The top 10 public-use sectors in India for LLM (Large Language Models) applications and the best suited LLM models for each sector, along with costing information, can be summarized as follows:
| Sector | Best LLM Model | Description | Cost Information (Approx.) |
|---|---|---|---|
| Finance | Specialized for financial analysis, risk management, sentiment analysis, customer service automation, and market forecasting. Sesame is region-specific for Indian financial data. | OpenAI GPT-4o pricing around $0.0005 to $0.005 per 1k tokens. Sesame pricing not publicly available but anticipated to be competitive for BFSI. | |
| Law | Legal research and case law analysis platforms focused on Indian law, enabling faster case research, document analysis, and drafting support. | Lexlegis AI pricing details not public; VIDUR AI targets professional legal users with subscription models. | |
| Education / Study | Multilingual LLMs supporting 10 Indian languages, text summarization, question answering, translation. Tailored for Indian regional languages. | Open-source based or institutional partnerships; generally low-cost or free for research use. | |
| General Purpose | High-parameter models suitable for varied NLP tasks including coding, reasoning, multilingual support. | GPT-4o: $0.00125 to $0.005 per 1,000 tokens processing; Claude 3 pricing comparable; Falcon pricing varies by access. | |
| Research | Efficient models suited for deep learning, text generation, coding, with open access for research & commercial use. | Llama 3 is free for research/commercial; Stable LM 2 low cost and open source. | |
| Public Sector (e-Governance) | Custom domain LLMs, potentially based on GPT or open source | Tailored models for governmental workflows, document processing, citizen services. | Government/enterprise contracts; pricing varies widely by deployment. |
| Healthcare | Domain-adapted medical LLMs (emerging) | Focus on medical documentation, diagnostics support, patient communication. | Typically enterprise priced, no public flat-rate pricing available. |
| Customer Service |
FinRobot for BFSI |
Automated chatbots and virtual assistants for customer query handling, product recommendations. | OpenAI business tier pricing or custom BFSI solutions; $0.001-$0.01 per 1k tokens. |
| E-commerce | Custom LLMs for product recommendation and UGC generation | Personalized customer engagement, reviews generation. | Pricing depends on provider; small to medium-scale deployments start from hundreds to thousands USD monthly. |
| Agriculture / Rural Development | Multilingual and regional NLP models (e.g., Bhashini) | Information dissemination in local languages, advisory services. | Typically open source or subsidized by government projects. |
Types of Copilots and LLMs for Technology and Coding
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Code Completion and Autocomplete Copilots
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These provide real-time code suggestions, autocompletions, and snippets directly inside IDEs.
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Example: GitHub Copilot, Tabnine, Cursor
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Use case: Speeding up coding with inline suggestions and error prevention.
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Text-to-Code Generative Models
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Generate entire code blocks, functions, or classes from natural language descriptions.
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Example: OpenAI GPT-5, Google Gemini Coder
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Use case: Rapid prototyping, boilerplate generation, coding from non-programmer input.
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Code Review and Bug Detection Assistants
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Analyze code for potential bugs, security risks, and best practice violations.
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Example: Amazon CodeWhisperer, DeepCode (Snyk)
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Use case: Improving code quality and security automatically.
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Collaborative Coding Bots
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Assist in team environments by managing pull requests, suggesting improvements, and commenting on code.
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Example: GitHub Copilot Chat, Replit AI with collaboration features
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Use case: Enhancing remote teamwork and code discussion.
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Domain-Specific Coding LLMs
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Specialized models trained on particular programming languages or technology stacks.
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Example: Salesforce CodeGen (for Apex), Meta Llama Codex (open-source multi-language)
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Use case: Deep expertise in a targeted language or ecosystem.
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Open-Source Self-Hosted LLMs for Coding
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Models that can be deployed and customized locally or on private infrastructure.
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Example: Meta Llama 4 Scout, DeepSeek, Qwen Coder
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Use case: Security-conscious organizations or advanced developers wanting custom AI coding assistants.
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Disclaimer: This information is based on research and personal analysis. While efforts have been made to ensure accuracy, the content may contain inaccuracies or become outdated. I welcome any comments, suggestions, or corrections to improve the quality and relevance of this information.
