What are Good Use Cases for Integrating LLMs into Our Own Products?

YES! You can integrate LLMs into your projects, products, and platforms. Some LLMs are available for outside companies like yourself, and some are not. For example, OpenAI provides an API to call their LLMs and pay per use. Building your own LLM is not an easy task. Companies like OpenAI spent billions of dollars to build these initial LLMs and continue to improve them. Building LLM is not just collecting data from all over the world, but also training these models.  The training cost alone for GPT 3.5 was more than $200 million for OpenAI. 

However, you can easily integrate LLMs into your website, app, product, or platform. Since most LLMs are not free, you need to buy a license to use them.

Let's look at some of the popular use cases of integrating LLMs into your own products and platforms:

✅ LLMs in Customer Support

• 🤖 Integrate LLMs into chatbots or help desks to handle common queries and escalate complex ones.
• Benefit: Reduces support tickets and response time.

Here are some companies that are using LLMs in customer support:

• JPMorgan Chase: Uses LLMs to assist financial advisors with client insights and automate customer support tasks.
• Morgan Stanley: Leverages OpenAI to help wealth managers retrieve insights from internal documents.
• Shopify: Integrates ChatGPT to help merchants with store setup, product listings, and customer questions.
• Instacart: Offers a GPT-powered chatbot to suggest recipes and assist users with grocery planning.
• Klarna: Uses OpenAI’s chatbot to automate 65% of customer service chats across multiple languages.
• Microsoft: Powers its Copilot features in Office and Azure customer support with LLMs.
• Zendesk: Enhances ticket responses and automates support workflows using LLMs.
• Intercom: Built a GPT-4 powered chatbot to respond to customer queries in real-time.
• Salesforce: Uses Einstein GPT to generate support replies and help agents assist customers faster.
• Expedia: Offers a ChatGPT-based trip planning assistant that guides users through bookings.

✅ LLMs in Content Generation

• ✍️ Auto-generate product descriptions, emails, reports, or social media content from structured data.
• Example: Turn bullet points into full articles or campaign copy.

Examples

• BuzzFeed: Uses OpenAI to generate personalized quizzes, listicles, and creative content at scale.
• The Associated Press (AP): Employs AI to automate news summaries, earnings reports, and data-driven stories.
• Canva: Integrates LLMs to auto-generate social media posts, blog headlines, and marketing copy.
• HubSpot: Uses LLMs in its content assistant to help marketers write blogs, emails, and campaign copy.
• Jasper: Built entirely around LLMs, it helps businesses create marketing content, ad copy, and blog articles.
• Grammarly: Uses LLMs in its “GrammarlyGO” feature to rewrite, expand, or ideate content across contexts.
• Notion: Offers “Notion AI” to generate meeting notes, project summaries, and knowledge base content.
• Shopify: Powers product descriptions and customer-facing content with LLM-generated text.
• Copy.ai: AI-first company that helps users create landing pages, email campaigns, and SEO content using LLMs.
• LinkedIn: Uses LLMs to assist users in writing profile summaries, job descriptions, and messaging templates.

✅ LLMs in Coding Assistance

• 👨‍💻 Embed AI coding assistants into IDEs, internal platforms, or DevOps tools.
• Examples: Autocomplete code, generate test cases, explain code logic, suggest refactors.

Examples

• GitHub Copilot: Autocompletes code and generates functions using OpenAI’s Codex, integrated into major IDEs.
• Amazon CodeWhisperer: Offers real-time code suggestions optimized for AWS and secure coding practices.
• Google Gemini (Codey): Assists coding in Colab and Cloud tools with contextual code generation and fixes.
• Replit Ghostwriter: AI assistant built into Replit IDE for code generation, explanation, and debugging.
• Tabnine: Privacy-focused AI that provides fast and relevant code completions across multiple languages.
• Sourcegraph Cody: Helps developers understand large codebases through conversational code search and Q&A.
• Cursor: A GPT-4-powered coding IDE that merges AI chat with code editing in a custom VS Code fork.
• Codeium: Free AI assistant offering autocomplete and natural language search in over 70 languages.
• Magic.dev: Builds autonomous AI engineers capable of writing and modifying full software components.
• Kite: Pioneered AI code completion before being acquired by Databricks (now discontinued).

✅ Healthcare: LLM Integration Use Cases

1. Patient Symptom Triage Assistants

• LLMs can power chatbots or voice agents that ask users about symptoms and guide them on next steps (e.g., self-care, visit a doctor, call emergency).
• Benefits: Reduces burden on front-desk staff, improves access to initial care.

2. Medical Documentation & Summarization

• Automatically summarize doctor-patient conversations, EHR notes, or transcribed consultations into structured SOAP notes.
• Use Case: Assist doctors by auto-generating visit summaries, discharge instructions, or referral letters.

3. Clinical Decision Support

• Help clinicians quickly find treatment guidelines, drug interaction information, or clinical trial options by asking natural-language queries.
• Example: “What are the latest NCCN guidelines for stage II lung cancer?”

