Puzzle
Docs IA
Puzzle DocsIA
We adapt the documents to be processed so that you can adopt this technology, extracting the data that drives your business.
In a few seconds we search or receive documents from multiple sources such as: multifunctional devices (MDFS), scanners, digitized documents, images captured from mobile phones.
al destino deseado, ya sea una base de datos o a un sistema que el cliente considere seguro y confidencial.
• Receipts
• Referees
• Bills
• Expense summaries
• Purchase Orders
• Contracts
• Waybills
• Forms
• Judicial documents
• Clinical Histories
• Certificates
• Requests
• Titles
• Policies
With Machine Learning technology, it automatically extracts, processes and analyzes your documents.
Puzzle DocsIA eliminates the risk of human error by manually interpreting documents and then transcribing the data into other formats. It reduces the possibility of human error and greatly improves the accuracy and consistency of the data, which is crucial for effective decision making and risk management.
At the most basic level, it’s easier to ensure that all documents are in order when they’re stored electronically than when they’re stored on paper.
Frequent Questions
The most important thing you have to keep in mind is that the costs are for consumption. The more you consume, the cheaper the service is.
To estimate the processing costs you have to take into account the complexity of the data to be extracted and the monthly processing volume. For that there are 3 categorized bands. Check your quote in an interview or phone call.
All types of scanned digital documents. Including handwritten text, table embeds, digital text, text only, symbols, etc.
Yeah! It does not require any user training.
You do not need any prior platform or service, or programming language, or a computer specialist. It is simple and for anyone.
PUZZLE DOCS AI uses AI algorithms combined with NLP to identify document types by matching unknown documents to existing categories.
Features are extracted and fed to algorithms, which calculate a similarity score. The similarity score is used to determine the most accurate category for document classification
When receiving a scanned or captured image of a document, IDP intelligently extracts relevant data using OCR and AI algorithms. All types of data can be extracted: Structured data – Data that is organized and has a logical structure (e.g. CSV, JSON, XML).
Unstructured data that requires manipulation, such as data cleansing, prior to the extraction process, as they do not always have a logical structure that machines can read (e.g. emails, images or scanned documents).
Al recibir una imagen escaneada o capturada de un documento, IDP extrae de forma inteligente los datos relevantes mediante algoritmos de OCR y de IA. Se pueden extraer todo tipo de datos: Datos estructurados – Datos que están organizados y tienen una estructura lógica (por ejemplo, CSV, JSON, XML).
Datos no estructurados que requieren una manipulación, como la limpieza de los datos, antes del proceso de extracción, ya que no siempre tienen una estructura lógica que puedan leer las máquinas (por ejemplo, correos electrónicos, imágenes o documentos escaneados).
PUZZLE DOCS IA utiliza algoritmos de IA combinados con PNL para identificar los tipos de documentos mediante la correspondencia de los documentos desconocidos con las categorías existentes.
Se extraen las características y alimentan a los algoritmos, que calculan una puntuación de similitud. La puntuación de similitud se utiliza para determinar la categoría más precisa para la clasificación de documentos.
Combinamos el reconocimiento óptico de caracteres y las tecnologías de inteligencia artificial (IA) como el aprendizaje automático, el procesamiento de lenguaje natural y el aprendizaje profundo para extraer información de documentos no estructurados o semiestructurados, y convertirla en datos estructurados y de búsqueda.