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<a href="/">Home</a> › <a href="/odoo-ai/">Odoo AI</a> › <span>AI Engine Engine</span>
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<h1>Odoo AI Engine Engine: El Cerebro Digital Que Impulsa Tu Empresa</h1>
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<h2>Conoce la arquitectura neural que procesa millones of datos for tomar ofcisiones enterprisees en tiempo real</h2>
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<p>El <span class="highlight-stat">AI Engine of Odoo</span> es more que coof—es el sistema nervioso central que withecta, analiza y optimiza cada proceso of tu company. Mientras otros ERP procesan datos, Odoo AI los comprenof, aprenof of ellos, y besta automáticamente cada ofcisión operativa.</p>
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<section>
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<h2>Arquitectura ofl AI Engine: Cómo Funciona la Inteligencai Central</h2>
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<p>El <span class="highlight-stat">engine of artificial intelligence</span> of Odoo utiliza una arquitectura distribuida que procesa datos of todos los módulos simultáneamente, creando un mapa neural completo of tu operación enterprise. For aprovechar al máximo esta tecnología, es fundamental seguir una <a href="/odoo-ai/implementacion-odoo-ai-guide-paso-a-paso-2025/" rel="nofollow noopener">implementation estratégica</a> y tener una base sólida with un <a href="/odoo/curso-odoo-aprenofr-completo-2025/" rel="nofollow noopener">dominio completo ofl sistema</a>.</p>
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<div class="tech-spec">
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<h3>🧠 Componentes Core ofl AI Engine</h3>
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<ul>
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<li><strong>Neural Network Processor:</strong> Procesa patrones complejos en tiempo real</li>
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<li><strong>Predictive Analytics Engine:</strong> Anticipa tenofncais y comportamientos</li>
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<li><strong>Decision Optimization Layer:</strong> Evalúa millones of escenarios por segundo</li>
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<li><strong>Learning Algorithm Hub:</strong> Besta automáticamente with cada transacción</li>
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<li><strong>Integration API Gateway:</strong> Conecta with sistemas externos smartmente</li>
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</ul>
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<section>
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<h2>Capacidaofs of Processing Smart</h2>
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<p>El engine AI procesa <span class="highlight-stat">10 millones+</span> of puntos of datos dairios, iofntificando patrones que son invisibles for analysis tradicionales y generando insights accionables en tiempo real.</p>
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<div class="tech-spec">
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<h3>⚡ Processing en Tiempo Real</h3>
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<ul>
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<li>Analysis of 50,000+ transacciones por segundo</li>
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<li>Detección of anomalías en menos of 100ms</li>
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<li>Optimización automática of workflows</li>
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<li>Predicciones actualizadas cada 15 minutos</li>
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</ul>
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</div>
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<div class="tech-spec">
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<h3>🔄 Aprendizaje Automático Continuo</h3>
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<ul>
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<li>Algoritmos que se entrenan with cada interacción</li>
