An AI Model (or simply model) represents a program that has been trained on a set of data to recognize certain patterns or make certain decisions without further human intervention. You handle the models in Administration >...
Training AI models is a computationally intensive and time-consuming process, often requiring specialized hardware and large datasets. For this reason, not all models can be trained directly within LogicalDOC. To simplify adoption, the system allows...
Fillers are configurable components used to extract and populate structured information from documents automatically. They define how specific data, such as tags, language, and templates, are identified and retrieved from document content. Fillers are...
The Zero-Shot model enables automatic classification of documents into user-defined categories without requiring prior training on those specific labels. This allows the system to dynamically assign tags based on the semantic meaning of the content,...
Embeddings are vectors representing entire documents or fragment of them into a continuous vector space. This numerical representation of is required to efficiently infer similitudes between documents and implement features like Semantic Search. This...
Artificial Intelligence or simply AI, could be defined as a technology that enables machines to simulate human learning, comprehension, problem-solving, decision-making, creativity and autonomy. Beyond such introduction, there is no single, simple...
The Language Detection model automatically identifies the language of a document based on its textual content. This enables the system to classify documents by language and support language-specific processing workflows. The model is based on a...
A neural network is an AI model that teaches computers to process data by modeling it on how the human brain works. It is a type of machine learning (ML) process, called deep learning, that uses interconnected nodes or...
Natural Language Processing, or simply NLP, is a class of AI model designed to process naturally written texts. NLP enables computers to understand, interpret, and generate human language. It bridges the gap between human communication and machine...
The Classifier is a natural language component that assigns a category to a given text based on its content. In this system, the classifier is trained using pairs of example data, where each pair contains a category label and a sample sentence that...
The Custom Reports package leverages the reporting features of Eclipse BIRT, enabling users to create reports on the application's activity, directly from LogicalDOC. Users can create and generate reports, defining what...
The Embedder class models enable the mapping of entire documents to fixed-length vectors, making it possible their representation in a continuous vector space. This facilitates efficient comparison and manipulation of textual data in natural language...
Before you can start integrating LogicalDOC with ChatGPT’s API, you need to get an API key to access it. 1
Create an account You can create a free account by signing up here. 2
Generate an API...
The Tokens Detector is a specialized natural language model designed to identify and extract specific pieces of information, called tokens, from within a sentence. It is used to detect structured data like IDs, names, dates, or codes embedded in...
A robot is an intelligent agent designed to understand user questions and provide meaningful answers. Robots act as an interface between the user and the Natural Language Processing (NLP) engine, using trained models to...
A sampler is an object used to retrieve and prepare a dataset for the training of a model. You handle the samplers in Administration > Artificial Intelligence > Models > Samplers You can count on different types of samplers with different settings:...
DocuSign allows organizations to manage electronic agreements and offers eSignature, a way to sign electronically on different devices. Signatures processed by DocuSign are compliant with the US ESIGN Act and the European...
A vector store indexes and stores vector embeddings (the vectorial representation of documents) for fast retrieval and semantic search. Embeddings are generated by AI models, in the context of machine learning these features represent different...
This panel shows the list of all users currently existing into the system. To add a new user, you have to click on Add User button and then fill all the required data: Username Email First Name Last Name Language Group Each user can belong to one or...
