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<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>AWS Generative AI Success Stories</title>
    <script src="https://cdn.tailwindcss.com"></script>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css">
    <script>
        tailwind.config = {
            theme: {
                extend: {
                    colors: {
                        awsOrange: '#FF9900',
                        awsDark: '#232F3E',
                        awsLight: '#F2F3F7',
                        deepseekBlue: '#3B82F6',
                    },
                    fontFamily: {
                        sans: ['Amazon Ember', 'Helvetica Neue', 'Arial', 'sans-serif'],
                    },
                }
            }
        }
    </script>
    <style>
        @import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&display=swap');
        
        body {
            font-family: 'Inter', sans-serif;
        }
        
        .gradient-bg {
            background: linear-gradient(135deg, #232F3E 0%, #1A2533 100%);
        }
        
        .card-hover {
            transition: all 0.3s ease;
        }
        
        .card-hover:hover {
            transform: translateY(-5px);
            box-shadow: 0 20px 25px -5px rgba(0, 0, 0, 0.1), 0 10px 10px -5px rgba(0, 0, 0, 0.04);
        }
        
        .aws-pattern {
            background-image: radial-gradient(circle at 1px 1px, rgba(255, 255, 255, 0.1) 1px, transparent 0);
            background-size: 20px 20px;
        }
        
        .animated-underline {
            position: relative;
            display: inline-block;
        }
        
        .animated-underline::after {
            content: '';
            position: absolute;
            width: 0;
            height: 2px;
            bottom: -2px;
            left: 0;
            background-color: #FF9900;
            transition: width 0.3s ease;
        }
        
        .animated-underline:hover::after {
            width: 100%;
        }
        
        .fade-in {
            animation: fadeIn 0.5s ease-in;
        }
        
        @keyframes fadeIn {
            from { opacity: 0; }
            to { opacity: 1; }
        }
        
        /* AI Assistant Styles */
        .assistant-container {
            position: fixed;
            bottom: 30px;
            right: 30px;
            z-index: 1000;
        }
        
        .assistant-button {
            width: 60px;
            height: 60px;
            border-radius: 50%;
            background: linear-gradient(135deg, #3B82F6 0%, #1D4ED8 100%);
            color: white;
            display: flex;
            align-items: center;
            justify-content: center;
            cursor: pointer;
            box-shadow: 0 10px 15px -3px rgba(0, 0, 0, 0.1), 0 4px 6px -2px rgba(0, 0, 0, 0.05);
            transition: all 0.3s ease;
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        .assistant-button:hover {
            transform: scale(1.1);
        }
        
        .assistant-chat {
            position: absolute;
            bottom: 80px;
            right: 0;
            width: 350px;
            max-height: 500px;
            background: white;
            border-radius: 12px;
            box-shadow: 0 20px 25px -5px rgba(0, 0, 0, 0.1), 0 10px 10px -5px rgba(0, 0, 0, 0.04);
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            flex-direction: column;
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        .chat-header {
            background: linear-gradient(135deg, #3B82F6 0%, #1D4ED8 100%);
            color: white;
            padding: 12px 16px;
            display: flex;
            justify-content: space-between;
            align-items: center;
        }
        
        .chat-messages {
            flex: 1;
            padding: 16px;
            overflow-y: auto;
            background-color: #f9fafb;
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        .message {
            margin-bottom: 12px;
            max-width: 80%;
            padding: 8px 12px;
            border-radius: 12px;
            font-size: 14px;
            line-height: 1.4;
        }
        
        .user-message {
            background-color: #3B82F6;
            color: white;
            margin-left: auto;
            border-bottom-right-radius: 4px;
        }
        