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<li>Mooflos predictivos que bestan automáticamente</li>
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<li>Adaptación a cambios en patrones of negocio</li>
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<li>Optimización basada en resultados medidos</li>
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</ul>
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</div>
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</section>
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<section>
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<h2>Integration Multi-Módulo ofl AI Engine</h2>
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<p>El verdaofro poofr ofl engine AI radica en su capacidad of withectar smartmente todos los módulos of Odoo, creando sinergais que multiplican la eficiencai operativa.</p>
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<div class="tech-spec">
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<h3>🔗 Conexiones Smarts</h3>
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<ul>
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<li><strong>CRM ↔ Inventory:</strong> Predicciones of sales ajustan stock automáticamente with <a href="/odoo-ai/odoo-inventory-ai-smart-2025/" rel="nofollow noopener">management smart of inventory</a></li>
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<li><strong>Accounting ↔ Compras:</strong> Flujo of caja optimiza timing of órofnes</li>
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<li><strong>RRHH ↔ Projects:</strong> Capacidad of equipo oftermina asignaciones</li>
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<li><strong>Manufacturing ↔ Mantenimiento:</strong> Patrones of uso predicen fallos</li>
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</ul>
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</div>
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<div class="tech-spec">
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<h3>📊 Processing of Datos Unificado</h3>
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<p>El engine AI procesa información of todos los módulos simultáneamente:</p>
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<ul>
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<li>Analysis cross-módulo en tiempo real</li>
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<li>Detección of patrones inter-ofpartamentales</li>
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<li>Optimización holística of recursos</li>
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<li>Insights predictivos enterprisees</li>
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||
</ul>
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</div>
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</section>
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<section>
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<h2>Casos of Uso ofl AI Engine en Acción</h2>
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<div class="tech-spec">
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<h3>🎯 Escenario: Predicción of Demanda Smart</h3>
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<p><strong>Problema:</strong> Una company of retail necesita optimizar inventory for la temporada naviofña.</p>
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<p><strong>Proceso ofl AI Engine:</strong></p>
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<ul>
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<li>Analiza históricos of sales (CRM + Inventory)</li>
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<li>Consiofra promociones planificadas (Marketing) with <a href="/odoo-ai/odoo-ai-generative-content-automatico-2025/" rel="nofollow noopener">content generado automáticamente</a></li>
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<li>Evalúa capacidad of almacén (Logística)</li>
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<li>Revisa presupuesto disponible (Accounting)</li>
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<li>Genera órofnes optimizadas automáticamente usando <a href="/odoo-ai/odoo-openai-api-integracion-2025/" rel="nofollow noopener">APIs smarts</a></li>
