Open-source LLM development and private AI
Open-weight models like Llama, Mistral, and Qwen can run entirely inside your own infrastructure — so sensitive data never leaves your environment, and costs are predictable at high volume.
We select, fine-tune, and deploy open-source models on your cloud or on-premise hardware, with the same retrieval, evaluation, and monitoring we use for hosted models.
What we build with Open-Source LLMs
Private AI assistants
Assistants over confidential data, running fully in your environment.
Fine-tuned models
Smaller models fine-tuned for your specific task and tone.
High-volume pipelines
Classification and extraction at volumes where API costs add up.
On-device & edge AI
Compact models for mobile and edge deployments.
Why teams choose Open-Source LLMs
- Data stays entirely within your infrastructure
- Predictable costs at high volume
- Full control over model versions and fine-tuning
When we'd suggest something else
For the hardest reasoning tasks, frontier hosted models may still be more capable; hybrid setups can route only sensitive or high-volume work to open-source models.
We're model-agnostic — we recommend what fits your use case, not a favourite vendor.
Related AI services
Open-Source LLMs FAQs
Other technologies
Building with Open-Source LLMs?
Talk to an engineer who has shipped it in production — free, no obligation.