Model Fine-Tuning
Optimize foundation models on your proprietary data. Get 3-10x accuracy improvements while reducing inference costs by up to 70%.
Fine-Tuning Techniques
LoRA Fine-Tuning
Low-rank adaptation for efficient fine-tuning with minimal compute. Perfect for adapting large models to specific domains.
QLoRA
Quantized LoRA for fine-tuning on consumer GPUs. 4-bit quantization with no quality loss for cost-effective training.
Full Fine-Tuning
Complete parameter updates for maximum performance when you need the best possible results on your domain.
Data Curation
We help prepare, clean, and format your training data with quality scoring and deduplication pipelines.
Evaluation Suite
Custom benchmark suite tailored to your use case with automated regression testing and quality gates.
Secure Training
All training happens in isolated VPCs. Your data never leaves your designated region. SOC2 compliant.
Supported Base Models
Common Use Cases
Domain-Specific Chatbots
Fine-tune for customer support, sales, or internal knowledge bases.
Code Generation
Train models on your codebase for internal tooling and autocomplete.
Document Processing
Extract structured data from invoices, contracts, and forms.
Content Generation
Adapt models to your brand voice and content style guidelines.
Make your models work harder
Share your requirements and we'll recommend the right fine-tuning approach.
Talk to an Expert