Private LLM & On-Premise AI Deployment

A private LLM deployment typically costs Rs 20-50 lakhs for initial setup including infrastructure, model fine-tuning, and production deployment. Ongoing GPU infrastructure costs Rs 2-8 lakhs/month depending on usage. At scale (10,000+ daily queries), private deployment costs 60-80% less than API-based solutions like OpenAI — while keeping all data within your network.

The best open-source LLMs for on-premise deployment in 2025-2026 are: Llama 3.1 (405B, 70B, 8B variants by Meta), Mistral Large and Mixtral, Microsoft Phi-3, Google Gemma 2, and DeepSeek-V3. For Indian language support, Sarvam AI and AI4Bharat models work well. Model choice depends on your use case, hardware, and latency requirements.

RBI's data localization rules require that financial data of Indian customers is stored and processed within India. Sending customer queries containing financial data to OpenAI's US servers potentially violates these rules. Private LLM deployment on Indian data centres (AWS Mumbai, Azure Pune) ensures full compliance while enabling AI capabilities for banking, insurance, and fintech applications.

For domain-specific tasks, yes — often exceeding it. A Llama 70B model fine-tuned on your industry data typically outperforms GPT-4 on your specific use cases while being 10x cheaper to run. For general knowledge tasks, GPT-4/Claude remain stronger. The optimal approach is often hybrid: private LLM for sensitive data tasks, API-based LLM for general tasks.

Boolean & Beyond is a software engineering company in Bangalore (Bengaluru) specializing in private LLM deployment for enterprises. We handle model selection, infrastructure setup, fine-tuning, and production deployment on AWS, Azure, GCP, or bare-metal servers. We serve BFSI, healthcare, and government clients in Bengaluru, Coimbatore, and across India.