ML Finetuning Solutions

We fine-tune language, vision and speech models on your data so they perform better on your specific tasks than general-purpose models, at lower cost and latency.

What We Offer

• Data Preparation & Curation: Collect, clean, label and balance training data, with privacy and PII handling built in
• Efficient Fine-Tuning: LoRA, QLoRA and full fine-tuning of open-source and hosted models
• Evaluation & Benchmarking: Task-specific test sets and side-by-side comparison against base models and prompts
• Deployment & Serving: Optimised inference on cloud or private infrastructure, with versioning and rollback
• Continuous Improvement: Feedback loops and scheduled retraining as your data and needs change

Benefits

Higher accuracy on domain tasks, consistent brand voice, smaller and faster models, and full control over where your data and models live.

Use Cases

• Domain-specific assistants for finance, health and legal
• Classification, extraction and routing at scale
• Brand-tone content generation
• Distilling large models into smaller, cheaper ones