AI Fine-Tuning Services in India
Make AI models that understand YOUR business. We fine-tune LLMs on your domain data, whether that is medical terminology, legal language, financial regulations, product catalogs, or any specialized knowledge. Better accuracy, lower costs, consistent outputs. From data preparation to deployed custom model.
Proof-First Delivery
Measurable Outcomes We Optimize For
What We Offer
Service Modules Built for Production
Each module is designed as a production block with integration boundaries, governance hooks, and measurable outcomes.
Training Data Curation
The quality of fine-tuning depends on data quality. We help you collect, clean, format, and augment training examples. Instruction-response pairs, preference data for DPO/RLHF, and synthetic data generation to fill gaps in your dataset.
LoRA & QLoRA Fine-Tuning
Parameter-efficient fine-tuning that adapts large models on modest hardware. LoRA for full precision, QLoRA for 4-bit quantized training. Fine-tune 70B parameter models on a single A100 GPU. Merge adapters for production deployment.
Full Fine-Tuning
Full parameter training for maximum model adaptation. Multi-GPU training with DeepSpeed and FSDP. When your domain is significantly different from the base model training data and LoRA is not enough.
OpenAI Model Fine-Tuning
Fine-tune GPT-4o and GPT-4o-mini via OpenAI API. Training data preparation in JSONL format, hyperparameter optimization, evaluation metrics, and A/B testing against base models.
Model Evaluation & Benchmarking
Rigorous evaluation against your domain benchmarks. Automated evaluation suites, human evaluation frameworks, A/B testing, and regression detection. Know exactly how much better your fine-tuned model performs.
Deployment & Serving
Deploy fine-tuned models with vLLM, TGI, or Ollama. GPU-optimized inference, model quantization (GGUF, GPTQ, AWQ), auto-scaling, and API endpoints. On-premise or cloud deployment with monitoring.
Delivery Proof
See Our Work in Action
Selected engagements that show architecture depth, execution quality, and measurable business impact.
Delivery Advantages
Why Choose Boolean & Beyond
Training Data Curation
The quality of fine-tuning depends on data quality. We help you collect, clean, format, and augment training examples. Instruction-response pairs, preference data for DPO/RLHF, and synthetic data generation to fill gaps in your dataset.
LoRA & QLoRA Fine-Tuning
Parameter-efficient fine-tuning that adapts large models on modest hardware. LoRA for full precision, QLoRA for 4-bit quantized training. Fine-tune 70B parameter models on a single A100 GPU. Merge adapters for production deployment.
Full Fine-Tuning
Full parameter training for maximum model adaptation. Multi-GPU training with DeepSpeed and FSDP. When your domain is significantly different from the base model training data and LoRA is not enough.
OpenAI Model Fine-Tuning
Fine-tune GPT-4o and GPT-4o-mini via OpenAI API. Training data preparation in JSONL format, hyperparameter optimization, evaluation metrics, and A/B testing against base models.
FAQ
Frequently Asked Questions
Ready to Fine-Tune Your AI?
Tell us about your domain and data — we'll assess whether fine-tuning is the right approach and design a training pipeline that delivers measurable accuracy improvements.