RAG ImplementationCustom Model Training & Distillation

Custom Models for RAG Systems

Train custom embedding, reranking, and generation models optimised for RAG pipelines. We fine-tune models that improve retrieval accuracy and response quality for your domain.

RAG Implementation Capabilities for Custom Model Training & Distillation

RAG-optimised embedding training

Custom reranker development

Generation model fine-tuning for RAG

Retrieval quality evaluation

End-to-end RAG benchmarking

Use Cases

1

Domain-tuned embeddings for enterprise RAG

2

Custom rerankers for improved retrieval precision

3

Fine-tuned generators for grounded responses

4

Specialised RAG models for regulated industries

Integration Details

RAG Implementation

Retrieval-Augmented Generation systems that deliver accurate, grounded responses. We solve the hard problems: chunking, retrieval quality, and hallucination prevention.

All embedding modelsVector databasesDocument pipelinesLLM providersEnterprise systems

Custom Model Training & Distillation

Training domain models on curated corpora, applying NeMo and LoRA distillation, and wiring evaluation harnesses so accuracy stays high while latency and spend drop.

NVIDIA NeMo MicroservicesHugging Face TransformersLoRA & QLoRADeepSpeed & MegatronRAG Evaluation HarnessesPromptFlow & TruLensWeights & Biases

Ready to Implement RAG Implementation for Custom Model Training & Distillation?

Let's discuss how we can help you leverage rag implementation within your custom model training & distillation strategy.

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