4. Medical Coding & Billing Automation

• Extract diagnostic codes (ICD-10), procedure codes (CPT), and generate billing summaries from patient records.

5. Health Literacy and Patient Education

• Generate personalized, easy-to-understand health education content based on a patient’s condition and medical history.

Examples:

• Nabla: Uses LLMs to generate real-time medical documentation during patient-doctor conversations.
• Microsoft + Epic Systems: Integrates GPT-powered tools into Epic's EHR to draft patient messages and support clinical decision-making.
• Google DeepMind (Med-PaLM): Developed LLMs specifically trained to answer medical questions with expert-level accuracy.
• Abridge: Applies LLMs to transcribe and summarize medical visits, helping clinicians reduce administrative burden.
• Mayo Clinic: Collaborates with tech partners to explore LLMs for summarizing clinical notes and personalizing care plans.
• Hippocratic AI: Builds safety-focused LLMs tailored for non-diagnostic healthcare roles like follow-up calls and care coordination.
• Butterfly Network: Uses LLMs to assist with interpreting ultrasound images and generating diagnostic summaries.
• Ambience Healthcare: Uses generative AI to automate clinical note-taking, coding, and administrative workflows.
• Babylon Health: Implements LLMs in virtual assistants to triage patient symptoms and provide health guidance.
• Johns Hopkins Medicine: Experiments with LLMs to improve patient communication, summarize records, and streamline care workflows.

✅ Finance: LLM Integration Use Cases

1. Regulatory Document Summarization

• Summarize large compliance documents like KYC/AML policies, regulatory changes, or financial disclosures into digestible insights.

2. Client Communication Automation

• Draft personalized client emails, portfolio summaries, investment updates, or responses to common finance-related queries.

3. Financial Report Generation

• Automatically generate quarterly earnings summaries, audit reports, or executive dashboards from raw financial data.

4. Fraud Pattern Explanation

• LLMs can assist analysts by explaining suspicious activity patterns in plain English and recommending possible causes/actions.

5. Chat-based Portfolio Assistants

• Let clients query their portfolio or account: “What changed in my portfolio this month?” or “Suggest 3 mutual funds based on my risk profile.”

Examples

1. JPMorgan Chase: Uses LLMs to automate contract analysis and generate financial reports.
2. Morgan Stanley: Leverages OpenAI models to assist wealth advisors with research summarization.
3. Goldman Sachs: Employs LLMs for market trend analysis and automating compliance documentation.
4. Citibank: Uses AI chatbots powered by LLMs to handle customer service queries efficiently.
5. Capital One: Implements LLMs to personalize customer interactions and detect fraud patterns.
6. American Express: Uses LLMs to automate dispute resolution and optimize customer communications.
7. BlackRock: Applies LLMs for risk assessment and generating investment insights.
8. Wells Fargo: Deploys LLM-powered assistants for loan processing and customer support.
9. Stripe: Uses LLMs to automate invoice generation and customer onboarding communications.
10. Square (Block): Integrates LLMs to power AI-driven financial advice and bookkeeping automation.

✅ Learning / EdTech: LLM Integration Use Cases

1. AI Tutors and Study Helpers

• Build conversational agents that can explain topics, solve problems step-by-step, or quiz learners interactively.
• Example: “Explain the Pythagorean theorem with a real-life example.”

2. Automated Assessment Generation

• Generate MCQs, short answer questions, or coding challenges from lecture notes, articles, or video transcripts.

3. Student Feedback and Grading

• Use LLMs to provide personalized, constructive feedback on student essays, assignments, or code submissions.

4. Learning Path Personalization

• Analyze a learner’s progress and recommend personalized courses, topics, or exercises to improve weak areas.

5. Course Content Creation

• Speed up curriculum design by auto-generating lesson plans, video scripts, and reading material based on a topic.

Examples

• Duolingo: Uses LLMs to generate personalized language practice exercises and conversational AI tutors.
• Coursera: Implements LLMs to create automated course summaries, quiz generation, and learner feedback.
• Khan Academy: Uses AI tutors powered by LLMs to provide customized explanations and hints to students.
• Udemy: Leverages LLMs for course content generation and automated instructor assistance.
• Quizlet: Applies LLMs to generate flashcards, practice tests, and study guides automatically.
• EdX: Uses LLMs to help create adaptive learning paths and interactive educational content.
• LinkedIn Learning: Employs LLMs to recommend personalized learning plans and generate course transcripts.
• BYJU’S: Integrates LLMs in chatbots for student queries and personalized tutoring.
• Brainly: Uses LLMs to provide instant, AI-powered homework help and explanations.
• Socratic (by Google): Applies LLMs to analyze student questions and deliver step-by-step solutions in various subjects.

✅ Summary of LLMS use cases

LLMs are the foundation of generative AI and other AI content generation. Many LLMs are publicly available to use in your own projects and platforms. In this article, we learned about some use cases and how popular companies are using LLMs in their businesses.

🚀 Are you looking to integrate Large Language Models (LLMs) into your business? Hire C# Corner Consulting for expert AI solutions that drive innovation and growth!