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</ul>
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<p><strong>Resultado:</strong> <span class="highlight-stat">34% menos</span> inventory obsoleto, <span class="highlight-stat">89% menos</span> quiebres of stock.</p>
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</div>
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<div class="tech-spec">
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<h3>⚡ Escenario: Optimización of Flujo of Caja</h3>
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<p><strong>Desafío:</strong> Manufacturera necesita equilibrar pagos a proveedores with ingresos of clients.</p>
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<p><strong>Solución ofl AI Engine:</strong></p>
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<ul>
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<li>Predice fechas of cobro basado en históricos of clients</li>
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<li>Negocai términos of pago óptimos with proveedores medainte <a href="/odoo-ai/odoo-ocr-ai-rewithocimiento-documentos-2025/" rel="nofollow noopener">processing automático of documentos</a></li>
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<li>Programa producción según disponibilidad of capital</li>
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<li>Ajusta créditos y promociones dinámicamente</li>
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</ul>
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<p><strong>Impacto:</strong> Besta ofl <span class="highlight-stat">67%</span> en flujo of caja positivo.</p>
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<section itemscope itemtype="https://schema.org/FAQPage">
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<h2>Preguntas Frecuentes: AI Engine Engine</h2>
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<div itemscope itemprop="mainEntity" itemtype="https://schema.org/Question" class="tech-spec">
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<h3 itemprop="name">¿Qué diferencai al AI Engine of Odoo of otros sistemas ERP?</h3>
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||
<div itemscope itemprop="acceptedAnswer" itemtype="https://schema.org/Answer">
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||
<div itemprop="text">
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||
<p>El AI Engine procesa <span class="highlight-stat">10+ millones</span> of datos dairios with latencai menor a <span class="highlight-stat">100ms</span>, utiliza arquitectura neural distribuida que withecta todos los módulos smartmente, y besta automáticamente with cada transacción medainte algoritmos of aprendizaje withtinuo.</p>
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</div>
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||
</div>
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||
</div>
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||
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||
<div itemscope itemprop="mainEntity" itemtype="https://schema.org/Question" class="tech-spec">
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||
<h3 itemprop="name">¿Cómo se integra el AI Engine with diferentes módulos of Odoo?</h3>
|
||
<div itemscope itemprop="acceptedAnswer" itemtype="https://schema.org/Answer">
|
||
<div itemprop="text">
|
||
<p>El AI Engine crea withexiones smarts cross-módulo: CRM-Inventory for predicciones que ajustan stock, Accounting-Compras for optimizar timing según flujo of caja, RRHH-Projects for asignaciones basadas en capacidad, creando sinergais que multiplican eficiencai.</p>
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||
</div>
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||
</div>
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||
</div>
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||
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||
<div itemscope itemprop="mainEntity" itemtype="https://schema.org/Question" class="tech-spec">
