosting?

Running a large language model on infrastructure dedicated to your company instead of sending data to a shared public AI service.

What is RAG?

Retrieval-augmented generation: the AI looks up your own documents before answering, so responses are grounded in your data.

Can we combine private and public models?

Yes. Our gateway routes each request to the right model by cost, speed and sensitivity.

Get a private AI cost estimate