Low-friction fine-tuning that aligns model behavior, accuracy, and outputs to your data — no ML expertise or infrastructure management required.
Fine-tune models with your own data to align behavior, accuracy, and outputs to your specific enterprise use case and domain.
Lower the cost and complexity of fine-tuning through a guided, simplified workflow — only exposing advanced settings when you need them.
Move tuned models into production in a repeatable, governed flow — from experiment to deployment with full auditability.
Upload your dataset and fine-tune any supported foundation model to match your domain language, tone, and output format. The model learns from your data — not generic training sets.
CIVI Fine Tuning is built to be simple by default. Advanced hyperparameters are hidden unless you need them — so any developer can start fine-tuning without a machine learning background or infrastructure knowledge.
Every fine-tuned model follows a structured, auditable path to production. Version your models, track training runs, and deploy with confidence using CIVI's governed deployment pipeline.
Customize a foundation model to your enterprise data — no ML expertise or infrastructure needed.