Abstract: A quality control system and method is disclosed which automates the quality control of invoices during invoice generation. The invoicing module of the quality control system receives the input data from the CRM platform. The prompt generator coupled with the invoicing module generates prompt based on the input data. The AI engine receives the prompt to classify and QC the input data to ensure completeness of the data. The validation module of the AI engine triggers invoice generation upon successful validation of the input data. The invoice provides real-time notifications or alerts to the user.

Abstract: A collaborative project workspace system and process facilitates real-time interaction between multiple users and an artificial intelligence (AI) engine within a shared project workspace. The collaborative project workspace system and process maintain a project database that stores users queries, documents, communications, responses, and user interactions. Through a user interface, the users can submit queries and documents, which are processed by an AI control system and transferred to an embedding module. The embedding module transforms inputs into vector representations, which are then stored in a vector database. Using this vectorized data along with contextual information from the vector database, the collaborative project workspace system and process generate responses through AI engines that combine both large and small language models.

Abstract: An application generation system and process using a user query and one or more documents ingested via an online document management platform is disclosed. The application generation process involves automatically ingesting documents from multiple sources, including local and cloud storage, using API bundles to create a vector database. The ingested documents are analyzed to identify patterns and contextual information, generating a priority score for the documents. Upon receiving a natural language input from the user, a prompt is generated based on the analyzed patterns to guide an AI engine. The AI engine utilizes the user query, prompts, and ingested documents to generate, test, and validate the application code in a simulated environment. The finalized application and its code are then presented to the user for execution.

Abstract: The system and method for guiding an Artificial Intelligence (AI) engine to automate the quality control process for generating quotes. The quote generation process involves receiving quote requests from a customer relationship management (CRM) system or a data structure entry point. Moreover, retrieving quote data associated with the quote request from data sources, including a CRM platform, via application programming interfaces (APIs) triggered by the submission of the quote request. Furthermore, the prompts are generated by a prompt generator to guide the AI engine in validating the retrieved quote data. The prompts are then transferred to the AI engine for validation, a process that involves analyzing the quote data against predefined rules and conditions, such as price structures, terms, and conditions. Subsequently, a quality control result is generated based on the validation, indicating whether the quote passes or fails the validation process.

Abstract: A document ingestion system and process that manages documents and generates a summarized document using a user query for ingesting and summarizing documents based on a user query is disclosed. The document ingestion process involves ingesting documents from local or cloud storage and analyzing them using natural language processing (NLP) techniques. The analysis assigns metadata tags and extracts relevant content, which is then converted into vectorized embeddings for efficient retrieval. The embedded document content is divided into smaller, coherent chunks based on semantic structure, facilitating granular processing. Each chunk is assigned a priority score based on content, context, and relevance, ensuring that the most important information is utilized. A prompt is generated to guide an AI engine in producing a summarized document or answering the user's query. The AI engine processes the prioritized content and generates a summary based on the user's query and ingested documents.

Abstract: A method and system for guiding an Artificial Intelligence (AI) engine to process call responses in a collection process. Typically, a crawler bot is utilized to fetch customer details such as contact numbers to initiate calls using voice module. The call responses, which can include human voice, Interactive Voice Response (IVR) system responses, recorded messages, or silence, are then received and processed. The voice-to-text converter is used to convert call responses into text. The converted response is classified using the AI engine. The categorized responses are used to generate appropriate follow-up actions, which are converted into voice scripts for subsequent follow-up calls in collection process.

Abstract: An automatic knowledge base article generation system and process receives a support ticket through a user interface integrated to a support platform, automatically processing the support ticket containing problem statements and their corresponding solutions. The automatic knowledge base article generation system and process employs an AI engine guided by generated prompts that transform unstructured the support ticket data into knowledge base articles. The AI engine extracts relevant problem statements and solutions from the support ticket using natural language processing (“NLP”) techniques and generates a knowledge base article. The knowledge base article is then transmitted to a knowledge base system for review.

Abstract: A method and system for guiding an artificial intelligence (AI) engine to process customer inquiries regarding financial information and provide a response to the customer. The system and method receive a customer inquiry related to a financial issue through a communication interface, which could be a voice or chat interface. The received inquiry is analyzed by a natural language processing (NLP) module to determine the intent associated with the inquiry. A prompt generator is used to dynamically generate a prompt for requesting financial data, with the prompt being populated with information relevant to the determined intent based on predefined templates for the financial inquiry. The generated prompt is provided to the AI engine, which analyzes the prompt to determine whether the provided information is sufficient to generate an application programming interface (API) request for a financial management system to receive a response from a database to respond to the inquiry.

Abstract: A debt management and collection system and process is disclosed which analyzes input data, including, debtor information, invoice details, payment histories, and interaction logs through a recording platform. A prompt generator guides an artificial intelligence (AI) engine by converting input data into prompts. The debt management and collection system and process feature a communication platform connecting an agent coordinator with multiple AI agents. The agent coordinator analyzes debtor profiles and collection stages to develop targeted strategies, then deploys the AI agents who engage with debtors using personalized approaches. The debt management and collection system and process continuously update an input database with new interaction data, including agent actions, debtor profiles, communication records, and payment statuses.

Abstract: The Artificial Intelligence driven service outage detection and customer support ticket management system in customer support platforms includes a customer support platform that is operatively coupled to the service outage detection system. A data collector gathers input data from a product status page and a service request tracker document. A service outage detector (SRT) detects the service outage by monitoring the product status page and incoming customer support tickets raised against the products by the users. A comparator compares the details of the product status page and the SRT document to confirm the occurrence of the service outage. A customer support ticket router updates the customer support ticket routing process based on the confirmed service outage status. A response generator generates an automated, predefined response including service outage information and any expected resolution or alternative support options and notifies the user utilizing a notification module.

Abstract: An AI-based customer ticket routing system and method for optimizing the efficiency of the AI engine to enhance the ability of the customer routing system to route the customer ticket to a relevant department or agent. The method involves the receiving of customer tickets from the ticket generation platform. The ticket routing system receives the customer ticket and accesses the SRT database. The ticket routing system utilizes an AI engine to check the intent of the customer's tickets. The AI engine guides the ticket routing system to route the customer ticket to a relevant department for resolution which in this case in an agent, automation, L1 bot, and L2 bot.

Abstract: A configuration mapping system and method increase the effectiveness of mapping of information from an established product line to a new product offering. In at least one embodiment, the configuration mapping system herein uses configuration mapping rules to map individual product features and entire configurations from established products to a new product offering. The configuration mapping system also provides a way to appropriately map, for example, demand and sales information for the purpose of demand estimation and sales prediction. Conventionally, mapping can be ineffective because the configuration mapping rules usually focus on one part of the product at a time, and, if applied in isolation, the impact on other parts is missed. The systems and method herein provide a way to integrate configuration mapping rules across feature parts, time periods, and product lines into a unified, holistic view, allowing for new insights.

Abstract: A configuration mapping system and method increase the effectiveness of mapping of information from an established product line to a new product offering. In at least one embodiment, the configuration mapping system herein uses configuration mapping rules to map individual product features and entire configurations from established products to a new product offering. The configuration mapping system also provides a way to appropriately map, for example, demand and sales information for the purpose of demand estimation and sales prediction. Conventionally, mapping can be ineffective because the configuration mapping rules usually focus on one part of the product at a time, and, if applied in isolation, the impact on other parts is missed. The systems and method herein provide a way to integrate configuration mapping rules across feature parts, time periods, and product lines into a unified, holistic view, allowing for new insights.