        .assistant-message {
            background-color: #e5e7eb;
            color: #111827;
            margin-right: auto;
            border-bottom-left-radius: 4px;
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        .chat-input {
            display: flex;
            padding: 12px;
            border-top: 1px solid #e5e7eb;
            background-color: white;
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        .chat-input input {
            flex: 1;
            padding: 8px 12px;
            border: 1px solid #e5e7eb;
            border-radius: 20px;
            outline: none;
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        .chat-input button {
            background-color: #3B82F6;
            color: white;
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            width: 36px;
            height: 36px;
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            display: flex;
            align-items: center;
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            cursor: pointer;
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        .typing-indicator {
            display: flex;
            padding: 8px 12px;
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        .typing-dot {
            width: 8px;
            height: 8px;
            background-color: #9ca3af;
            border-radius: 50%;
            margin: 0 2px;
            animation: typing 1.4s infinite ease-in-out;
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        .typing-dot:nth-child(1) {
            animation-delay: 0s;
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        .typing-dot:nth-child(2) {
            animation-delay: 0.2s;
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        .typing-dot:nth-child(3) {
            animation-delay: 0.4s;
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        @keyframes typing {
            0%, 60%, 100% {
                transform: translateY(0);
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            30% {
                transform: translateY(-5px);
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    </style>
</head>
<body class="bg-awsLight">
    <!-- Navigation -->
    <nav class="gradient-bg text-white shadow-lg">
        <div class="container mx-auto px-6 py-4">
            <div class="flex justify-between items-center">
                <div class="flex items-center space-x-4">
                    <img src="https://d1.awsstatic.com/logos/aws-logo-lockups/poweredbyaws/PB_AWS_logo_RGB_stacked_REV_SQ.91cd4af40773cbfbd15577a3c2b8a346fe3e8fa2.png" alt="AWS Logo" class="h-12">
                    <span class="text-xl font-bold">Generative AI Success Stories</span>
                </div>
                <div class="hidden md:flex items-center space-x-8">
                    <a href="#stories" class="animated-underline">Case Studies</a>
                    <a href="#solutions" class="animated-underline">Solutions</a>
                    <a href="#testimonials" class="animated-underline">Testimonials</a>
                    <a href="#contact" class="animated-underline">Contact</a>
                </div>
                <button class="md:hidden focus:outline-none">
                    <i class="fas fa-bars text-2xl"></i>
                </button>
            </div>
        </div>
    </nav>

    <!-- Hero Section -->
    <header class="gradient-bg text-white aws-pattern">
        <div class="container mx-auto px-6 py-20">
            <div class="max-w-4xl mx-auto text-center">
                <h1 class="text-4xl md:text-6xl font-bold mb-6">Transform Your Business with AWS Generative AI</h1>
                <p class="text-xl md:text-2xl mb-8">Discover how industry leaders are leveraging AWS's cutting-edge generative AI services to drive innovation, efficiency, and growth.</p>
                <div class="flex flex-col sm:flex-row justify-center gap-4">
                    <a href="#stories" class="bg-awsOrange hover:bg-yellow-600 text-white font-bold py-3 px-8 rounded-lg transition duration-300 transform hover:scale-105">
                        Explore Success Stories
                    </a>
                    <a href="#contact" class="bg-transparent hover:bg-white hover:text-awsDark border-2 border-white text-white font-bold py-3 px-8 rounded-lg transition duration-300 transform hover:scale-105">
                        Get Started
                    </a>
                </div>
            </div>
        </div>
    </header>

    <!-- Stats Section -->
    <section class="bg-white py-16">
        <div class="container mx-auto px-6">
            <div class="grid grid-cols-1 md:grid-cols-4 gap-8 text-center">
                <div class="p-6 rounded-lg shadow-md">
                    <div class="text-4xl font-bold text-awsOrange mb-2">87%</div>
                    <div class="text-gray-600">of enterprises report improved efficiency</div>
                </div>
                <div class="p-6 rounded-lg shadow-md">
                    <div class="text-4xl font-bold text-awsOrange mb-2">3.5x</div>
                    <div class="text-gray-600">faster time-to-market for AI solutions</div>
                </div>
                <div class="p-6 rounded-lg shadow-md">
                    <div class="text-4xl font-bold text-awsOrange mb-2">$12B</div>
                    <div class="text-gray-600">in estimated cost savings for customers</div>
                </div>
                <div class="p-6 rounded-lg shadow-md">
                    <div class="text-4xl font-bold text-awsOrange mb-2">94%</div>
                    <div class="text-gray-600">customer satisfaction with AWS AI services</div>
                </div>
            </div>
        </div>
    </section>

    <!-- Success Stories Section -->
    <section id="stories" class="py-16 bg-gray-50">
        <div class="container mx-auto px-6">
            <h2 class="text-3xl font-bold text-center mb-12 text-awsDark">Featured Success Stories</h2>
            