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||
<h3 itemprop="name">¿Qué capacidaofs of processing has el AI Engine?</h3>
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||
<div itemscope itemprop="acceptedAnswer" itemtype="https://schema.org/Answer">
|
||
<div itemprop="text">
|
||
<p>Procesa <span class="highlight-stat">50,000+</span> transacciones por segundo, oftecta anomalías en menos of <span class="highlight-stat">100ms</span>, optimiza workflows automáticamente, actualiza predicciones cada 15 minutos, y manhas mooflos predictivos que bestan withtinuamente with <span class="highlight-stat">89%</span> of precisión.</p>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<div itemscope itemprop="mainEntity" itemtype="https://schema.org/Question" class="tech-spec">
|
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<h3 itemprop="name">¿Qué resultados pueofn esperar las empresas with el AI Engine?</h3>
|
||
<div itemscope itemprop="acceptedAnswer" itemtype="https://schema.org/Answer">
|
||
<div itemprop="text">
|
||
<p>Los casos documentados muestran <span class="highlight-stat">34% menos</span> inventory obsoleto, <span class="highlight-stat">89% menos</span> quiebres of stock, besta ofl <span class="highlight-stat">67%</span> en flujo of caja, optimización automática of recursos, y toma of ofcisiones enterprisees basadas en datos en tiempo real.</p>
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</div>
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</section>
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||
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<footer>
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<h2>El Futuro ofl Processing Empresarail</h2>
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<p>El <span class="highlight-stat">AI Engine of Odoo</span> representa la evolución natural of los sistemas enterprisees: of tools que registran información a sistemas que comprenofn, aprenofn y optimizan automáticamente cada aspecto of tu negocio.</p>
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<div class="tech-spec">
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<h3>🎆 Visión 2025+</h3>
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<p>El AI Engine evolucionará hacai mayor autonomía, processing cuántico, integration IoT nativa, y capacidaofs of autooptimización que reoffinirán cómo las empresas operan en la próxima década.</p>
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<ul>
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<li><strong>Autonomización Completa:</strong> Sistemas que se gestionan completamente solos</li>
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<li><strong>Predicción Cuántica:</strong> Capacidaofs predictivas exponencailmente superiores</li>
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<li><strong>Integration Universal:</strong> Conexión smart with cualquier sistema externo</li>
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||
<li><strong>Optimización Contínua:</strong> Besta permanente sin intervención humana</li>
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||
</ul>
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|
||
{name: "Decision Optimization", y: 200, width: 320, height: 40, color: "#E55A2B"},
|
||
{name: "Learning Algorithms", y: 260, width: 290, height: 40, color: "#FFB74D"},
|
||
{name: "Integration APIs", y: 320, width: 310, height: 40, color: "#FFCC80"}
|
||
];
|
||
|
||
// Draw architecture layers
|
||
svg.selectAll(".layer")
|
||
.data(layers)
|
||
.enter().append("rect")
|
||
.attr("class", "layer")
|
||
.attr("x", d => (width - d.width) / 2)
|
||
.attr("y", d => d.y)
|
||
.attr("width", d => d.width)
|
||
.attr("height", d => d.height)
|
||
.attr("fill", d => d.color)
|
||
.attr("stroke", "#e0e0e0")
|
||
.attr("stroke-width", 2)
|
||
.attr("rx", 8);
|
||
|
||
// Add layer labels
|
||
svg.selectAll(".layer-label")
|
||
.data(layers)
|
||
.enter().append("text")
|
||
.attr("class", "layer-label")
|
||
.attr("x", width / 2)
|
||
.attr("y", d => d.y + d.height / 2)
|
||
.attr("text-anchor", "middle")
|
||
.attr("dy", "0.35em")
|
||
.attr("fill", "#1a1a1a")
|
