LLM Development Services
Custom Language Models for Your Business
Go beyond generic AI with language models trained on your data and optimized for your use cases. We develop, fine-tune, and deploy LLMs that understand your domain.
Custom LLM Development
Adapt pre-trained models to your specific domain, terminology, and use cases. Get better results than generic models for your particular needs.
Train models from scratch or continue training on your proprietary data for truly unique capabilities.
Reduce model size and inference costs while maintaining quality. Quantization, distillation, and architecture optimization.
Production-ready model serving with proper scaling, monitoring, and cost optimization.
Fine-tuning
Adapt pre-trained models to your specific domain, terminology, and use cases. Get better results than generic models for your particular needs.
Custom Training
Train models from scratch or continue training on your proprietary data for truly unique capabilities.
Model Optimization
Reduce model size and inference costs while maintaining quality. Quantization, distillation, and architecture optimization.
Deployment & Serving
Production-ready model serving with proper scaling, monitoring, and cost optimization.
LLM Services
Domain Fine-tuning
Adapt models to your industry terminology and knowledge.
Instruction Tuning
Train models to follow your specific instructions and formats.
RLHF Implementation
Reinforcement learning from human feedback for better outputs.
Model Evaluation
Rigorous testing and benchmarking of model performance.
Cost Optimization
Reduce inference costs through model optimization techniques.
Private Deployment
Deploy models in your own infrastructure for data privacy.
LLM Expertise
Custom models that outperform generic alternatives.
25+
Models Fine-tuned
40%
Avg. Quality Improvement
60%
Cost Reduction
Need Custom LLM?
Explore how custom language models can improve your AI applications.
LLM Success
Legal Firm Fine-tunes LLM for Contract Analysis
"The fine-tuned model understands legal terminology and contract structures in ways generic models simply cannot. Accuracy improved dramatically."Read Case Study
LLM Best Practices
Data Quality First
High-quality training data is essential for good results.
Evaluation Rigor
Comprehensive testing before and after fine-tuning.
Bias Monitoring
Active monitoring and mitigation of model biases.
Version Control
Proper versioning of models and training data.
Cost Awareness
Clear understanding of training and inference costs.
Fallback Planning
Strategies for when custom models underperform.
Delivering Intelligent Solutions Across
10+ Industries
LLM Development Tools
Automated pipeline for LLM fine-tuning and evaluation.
Comprehensive benchmarks for model quality assessment.
Tools for preparing and validating training data.
Production-ready model serving with auto-scaling.
Why Equiwiz for LLM Development
Deep expertise in language model customization.
- Experience across multiple model architectures
- Rigorous evaluation and testing methodology
- Cost-conscious approach to training and serving
- End-to-end from data preparation to deployment
LLM FAQ
It depends. RAG is better for dynamic knowledge; fine-tuning for behavior and style. We often combine both approaches.
It varies by use case. Sometimes hundreds of examples suffice; complex domains may need thousands. We help you determine requirements.
We optimize for cost-effectiveness. Techniques like LoRA and QLoRA dramatically reduce training costs while maintaining quality.
Yes, we can fine-tune using your infrastructure or secure cloud environments. Your data never leaves your control.