            <!-- Filter Controls -->
            <div class="flex flex-wrap justify-center mb-12 gap-4">
                <button onclick="filterStories('all')" class="px-4 py-2 bg-awsOrange text-white rounded-full font-medium">All Industries</button>
                <button onclick="filterStories('healthcare')" class="px-4 py-2 bg-white border border-gray-300 rounded-full font-medium hover:bg-gray-100">Healthcare</button>
                <button onclick="filterStories('finance')" class="px-4 py-2 bg-white border border-gray-300 rounded-full font-medium hover:bg-gray-100">Financial Services</button>
                <button onclick="filterStories('retail')" class="px-4 py-2 bg-white border border-gray-300 rounded-full font-medium hover:bg-gray-100">Retail</button>
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                <p class="italic mb-4">"Generative design algorithms on AWS helped us optimize manufacturing processes, reducing material waste by 18% and improving production speed by 25%. The cost savings alone paid for the implementation in 6 months."</p>
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                    <ul class="list-disc pl-5 mt-2">
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                id: 1,
                title: "HealthGenius: Accelerating Drug Discovery",
                industry: "healthcare",
                summary: "Reduced drug discovery time by 40% using generative molecular design",
                logo: "https://via.placeholder.com/150x80?text=HealthGenius",
                challenge: "Traditional drug discovery processes were time-consuming and expensive, often taking years to identify promising compounds.",
                solution: "Implemented AWS Bedrock with custom generative models to explore molecular combinations and predict effectiveness.",
                results: [
                    "40% reduction in discovery time",
                    "28% increase in viable candidates",
                    "$15M annual cost savings"
                ],
                services: ["Amazon Bedrock", "Amazon SageMaker", "AWS Batch"],
                keywords: ["drug discovery", "molecular design", "healthcare", "pharmaceutical", "biology"]
            },
            {
                id: 2,
                title: "Finova: AI-Powered Fraud Detection",
                industry: "finance",
                summary: "Reduced false positives by 65% while identifying 30% more fraud",
                logo: "https://via.placeholder.com/150x80?text=Finova",
                challenge: "Existing fraud detection systems generated too many false positives, creating operational inefficiencies.",
                solution: "Deployed generative adversarial networks (GANs) on AWS to create synthetic fraud patterns for training.",
                results: [
                    "65% reduction in false positives",
                    "30% increase in fraud detection",
                    "98.7% accuracy rate"
                ],
                services: ["Amazon SageMaker", "AWS Lambda", "Amazon Fraud Detector"],
                keywords: ["fraud detection", "financial services", "GANs", "banking", "security"]
            },
            {
                id: 3,
                title: "StyleHub: Virtual Stylist Assistant",
                industry: "retail",
                summary: "Increased conversion by 22% with AI-powered fashion recommendations",
                logo: "https://via.placeholder.com/150x80?text=StyleHub",
                challenge: "Online shoppers struggled to find coordinated outfits, leading to low conversion and high returns.",
                solution: "Built a generative AI stylist using Amazon Lex and computer vision to create personalized outfits.",
                results: [
                    "22% increase in conversion",
                    "15% reduction in returns",
                    "4.8/5 customer satisfaction"
                ],
                services: ["Amazon Lex", "Amazon Rekognition", "Amazon Personalize"],
                keywords: ["retail", "fashion", "recommendations", "e-commerce", "personalization"]
            },
            {
                id: 4,
                title: "AutoMech: Generative Design Optimization",
                industry: "manufacturing",
                summary: "Reduced material waste by 18% with AI-generated designs",
                logo: "https://via.placeholder.com/150x80?text=AutoMech",
                challenge: "Traditional mechanical design processes were inefficient and resulted in material waste.",
                solution: "Implemented generative design algorithms on AWS to optimize part geometries for strength and material use.",
                results: [
                    "18% material reduction",
                    "25% faster production",
                    "ROI in 6 months"
                ],
                services: ["Amazon SageMaker", "AWS Batch", "Amazon EC2 Spot Instances"],
                keywords: ["manufacturing", "generative design", "engineering", "3D modeling", "optimization"]
            },
            {
                id: 5,
