The recent tryst with recurrent pandemics, infection risk due to repeated handling of paper documents, and the focus on Go Green initiatives is mandating governments, social bodies, banks, and PSU organizations to look for Digital alternatives as their paper consumption is on the higher side. Misplaced paper documents and files as well as lack of transparency, accountability, and traceability is demanding Digital Transition and a change in the protocols in which enterprises function towards a paperless Digital Office model.
NAlliancetech Digital Workplace offers a cloud-based, paperless digital eOffice solution. It can be customized and tailored to suit the widest set of business requirements including snail mail tracking and file management, digital office automation, and records management towards a remote collaborative workspace. It enables enterprises to embrace an immensely agile, safe, scalable, and future-proof business model for supporting a remote operations or work from home culture.
NAlliancetech Digital Workplace eOffice solution is powered by Cloud-based Enterprise Content Management (ECM), Intelligent Data Capture or Intelligent Data Processing or Intelligent OCR, and configurable workflows. Artificial Intelligence (AI) / Machine Learning (ML) algorithms improve the classification, storage, and retrieval of the digitized data assets. A seamless User Experience Design (UXD) powered by .Net technologies offers an intuitive and strategically designed user interface.
Snail Mail / File Management and Tracking on Whitehall based file system
Correspondence / Letter Management
Office Note Management
Committee & Meeting Management
Integration with Circular Management Application
Digital Office Automation
Dashboard & Reporting
Eliminates Paper Usage
Pre-defined Escalation Matrix
Advanced Collaborative Features
Anytime Anywhere Access
Native Language Compliance
Integration With Enterprise Applications
Captures and archives all decisions throughout the lifetime of the office correspondence or snail mail
Helps in efficient movement of the digitized assets with complete accountability and audit-ability throughout the lifecycle
Office Note Management
Manage files and correspondences with electronically driven green notations
Committee & Meeting Management
Helps with system managed alerts, notifications, and reminders, with ease of creating or dissolving committees dynamically, maintaining records of the committee decisions, minutes, etc.
Collaboration & Messaging
Provides a collaborative environment with advanced features, such as chat rooms, discussion forums, etc.
Captures, maintains, and manages the information and knowledge generated through various business processes for future reference
Internal / External Query Management
Helps to adhere to the deadlines for response to queries and provides a glimpse of approaching deadline without even opening the file through visual indicators
Improved Productivity & Efficiency
Optimization Of Digital Office And Go-green Initiatives
Faster Decision Making Due To Fast Search And Faster Retrieval
Increased Security Through Multi-level Authentication
Increased Accountability Due To Usage Of Digital Signatures
Improved Cost Savings Through Reduction In Physical Spaces
Elimination Of Data Loss Due To Misplacement Or Thefts
Increased Employee Engagement In WFH Mode
Increased Revenues Due To Speedier Movement Of Files
Optimized Usage Of Man-power
Improved Processes Eliminating Pendency
Easier Tracking, Traceability, Search-ability And Retrieval
Artificial Intelligence solutions enable the automation of medium to complex processes and take Robotic Process Automation to the next level. It powers predictive maintenance of heavy machines thus reducing operational costs. AI enables pattern identification with vast data volumes thus augmenting human intelligence and decision making. It improves the analytics domain to the nth extent. While Natural Language Programing (NLP) algorithms read and augmedata nt to produce analytical reports, Natural Language Generation (NLG) algorithms write sentences.
AI joins the dots from disparate data sources and discovers interesting patterns that are less visible to the human eye and intellect. Consistent variations, clustering of data points, dependencies, etc., bring forth interesting stories from the stagnant data resources. Using data, AI-enabled information mining generates hypotheses, verifies them, and deduces information. Information Mining forms the basis of Predictive Analytics and Machine Learning.
AI-powered Data Mining enables users to perform different levels of tasks –
Anomaly detection, where unusual patterns or outliers are thrown up, which may be errors or require deeper investigation
Associations, where the relationship between two or more variables are brought forth, and is frequently used in forensic investigations
Clustering, where data points that are similar in more than one ways are discovered
Classification, where known structures are generalized in order to apply to new data points; for example: Records or File Classification
Regression, where a function is found, which models the data and estimates the relationship between different data points
Summarization, where a concise summary is generated based on weighted keywords. It is popularly used for generating audit reports and executive summaries.
AI simplifies Document Management to a great extent. It enables automatic file classification or categorization as well as summarization. The files may include spreadsheets, documents, emails, PDFs, video files, audio files, social media, news, and other data types.
AI algorithms generate intelligence from high data volumes by correlating disparate data points. This data may comprise structured, unstructured, and multi-structured data.
A recent feature is AI-enabled Topic Modelling. It allows screening of huge data sets, such as reviews, emails, social media snippets, etc., and segregating them as per the predominant sentiment.
AI algorithms use weighted keywords and correlate them to generate concise summaries of lengthy documents, news articles, research papers, agreements, books, tweets, etc.
It uses two methods – Extractive and Abstractive. Extractive Summarization extracts several portions of the text and stacks them to create a summary. Abstractive Summarization uses NLP algorithms and generates a new summary.
AI-powered document summarization is used in audits, research study scenarios, social media listening, government services, etc.
N Alliance Tech Commercial Director
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