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1205, Pehel, Vaishnodevi Circle, Ahmedabad, GJ, India

+91-97244-97492

jaydeep@aigentora.ai

LLM Development Services

LLM Development Services

Build intelligent tools and internal systems using fine-tuned Large Language Models like GPT-4, Claude, or Gemini or using them as models.

Today’s enterprises are evolving beyond basic automation—LLMs are enabling smarter, context-aware tools that can reason, generate content, summarize documents, and even make data-driven decisions. At Aigentora, we help you unlock that potential by building secure, custom LLM-powered applications tailored to your unique workflows.

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💡 What We Build

  • Knowledge Assistants: Internal Q&A tools trained on your documentation, SOPs, and policies.

  • Smart Content Tools: Copywriters, email generators, report writers customized to your tone and brand.

  • Form & Workflow Agents: Agents that read inputs, fill forms, extract structured data from unstructured sources.

  • LLM + RAG Systems: Combine your private data with public knowledge for contextual, reliable answers.

  • Fine-Tuned Models: Domain-specific LLMs built with your proprietary data, reducing hallucination and boosting accuracy.

💼 Industry-Specific LLM Use Cases

Tailored LLM solutions for every industry. Unlock smarter workflows with domain-specific intelligence that fits your business.

🛍️ E-commerce & Retail

  • Product Description Generator: Auto-generate SEO-optimized content at scale for thousands of SKUs.

  • Customer Support Assistant: Help agents respond faster with LLM-suggested replies, even for complex queries.

🏥 Healthcare

  • Medical Knowledgebase Search: Retrieve clinical information from patient notes, manuals, or EMRs.

  • Patient Intake Summary Tool: Convert unstructured patient histories into structured case summaries.

💰 Financial Services

  • Policy & Compliance Explainer: Help teams query financial policies in natural language.

  • Contract Analyzer: Extract and highlight critical clauses from complex agreements.

🏭 Manufacturing & Logistics

  • SOP Interpreter: Enable frontline teams to query technical instructions or safety procedures instantly.

  • Supplier Chat Assistant: Convert RFQs, specs, and vendor communication into standardized formats.

🏠 Real Estate

  • LLM-Powered Investment Summary: Convert listing data and market trends into ready-to-share investor briefs.

  • Property Comparison Bot: Let buyers compare listings by typing in their specific preferences.

🏫 Education & Training

  • Custom Tutor Bots: Generate lesson plans, quiz questions, or summaries based on learning objectives.

  • Student Helpdesk: 24/7 virtual assistant trained on school policies, forms, and academic queries.

📘 Case Studies

See how custom LLM solutions drive real business impact. From retail to real estate, our tools deliver measurable results.

🛒 Fashion Retailer (US)

We helped a Shopify-based brand deploy a GPT-4 tool that auto-generates multilingual product descriptions. Result? 40% faster time-to-market and improved SEO rankings in under 3 months.

🏥 HealthTech Startup (India)

Built a secure knowledge assistant using RAG + fine-tuned Claude model. Internal team queries dropped by 70%, and compliance responses became 2x faster.

🏗️ Manufacturing Company (Germany)

Integrated Gemini Pro into their ERP to assist in interpreting long SOPs. Shop floor queries that once took 15 mins are now answered in under 30 seconds.

🏠 Real Estate Group (UAE)

Developed a listing assistant that summarizes key selling points, market comps, and investment potential. Helped agents close 20% more leads with faster client follow-ups.

FAQEverything you need to know about

Generic tools can’t access your internal data or match your workflows. Custom LLM tools are private, fine-tuned, and integrated into your business systems.

No. We handle everything—from model selection to deployment and iteration. We also provide admin dashboards for non-technical teams.

Yes. We specialize in secure LLM integrations using RAG (Retrieval Augmented Generation) and vector databases to make models context-aware.

 

A functional MVP takes 2–4 weeks, while enterprise-scale deployments with feedback loops may take 6–8 weeks.

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