                title: "StreamNation: Personalized Content Creation",
                industry: "media",
                summary: "Increased engagement by 35% with AI-generated content variations",
                logo: "https://via.placeholder.com/150x80?text=StreamNation",
                challenge: "Needed to create personalized content variations at scale for different audience segments.",
                solution: "Used AWS generative AI services to automatically create localized and personalized content versions.",
                results: [
                    "35% increase in engagement",
                    "50% faster content localization",
                    "3x more content variations"
                ],
                services: ["Amazon Bedrock", "Amazon Polly", "Amazon Transcribe"],
                keywords: ["media", "content creation", "personalization", "entertainment", "localization"]
            },
            {
                id: 6,
                title: "MediCare AI: Diagnostic Assistance",
                industry: "healthcare",
                summary: "Improved diagnostic accuracy by 27% with AI co-pilot",
                logo: "https://via.placeholder.com/150x80?text=MediCare+AI",
                challenge: "Doctors needed assistance interpreting complex medical imaging while maintaining accuracy.",
                solution: "Developed a generative AI assistant that suggests diagnoses based on imaging and patient history.",
                results: [
                    "27% improvement in diagnostic accuracy",
                    "40% faster preliminary reports",
                    "Reduced physician burnout"
                ],
                services: ["Amazon HealthLake", "Amazon SageMaker", "Amazon Textract"],
                keywords: ["healthcare", "diagnostics", "medical imaging", "radiology", "AI assistant"]
            }
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                "I can analyze the success stories in our database to find relevant examples for your needs.",
                "I can suggest potential use cases based on your industry and business challenges.",
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                "I can compare different approaches used across various industries."
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            services: {
                "Amazon Bedrock": "A fully managed service that makes foundation models (FMs) from Amazon and leading AI startups available through an API. Bedrock offers a choice of high-performing FMs that you can use standalone or customize with your data.",
                "Amazon SageMaker": "A fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process.",
                "Amazon Lex": "A service for building conversational interfaces into any application using voice and text. Lex provides advanced deep learning functionalities of automatic speech recognition (ASR) and natural language understanding (NLU)."
            },
            useCases: {
                healthcare: [
                    "Drug discovery and molecular design",
                    "Medical imaging analysis and diagnostics",
                    "Personalized treatment recommendations",
                    "Clinical trial matching and optimization",
                    "Medical documentation automation"
                ],
                finance: [
                    "Fraud detection and prevention",
                    "Personalized financial advice",
                    "Risk assessment modeling",
                    "Document processing and analysis",
                    "Algorithmic trading strategies"
                ],
                retail: [
                    "Personalized product recommendations",
                    "Virtual shopping assistants",
                    "Inventory optimization",
                    "Dynamic pricing models",
                    "Visual search and product discovery"
                ],
                manufacturing: [
                    "Generative design for parts optimization",
                    "Predictive maintenance",
                    "Supply chain optimization",
                    "Quality control automation",
                    "Process optimization"
                ],
                media: [
                    "Content personalization",
                    "Automated content generation",
                    "Voice synthesis and dubbing",
                    "Video summarization",
                    "Interactive storytelling"
                ]
            },
            newIdeas: [
                "Consider using generative AI for automated report generation in your business intelligence workflows.",
                "Generative design could optimize your physical product layouts or packaging solutions.",
                "AI-powered content moderation could help scale your user-generated content platforms.",
                "Personalized learning paths using generative AI could transform your training programs.",
                "Automated code generation could accelerate your software development lifecycle."
            ]
        };

