Native Cognitive Capabilities for Complex Processes
By combining the power of RPA with native Artificial Intelligence (AI) and other cognitive capabilities, Nividous Smart Bots empower business users with the ability to easily automate processes involving complex documents. Capabilities such as Intelligent Document Processing (IDP), Natural Language Processing (NLP) and Predictive Analysis give our Smart Bots the ability to classify, extract and validate data from any type of document, application or database. Using proprietary Machine Learning (ML) models, Nividous Smart Bots learn from experience, becoming faster and more reliable, significantly reducing operational costs and human errors. All of this work can be done without the need for data scientists or other scarce specialists and no expensive third-party components are required.
Intelligent Document Processing
Documents are still a reality in almost every business and industry. They exist in large volumes, differing languages, and in varying formats and quality. They can present an impediment to digital transformation, particularly those in semi-structured or unstructured formats. Businesses often struggle to process these documents with accuracy and speed.
Nividous’ Intelligent Document Processing (IDP) solution solves this problem by capturing, categorizing and extracting relevant data from these documents for further processing using Computer Vision (CV) based Optical Character Recognition (OCR) and ML.
An intuitive and simple interface makes it extremely easy for the business user to create custom templates that allow for high quality data extraction from structured, semi-structured, and unstructured documents. The cognitive capabilities can be easily extended for on-device data extraction allowing the field workers to manage structured data on their fingertips. A range of pre-built domain specific ML models are available out of the box. Unlike other platforms, users can build custom ML models as needed and train them by annotating feedback on the fly. That learning is transferred for future processing to achieve significantly improved accuracy.
IDP can be applied to a wide variety of use cases including
- Invoice and purchase order processing
- Know your customer (KYC)
- Proof of delivery
- Loan applications
- Customer onboarding
- Insurance claims
Structured Data on Your Fingertips
Employees and partners that are constantly on the go extensively use mobile devices for convenience, but there is often a need for additional processing through the back office. Leverage intelligent data extraction on-device to eliminate manual errors, high human capital costs, and infrastructure costs. The natively embedded cognitive capabilities within Nividous Smart Bots can be easily extended to hand-held devices for straight-through processing enabling field workforce to complete mission-critical tasks in real-time without any need to connect to other systems.
Natural Language Processing
Natural Language Processing (NLP) adds the capability to understand the human language the way it is written or spoken. Applications such Chatbots and Virtual Assistants are using NLP to perform tasks traditionally carried out by humans. By combining NLP with Machine Learning, critical information can be discovered by developing models from unstructured data including emails, videos, social media posts, etc. With Nividous, there is no need to rely on third party services. Users can simply train custom NLP models from their existing data to achieve exceptionally accurate results. Several pre-trained models are available for email and text classification, sentiment analysis, named-entity recognition and more.
Predictive Analysis
Predictive Analysis is the practice of making projections about possible future outcomes based on available historical data and ML techniques. Businesses often use predictive models to evaluate risk and uncover opportunities. By incorporating RPA and AI, companies achieve improved data quality through a reduction in errors and better data accessibility. Workload is reduced through report automation and there is a resulting decrease in overall costs. Nividous enables users to create a model that helps to predict probable outcomes with a confidence score allowing for better informed decision making. Several pre-built models are available for mission critical processes including predicting fraud propensity for loan approvals, probability of an insurance claim and predicting fraudulent credit card transactions.
Key Features
Out-Of-The-Box Maker Checker
An intuitive interface that shows the original document and extracted data side by side with the fields being highlighted for review. Easily tab through the fields for data review and correction.
Feedback Loop
The corrections made during the maker-checker stage can be annotated on the fly to train machine learning models so that similar exceptions can be managed without human intervention in the future.
Training Custom ML Models
Train your custom ML models using an intuitive interface that allows users to annotate exceptions on new documents for training as well as feedback.
Ease of Template Creation
Create custom templates with an intuitive interface that allows users to add fields, define their labels and map relevant values. User can also specify synonyms and patterns for value extraction.
Confidence Score
Set your custom process-specific benchmark i.e. confidence score for the extracted data. The Smart Bot highlights the extracted data that falls below the confidence level and triggers an instant for a human intervention.
Pre-Built ML Models
A range of pre-built domain specific ML models are available out of the box. Leverage built-in domain expertise that is specialized in instantly finding unique process specific data.