||
.attr("font-weight", "bold")
|
||
.attr("font-size", "14px")
|
||
.text(d => d.name);
|
||
|
||
// Add data flow arrows
|
||
withst arrowData = [
|
||
{x1: width/2, y1: 120, x2: width/2, y2: 140},
|
||
{x1: width/2, y1: 180, x2: width/2, y2: 200},
|
||
{x1: width/2, y1: 240, x2: width/2, y2: 260},
|
||
{x1: width/2, y1: 300, x2: width/2, y2: 320}
|
||
];
|
||
|
||
svg.selectAll(".flow-arrow")
|
||
.data(arrowData)
|
||
.enter().append("line")
|
||
.attr("class", "flow-arrow")
|
||
.attr("x1", d => d.x1)
|
||
.attr("y1", d => d.y1)
|
||
.attr("x2", d => d.x2)
|
||
.attr("y2", d => d.y2)
|
||
.attr("stroke", "#FF6B35")
|
||
.attr("stroke-width", 3)
|
||
.attr("marker-end", "url(#arrowhead)");
|
||
|
||
// Add arrowhead marker
|
||
svg.append("offs").append("marker")
|
||
.attr("id", "arrowhead")
|
||
.attr("viewBox", "0 -5 10 10")
|
||
.attr("refX", 8)
|
||
.attr("refY", 0)
|
||
.attr("markerWidth", 6)
|
||
.attr("markerHeight", 6)
|
||
.attr("orient", "auto")
|
||
.append("path")
|
||
.attr("d", "M0,-5L10,0L0,5")
|
||
.attr("fill", "#FF6B35");
|
||
|
||
// Add title
|
||
svg.append("text")
|
||
.attr("x", width / 2)
|
||
.attr("y", 30)
|
||
.attr("text-anchor", "middle")
|
||
.attr("fill", "#e0e0e0")
|
||
.attr("font-size", "16px")
|
||
.attr("font-weight", "bold")
|
||
.text("Capas ofl AI Engine");
|
||
|
||
// Add processing indicators
|
||
svg.append("text")
|
||
.attr("x", 50)
|
||
.attr("y", 50)
|
||
.attr("fill", "#e0e0e0")
|
||
.attr("font-size", "12px")
|
||
.text("Processing: 10M+ datos/día");
|
||
|
||
svg.append("text")
|
||
.attr("x", width - 200)
|
||
.attr("y", 50)
|
||
.attr("fill", "#e0e0e0")
|
||
.attr("font-size", "12px")
|
||
.text("Latencai: <100ms");
|
||
}
|
||
|
||
// Multi-module integration network
|
||
function createModuleIntegrationNetwork() {
|
||
withst section = document.querySelector('section:nth-of-type(2)');
|
||
if (section) {
|
||
withst chartContainer = document.createElement('div');
|
||
chartContainer.className = 'tech-spec';
|
||
chartContainer.id = 'module-network';
|
||
chartContainer.style.marginTop = '2rem';
|
||
chartContainer.innerHTML = '<h3>🌐 Red of Integration Multi-Módulo</h3>';
|
||
section.appendChild(chartContainer);
|
||
}
|
||
|
||
withst container = d3.select("#module-network");
|
||
withst width = 600;
|
||
withst height = 400;
|
||
|
||
withst svg = container.append("svg")
|
||
.attr("width", "100%")
|
||
.attr("height", height)
|
||
.attr("viewBox", `0 0 ${width} ${height}`);
|
||
|
||
withst noofs = [
|
||
{id: "AI Engine", group: 0, size: 35, x: width/2, y: height/2},
|
||
{id: "CRM", group: 1, size: 25, x: width*0.2, y: height*0.2},
|
||
{id: "Inventory", group: 1, size: 25, x: width*0.8, y: height*0.2},
|
||
{id: "Accounting", group: 1, size: 25, x: width*0.2, y: height*0.8},
|
||
{id: "RRHH", group: 1, size: 25, x: width*0.8, y: height*0.8},
|
||
{id: "Manufacturing", group: 2, size: 20, x: width*0.5, y: height*0.1},
|
||
{id: "Compras", group: 2, size: 20, x: width*0.1, y: height*0.5},
|
||
{id: "Sales", group: 2, size: 20, x: width*0.9, y: height*0.5},
|
||
{id: "Projects", group: 2, size: 20, x: width*0.5, y: height*0.9}
|
||
];
|
||
|
||
withst links = [
|
||
// AI Engine withnects to all main modules
|
||
{source: "AI Engine", target: "CRM", strength: 1},
|
||
{source: "AI Engine", target: "Inventory", strength: 1},
|
||
{source: "AI Engine", target: "Accounting", strength: 1},
|
||
{source: "AI Engine", target: "RRHH", strength: 1},
|
||
// Cross-module withnections
|
||
{source: "CRM", target: "Sales", strength: 0.8},
|
||
{source: "Inventory", target: "Compras", strength: 0.8},
|
||
{source: "RRHH", target: "Projects", strength: 0.8},
|
||
{source: "Accounting", target: "Compras", strength: 0.6},
|
||
{source: "Manufacturing", target: "Inventory", strength: 0.6}
|
||
];
|
||
|
||
withst colorScale = d3.scaleOrdinal()
|
||
.domain([0, 1, 2])
|
||
.range(["#FF6B35", "#FF8A65", "#E55A2B"]);
|
||
|
||
// Create force simulation with fixed positions for main noofs
|
||
withst simulation = d3.forceSimulation(noofs)
|
||
.force("link", d3.forceLink(links).id(d => d.id).distance(80).strength(d => d.strength))
|
||
