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La hiperautomatización utiliza IA para automatizar tareas en las empresas

SOLUCIONES

HIPERAUTOMATIZACIÓN EN ABOX

QUÉ ES LA HIPERAUTOMATIZACIÓN

La hiperautomatización se encarga de automatizar tareas que normalmente realizan manos humanas. Aplica tecnologías como Modelado de procesos (BPA), Robotización (RPA) e Inteligencia Artificial (IA) para mejorar significativamente los flujos documentales.

Incluye la sofisticación de dicha automatización con etapas como descubrir, analizar, diseñar, automatizar, medir, monitorear y mejorar.

Captura asistida de documentos

Captura asistida de documentos

Detección de errores e inconsistencias

Detección de errores e inconsistencias

Medición emocional del texto de las comunicaciones

Medición emocional del texto de las comunicaciones

Automatización de acciones con BPM

Automatización de acciones con BPM

Clasificación automática con Machine Learning

Clasificación automática con Machine Learning

Servicio de integración a sistemas heredados

Servicio de integración a sistemas heredados

HERRAMIENTAS DE CAPTURA INTELIGENTE

Disponemos de integraciones de Abox-ECM con las principales herramientas de captura inteligente del mercado.

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Las funcionalidades que aporta esta integración son las siguientes:

  • Procesamiento automático de imágenes (mejora, filtrado, transformación de formatos, etc.)
  • Reconocimiento automático de caracteres y códigos (OCR, OMR, multilingüe).
  • Diseño de plantillas para extracción de texto (ICR).
  • Validación de contenidos extraídos (base de datos, supervisión humana, etc.)
  • Exportación multiformato e integración con otros sistemas.

Ver más información aquí

DISEÑO DE FLUJOS DOCUMENTALES CON BPMN

La automatización de procesos empresariales (BPA) gestiona los flujos de trabajo para mejorar la eficiencia de una organización. La BPA no se centra en un solo departamento, sino en toda la organización mediante la implantación de sistemas de software que integran todas las aplicaciones existentes.

Abox-ECM aporta editores gráficos para el diseño de procesos, con más de 100 acciones y comprobaciones incluidas para permitir una automatización completa de cualquier proceso documental, incluyendo la integración con otras aplicaciones.

Dispone de dos lenguajes estándar para la definición de workflows:

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Notación de máquina de estados

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Notación BPMN2

Abox ECM nos ofrece potentes prestaciones para:

  • Pilotar expedientes mediante flujos de trabajo que controlan la presencia y estado de los documentos y metadatos.
  • Pilotar documentos mediante flujos de trabajo independientes o subordinados a procesos vinculados a expedientes.
  • Integrarse con aplicaciones externas mediante una potente API de interoperabilidad.
  • Diseñar y ejecutar flujos de trabajo sobre un doble motor: lenguaje BPMN2 y máquina de estados.

Ver más información aquí

CONTROL DE EVENTOS EN VARIABLES MONITOREADAS MASIVAMENTE

Las alertas generalmente se enfocan en detectar una condición y luego atraer la atención de una persona. Sin embargo, un sistema de alertas puede pensarse como parte de un bucle de control y mejora: observar, detectar una condición, tomar medidas y volver a observar.

Un sistema de alertas debe soportar detección y acciones sofisticadas, reconociendo que la “detección” puede ser más que una búsqueda en el repositorio de datos y que la “acción” se está convirtiendo en algo más que enviar un correo electrónico o llamar un webhook.

Abox-ECM dispone de una integración nativa con la suite Elastic Stack, un conjunto de herramientas open-source para la ingesta, el enriquecimiento, el almacenamiento, el análisis y la visualización de datos.

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Gracias al potente sistema de alertas de Elastic, es posible detectar alguno de los siguientes eventos:

  • Errores o inconsistencias en el registro de información en el sistema.
  • Detección de situaciones anómalas predecibles.
  • Problemas en la infraestructura o conectividad.

DISEÑO DE MODELOS PREDICTIVOS DE MACHINE LEARNING

En los últimos años, el avance de los métodos de Inteligencia Artificial y, en particular, las tecnologías de Machine Learning, ha sido espectacular para el descubrimiento de patrones y la clasificación automática de contenidos digitales.

Grupo Adapting ha realizado investigaciones en esta área, logrando definir una metodología para el diseño y despliegue de modelos predictivos basados en técnicas de Inteligencia Artificial, que consta de 6 pasos:

  1. Recolección y muestreo de los datos.
  2. Análisis exploratorio de datos
  3. Ingeniería de variables
  4. Especificación, entrenamiento y evaluación de los modelos.
  5. Calibración de hiper-parámetros
  6. Despliegue del modelo

Los modelos permiten realizar predicciones empleando y combinando óptimamente información de metadatos, textos reconocidos en los archivos, así como imágenes de la portada de los documentos.

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Algunos ejemplos de modelos a implementar son:

  • Modelo de clasificación de tipos documentales para la reasignación automática de documentos radicados.
  • Modelo de detección de similitud basado en reconocimiento de patrones para relacionar documentos e identificar agrupaciones (p.ej. expedientes).
  • Modelo de priorización de solicitudes y generación de alertas basado en criterios de análisis de sentimientos.

Ver más información aquí

METODOLOGÍA DE DISEÑO DE MODELOS PREDICTIVOS

Esta metodología nos permite ofrecer a nuestros clientes un innovador servicio de diseño que persigue automatizar aquellas acciones que representan cuellos de botella en los procesos documentales que se ejecutan en el SGDEA.

Este servicio se configura como una “co-creación” entre el cliente y nuestra empresa que incluye las siguientes etapas:

Definición del problema

Obtención de datos de entrenamiento

Análisis y determinación de objetivos

Acuerdo económico

Diseño e integración del modelo

Validación y mejora continua

Contacte con nosotros si desea que evaluemos su caso.

APROVISIONAMIENTO DE MODELOS INTELIGENTES EN CLOUD PARA SISTEMAS HEREDADOS

Es posible realizar el diseño de modelos predictivos a medida basados en nuestra metodología para otros sistemas heredados. Los modelos se instalan en nuestros servidores en cloud y se dotan de una API basada en webservices.

modelo-de-sistema-de-clasificacion-predictiva

En estos casos el cliente deberá contar con las capacidades de desarrollo e integración necesarias y se definirán las responsabilidades de cada parte.

Contacte con nosotros si desea que evaluemos su caso.

¿QUIERE AMPLIAR INFORMACIÓN SOBRE ESTA SOLUCIÓN?

SOLICITE UNA DEMO

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