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        function filterStories(industry) {
            renderStories(industry);
            
            // Update active button state
            document.querySelectorAll('#stories button').forEach(btn => {
                if (btn.textContent.toLowerCase().includes(industry) || 
                    (industry === 'all' && btn.textContent === 'All Industries')) {
                    btn.classList.remove('bg-white', 'border', 'border-gray-300');
                    btn.classList.add('bg-awsOrange', 'text-white');
                } else {
                    btn.classList.remove('bg-awsOrange', 'text-white');
                    btn.classList.add('bg-white', 'border', 'border-gray-300');
                }
            });
        }

        // Helper functions
        function capitalizeFirstLetter(string) {
            return string.charAt(0).toUpperCase() + string.slice(1);
        }

        function getIndustryColor(industry) {
            const colors = {
                healthcare: 'bg-blue-600',
                finance: 'bg-green-600',
                retail: 'bg-purple-600',
                manufacturing: 'bg-yellow-600',
                media: 'bg-red-600'
            };
            return colors[industry] || 'bg-gray-600';
        }

        // Modal functions
        function openModal(storyId) {
            const story = stories.find(s => s.id === storyId);
            if (!story) return;
            
            const modal = document.createElement('div');
            modal.className = 'fixed inset-0 bg-black bg-opacity-75 flex items-center justify-center p-4 z-50';
            modal.innerHTML = `
                <div class="bg-white rounded-xl max-w-4xl w-full max-h-[90vh] overflow-y-auto">
                    <div class="sticky top-0 bg-white p-4 border-b flex justify-between items-center">
                        <h3 class="text-2xl font-bold">${story.title}</h3>
                        <button onclick="closeModal()" class="text-gray-500 hover:text-gray-700">
                            <i class="fas fa-times text-2xl"></i>
                        </button>
                    </div>
                    <div class="p-8">
                        <div class="flex flex-wrap items-center mb-6">
                            <span class="inline-block px-3 py-1 text-sm font-semibold rounded-full ${getIndustryColor(story.industry)} text-white mr-4">
                                ${capitalizeFirstLetter(story.industry)}
                            </span>
                            <div class="flex items-center text-gray-500">
                                <i class="fas fa-building mr-2"></i>
                                <span>${story.title.split(':')[0]}</span>
                            </div>
                        </div>
                        
                        <div class="grid md:grid-cols-3 gap-8 mb-8">
                            <div class="md:col-span-2">
                                <h4 class="text-xl font-bold mb-4 text-awsDark">The Challenge</h4>
                                <p class="text-gray-700 mb-6">${story.challenge}</p>
                                
                                <h4 class="text-xl font-bold mb-4 text-awsDark">The Solution</h4>
                                <p class="text-gray-700 mb-6">${story.solution}</p>
                                
                                <h4 class="text-xl font-bold mb-4 text-awsDark">AWS Services Used</h4>
                                <div class="flex flex-wrap gap-2 mb-6">
                                    ${story.services.map(service => `
                                        <span class="px-3 py-1 bg-gray-100 rounded-full text-sm">${service}</span>
                                    `).join('')}
                                </div>
                            </div>
                            
                            <div class="bg-gray-50 p-6 rounded-lg">
                                <h4 class="text-xl font-bold mb-4 text-awsDark">Key Results</h4>
                                <ul class="space-y-3">
                                    ${story.results.map(result => `
                                        <li class="flex items-start">
                                            <i class="fas fa-check-circle text-green-500 mt-1 mr-3"></i>
                                            <span>${result}</span>
                                        </li>
                                    `).join('')}
                                </ul>
                                
                                <div class="mt-8">
                                    <h4 class="text-lg font-bold mb-3">Ready to get started?</h4>
                                    <a href="#contact" onclick="closeModal()" class="inline-block bg-awsOrange hover:bg-yellow-600 text-white font-bold py-2 px-6 rounded-lg transition">
                                        Contact Us
                                    </a>
                                </div>
                            </div>
                        </div>
                        
                        <div class="border-t pt-6">
                            <p class="text-gray-500 text-sm">Disclaimer: Results may vary based on specific use cases and implementations.</p>
                        </div>
                    </div>
                </div>
            `;
            
            document.body.appendChild(modal);
            document.body.style.overflow = 'hidden';
        }

        function closeModal() {
            const modal = document.querySelector('.fixed.inset-0');
            if (modal) {
                modal.remove();
                document.body.style.overflow = '';
            }
        }

        // AI Assistant Functions
        function toggleChat() {
            const chat = document.getElementById('assistant-chat');
            chat.style.display = chat.style.display === 'flex' ? 'none' : 'flex';
        }

        function handleKeyPress(e) {
            if (e.key === 'Enter') {
                sendMessage();
            }
        }

        function sendMessage() {
            const input = document.getElementById('user-input');
            const message = input.value.trim();
            
            if (message) {
                addMessage(message, 'user');
                input.value = '';
                
                // Show typing indicator
                const messagesContainer = document.getElementById('chat-messages');
                const typingIndicator = document.createElement('div');
                typingIndicator.className = 'typing-indicator';
                typingIndicator.innerHTML = `
                    <div class="typing-dot"></div>
                    <div class="typing-dot"></div>
                    <div class="typing-dot"></div>
                `;
                messagesContainer.appendChild(typingIndicator);
                messagesContainer.scrollTop = messagesContainer.scrollHeight;
                
                // Simulate thinking time
                setTimeout(() => {
                    // Remove typing indicator
                    messagesContainer.removeChild(typingIndicator);
                    
                    // Generate response
                    const response = generateResponse(message);
                    addMessage(response, 'assistant');
                }, 1000 + Math.random() * 2000);
            }
        }

        function addMessage(text, sender) {
            const messagesContainer = document.getElementById('chat-messages');
            const messageElement = document.createElement('div');
            messageElement.className = `message ${sender}-message`;
            messageElement.textContent = text;
            messagesContainer.appendChild(messageElement);
            messagesContainer.scrollTop = messagesContainer.scrollHeight;
        }

        function generateResponse(message) {
            const lowerMessage = message.toLowerCase();
            
