LLM Fine-Tuning & Model Training
Train custom AI models that speak your domain's language with precision
Fine-tune foundation models on your proprietary data and domain knowledge to create specialized AI models that outperform generic LLMs on your specific tasks — with superior accuracy, consistent brand voice, and lower inference costs.
Key Benefits
Core Technologies
Deep Dive: Fine-Tuning
Fine-tuning transforms a general-purpose LLM into a domain expert tailored to your organization. By training on your specific data, terminology, writing style, and decision patterns, fine-tuned models achieve dramatically better performance on your tasks while typically being faster and cheaper to run than prompting larger base models.
We implement the full spectrum of fine-tuning techniques: supervised fine-tuning (SFT) for task adaptation, RLHF (Reinforcement Learning from Human Feedback) and DPO (Direct Preference Optimization) for alignment to human preferences, and PEFT methods like LoRA and QLoRA for efficient training on limited hardware.
Our fine-tuning projects span diverse domains: legal document classification, medical coding assistance, financial analysis, Hindi-English code-switching for Indian markets, custom employee assessment scoring, and domain-specific question answering. We handle everything from dataset curation and quality filtering to training, evaluation, and deployment.
Beyond accuracy, we optimize fine-tuned models for production: quantization for inference speed, GGUF/GPTQ formats for efficient deployment, safety evaluation, and rigorous red-teaming to ensure the model behaves appropriately in all edge cases your production environment might encounter.
Key Features & Capabilities
Everything included in our Fine-Tuning service offering.
Dataset Curation & Preparation
Systematic collection, cleaning, deduplication, quality filtering, and formatting of training data to maximize fine-tuning outcomes.
LoRA / QLoRA Training
Parameter-efficient fine-tuning using LoRA adapters — achieving 95%+ of full fine-tuning performance at a fraction of the compute cost.
RLHF & DPO Alignment
Human preference learning to align model outputs with your organization's values, tone, and quality standards.
Multi-Task Fine-Tuning
Train a single model to excel at multiple related tasks simultaneously — reducing model inventory and simplifying your AI infrastructure.
Evaluation & Benchmarking
Rigorous evaluation on held-out test sets, domain-specific benchmarks, and comparison against baseline models to quantify improvement.
Production Optimization
Model quantization (INT4, INT8), GGUF conversion, vLLM/TGI deployment, and inference optimization for your latency and cost targets.
Use Cases
How organizations across industries are leveraging Fine-Tuning.
Employee Assessment Scoring
UNO MINDA uses a fine-tuned model to consistently evaluate SAP competency assessments, achieving inter-rater reliability that surpasses human evaluators.
Indian Language Processing
Fine-tuned models for Hinglish (Hindi-English code-switching), regional language support, and India-specific business terminology.
Legal Document Classification
Custom models trained on corporate legal documents to automatically classify, extract key clauses, and flag risks with high precision.
Customer Communication Style
Brand-voice fine-tuning for customer communications, ensuring all AI-generated content matches your organization's established tone and guidelines.
Deliverables & Outcomes
A complete engagement includes all of the following — no hidden extras, no scope surprises. Our ISO 9001:2015 certified process ensures every deliverable meets documented quality standards.
Tools & Technologies
Best-in-class tools selected for your specific requirements — balancing performance, cost, and long-term maintainability.
Related Services
Ready to Deploy Fine-Tuning?
Let's discuss your specific requirements and design a solution that delivers real business outcomes -- not just impressive demos.