LLM stands for large language model. It is a neural network — typically a transformer architecture with billions of parameters — trained on vast text datasets to predict the next token in a sequence. Modern LLMs (GPT-5, Claude Sonnet, Gemini 2, Llama 4) can hold conversations, write code, summarise documents, answer questions, and reason about complex problems.
LLMs power everything from ChatGPT to production RAG systems to coding copilots. Nagro Solutions builds LLM-integrated features across the OpenAI, Anthropic, and open-source (Llama, Mistral) provider space — chosen based on the client's use case, latency tolerance, data-sensitivity requirements, and budget.
Key concepts LLMs bring: context window (how much input the model can attend to), tokens (the units of input and output), hallucination (the tendency to invent plausible-sounding wrong answers), and fine-tuning (retraining on domain-specific data).