DocQuest enables seamless document upload, accommodating a wide array of document types, such as reports, contracts, and policies that too in various formats. Using advanced content-based search capabilities, users can ask specific questions and receive precise answers directly from uploaded documents, ensuring rapid access to accurate and contextually relevant information.
This case study delves into the challenges faced by client, the solution we provided by streamlining workflow process automation using WordPress & Woo-Commerce.
Introduction: Overview of the Project This case study entails the development of a software system to track fuel inventories for Badri Rai & Company across its multiple warehouses. The objective was to prevent fuel theft, record fuel purchases, and automate the input data related to stock transfers and purchases. The lead project engineer, solution architect,
Abstract Insurance service providers operate in a highly competitive environment wherein customers and stakeholders expect on-demand settlement of claims. Despite digitization of processes, the insurance industry is prone to delay in grievance handling and claims processing resulting into rise in frauds and a dissatisfied consumer. One of the unresolved bottlenecks here is the errors in
Customer Background The customer is a renowned healthcare technology company in the United States. Over the years, the company has provided software solutions to an array of hospitals, clinics, research centers and other medical institutions. The business provides information management services on their native tool in United States. Business Requirement As the business underwent significant
We at Intellinez employed React, a declarative, efficient, and flexible, open source javascript library for building user interface.
A multinational company wanted to benefit from using data warehouse services, advanced analytics, data mining, and reporting, by migrating from an on-premise Oracle-based platform into a scalable cloud data warehouse solution. The solution to be migrated had two terabytes-sized Oracle databases. Advanced analytics queries were in many cases timing out and underlying infrastructure had to be optimized for OLAP rather than OLTP.