AI Models Trained on Your Data. Not Generic Ones.
General-purpose LLMs fail at specialized tasks. We fine-tune foundation models on your proprietary data — creating AI that understands your domain, speaks your language, and outperforms out-of-the-box alternatives.
Discuss Your Fine-tuning Project →What is LLM fine-tuning and when do you need it?
LLM fine-tuning is the process of training a pre-trained language model further on a domain-specific dataset to improve its performance on specialized tasks. You need fine-tuning when general-purpose models produce inaccurate results for your domain (legal, medical, financial, engineering), when you need consistent formatting or tone not achievable through prompting, when latency and cost optimization require a smaller specialized model, or when you need to incorporate proprietary knowledge that cannot be embedded in context windows.
Fine-tuning Capabilities
From data preparation to model deployment — we handle every step of the fine-tuning pipeline.
Domain Adaptation
Fine-tune models on legal, medical, financial, or technical corpora for dramatically better accuracy on specialized queries.
Instruction Tuning
Train models to follow specific formats, personas, and task instructions consistently across all outputs.
Proprietary Knowledge Injection
Encode your internal documents, policies, and domain knowledge directly into model weights for always-available context.
Model Distillation
Distill large frontier models into smaller, faster, cheaper models that maintain high accuracy on your specific tasks.
RLHF & Preference Tuning
Use reinforcement learning from human feedback (RLHF) or DPO to align model outputs with your quality standards.
Safety & Alignment Tuning
Fine-tune models to refuse specific types of outputs, adhere to compliance requirements, and maintain safe behavior.
Code & Technical Models
Specialize models for your codebase, programming languages, or technical documentation for better developer tooling.
Evaluation & Benchmarking
Build custom evaluation datasets and benchmarks to measure model performance before and after fine-tuning.
Ready to Build a Model That Actually Knows Your Domain?
Stop fighting general-purpose models. Fine-tune on your data and get AI that speaks your language.
Discuss Your Fine-tuning Project →