            // Check for greetings
            if (lowerMessage.includes('hello') || lowerMessage.includes('hi') || lowerMessage.includes('hey')) {
                return assistantKnowledge.greetings[Math.floor(Math.random() * assistantKnowledge.greetings.length)];
            }
            
            // Check for capabilities question
            if (lowerMessage.includes('what can you do') || lowerMessage.includes('help') || lowerMessage.includes('capabilities')) {
                return assistantKnowledge.capabilities.join('\n');
            }
            
            // Check for specific service questions
            for (const service in assistantKnowledge.services) {
                if (lowerMessage.includes(service.toLowerCase()) || lowerMessage.includes(service.split(' ')[1].toLowerCase())) {
                    return `${service}: ${assistantKnowledge.services[service]}`;
                }
            }
            
            // Check for industry-specific questions
            for (const industry in assistantKnowledge.useCases) {
                if (lowerMessage.includes(industry)) {
                    return `Common ${industry} use cases for AWS Generative AI:\n- ${assistantKnowledge.useCases[industry].join('\n- ')}`;
                }
            }
            
            // Check for new ideas
            if (lowerMessage.includes('new') || lowerMessage.includes('idea') || lowerMessage.includes('suggest')) {
                return "Here are some innovative ways to use AWS Generative AI:\n- " + 
                    assistantKnowledge.newIdeas.join('\n- ');
            }
            
            // Try to find matching success stories
            const matchingStories = stories.filter(story => 
                story.keywords.some(keyword => lowerMessage.includes(keyword)) ||
                story.title.toLowerCase().includes(lowerMessage) ||
                story.industry.toLowerCase().includes(lowerMessage)
            );
            
            if (matchingStories.length > 0) {
                if (matchingStories.length === 1) {
                    const story = matchingStories[0];
                    return `For ${story.title}, ${story.summary}. The company used ${story.services.join(', ')} to ${story.solution.toLowerCase()}. Key results included ${story.results.join(', ')}. Would you like more details about this case?`;
                } else {
                    return `I found ${matchingStories.length} relevant success stories:\n` +
                        matchingStories.map(story => `- ${story.title} (${story.industry}): ${story.summary}`).join('\n') +
                        `\nWould you like details on any of these?`;
                }
            }
            
            // Default response if nothing matches
            return "I'm not sure I understand. Could you rephrase your question? I can help with:\n" +
                "- Specific success story details\n" +
                "- Use cases for your industry\n" +
                "- Technical implementation questions\n" +
                "- New application ideas";
        }

        // Initialize
        document.addEventListener('DOMContentLoaded', () => {
            renderStories();
            
            // Smooth scrolling for anchor links
            document.querySelectorAll('a[href^="#"]').forEach(anchor => {
                anchor.addEventListener('click', function (e) {
                    e.preventDefault();
                    
                    const targetId = this.getAttribute('href');
                    if (targetId === '#') return;
                    
                    const targetElement = document.querySelector(targetId);
                    if (targetElement) {
                        window.scrollTo({
                            top: targetElement.offsetTop - 80,
                            behavior: 'smooth'
                        });
                    }
                });
            });
            
            // Form submission
            const contactForm = document.getElementById('contact-form');
            if (contactForm) {
                contactForm.addEventListener('submit', function(e) {
                    e.preventDefault();
                    alert('Thank you for your interest! Our team will contact you shortly.');
                    this.reset();
                });
            }
        });
    </script>
<p style="border-radius: 8px; text-align: center; font-size: 12px; color: #fff; margin-top: 16px;position: fixed; left: 8px; bottom: 8px; z-index: 10; background: rgba(0, 0, 0, 0.8); padding: 4px 8px;">Made with <img src="https://enzostvs-deepsite.hf.space/logo.svg" alt="DeepSite Logo" style="width: 16px; height: 16px; vertical-align: middle;display:inline-block;margin-right:3px;filter:brightness(0) invert(1);"><a href="https://enzostvs-deepsite.hf.space" style="color: #fff;text-decoration: underline;" target="_blank" >DeepSite</a> - 🧬 <a href="https://enzostvs-deepsite.hf.space?remix=rvelasco/genai-use-cases-v2" style="color: #fff;text-decoration: underline;" target="_blank" >Remix</a></p></body>
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