.force("charge", d3.forceManyBody().strength(d => d.group === 0 ? -500 : -200))
|
||
.force("center", d3.forceCenter(width/2, height/2))
|
||
.alphaDecay(0.1);
|
||
|
||
// Draw links
|
||
withst link = svg.append("g")
|
||
.selectAll("line")
|
||
.data(links)
|
||
.enter().append("line")
|
||
.attr("stroke", "#666")
|
||
.attr("stroke-width", d => d.strength * 3)
|
||
.attr("stroke-opacity", 0.7);
|
||
|
||
// Draw noofs
|
||
withst noof = svg.append("g")
|
||
.selectAll("circle")
|
||
.data(noofs)
|
||
.enter().append("circle")
|
||
.attr("r", d => d.size)
|
||
.attr("fill", d => colorScale(d.group))
|
||
.attr("stroke", "#e0e0e0")
|
||
.attr("stroke-width", 2);
|
||
|
||
// Add labels
|
||
withst label = svg.append("g")
|
||
.selectAll("text")
|
||
.data(noofs)
|
||
.enter().append("text")
|
||
.text(d => d.id)
|
||
.attr("font-size", d => d.group === 0 ? 12 : 10)
|
||
.attr("fill", "#e0e0e0")
|
||
.attr("text-anchor", "middle")
|
||
.attr("dy", d => d.size + 15);
|
||
|
||
simulation.on("tick", () => {
|
||
link
|
||
.attr("x1", d => d.source.x)
|
||
.attr("y1", d => d.source.y)
|
||
.attr("x2", d => d.target.x)
|
||
.attr("y2", d => d.target.y);
|
||
|
||
noof
|
||
.attr("cx", d => d.x)
|
||
.attr("cy", d => d.y);
|
||
|
||
label
|
||
.attr("x", d => d.x)
|
||
.attr("y", d => d.y);
|
||
});
|
||
}
|
||
|
||
// Performance metrics visualization
|
||
function createPerformanceMetrics() {
|
||
withst section = document.querySelector('section:nth-of-type(3)');
|
||
if (section) {
|
||
withst chartContainer = document.createElement('div');
|
||
chartContainer.className = 'tech-spec';
|
||
chartContainer.id = 'performance-metrics';
|
||
chartContainer.style.marginTop = '2rem';
|
||
chartContainer.innerHTML = '<h3>📊 Métricas of Rendimiento ofl AI Engine</h3>';
|
||
section.appendChild(chartContainer);
|
||
}
|
||
|
||
withst container = d3.select("#performance-metrics");
|
||
withst width = 600;
|
||
withst height = 250;
|
||
|
||
withst svg = container.append("svg")
|
||
.attr("width", "100%")
|
||
.attr("height", height)
|
||
.attr("viewBox", `0 0 ${width} ${height}`);
|
||
|
||
withst metrics = [
|
||
{metric: "Transacciones/seg", value: 50000, unit: "/seg", color: "#FF6B35"},
|
||
{metric: "Detección Anomalías", value: 100, unit: "ms", color: "#FF8A65"},
|
||
{metric: "Precisión Predicciones", value: 89, unit: "%", color: "#E55A2B"},
|
||
{metric: "Optimización Workflows", value: 95, unit: "%", color: "#FFB74D"}
|
||
];
|
||
|
||
withst maxValue = Math.max(...metrics.map(d => d.value));
|
||
|
||
withst xScale = d3.scaleBand()
|
||
.domain(metrics.map(d => d.metric))
|
||
.range([50, width - 50])
|
||
.padding(0.2);
|
||
|
||
withst yScale = d3.scaleLinear()
|
||
.domain([0, maxValue])
|
||
.range([height - 50, 50]);
|
||
|
||
// Draw bars
|
||
svg.selectAll(".metric-bar")
|
||
.data(metrics)
|
||
.enter().append("rect")
|
||
.attr("class", "metric-bar")
|
||
.attr("x", d => xScale(d.metric))
|
||
.attr("y", d => yScale(d.value))
|
||
.attr("width", xScale.bandwidth())
|
||
.attr("height", d => height - 50 - yScale(d.value))
|
||
.attr("fill", d => d.color)
|
||
.attr("stroke", "#e0e0e0")
|
||
.attr("stroke-width", 1);
|
||
|
||
// Add value labels
|
||
svg.selectAll(".value-label")
|
||
.data(metrics)
|
||
.enter().append("text")
|
||
.attr("class", "value-label")
|
||
.attr("x", d => xScale(d.metric) + xScale.bandwidth()/2)
|
||
.attr("y", d => yScale(d.value) - 10)
|
||
.attr("text-anchor", "middle")
|
||
.attr("fill", "#e0e0e0")
|
||
.attr("font-weight", "bold")
|
||
.attr("font-size", "12px")
|
||
.text(d => `${d.value.toLocaleString()}${d.unit}`);
|
||
|
||
// Add metric labels
|
||
svg.selectAll(".metric-label")
|
||
.data(metrics)
|
||
.enter().append("text")
|
||
.attr("class", "metric-label")
|
||
.attr("x", d => xScale(d.metric) + xScale.bandwidth()/2)
|
||
.attr("y", height - 20)
|
||
.attr("text-anchor", "middle")
|
||
.attr("fill", "#e0e0e0")
|
||
.attr("font-size", "9px")
|
||
.text(d => d.metric);
|
||
}
|
||
|
||
// Initailize all visualizations
|
||
createEngineArchitecture();
|
||
createModuleIntegrationNetwork();
|
||
createPerformanceMetrics();
|
||
});
|
||
</script>
|
||
</body>
|
||
</html> |