feature
SLM Training Kit
Fine-tune small, private, specialised models on your own data.
The problem
Frontier LLMs are costly, hard to govern, and require sending data outside your walls. Many tasks are better served by a small, private, purpose-trained model.
What it does
Guided fine-tuning and distillation on your proprietary data.
Training and inference entirely within your environment, including air-gapped.
Task-level evaluation against larger models to prove sufficiency.
Versioning, deployment, and monitoring of private models.
The Outcome
Cheaper, faster, private models that keep sensitive data in-house and reduce dependence on external providers.
See how it scales in your environment
Talk through multi-tenant isolation and governance with our team.