Intelligent Automation Solution
The Power of RPA and AI to Create Intelligent Automation Services
What is Intelligent Automation?
Intelligent Automation (IA) is a combination of Artificial Intelligence (AI) and automation technologies that can perform complex tasks without human intervention. It involves the use of cognitive technologies, such as machine learning, natural language processing, and computer vision, to automate tasks that previously required human intervention. IA can be applied to a wide range of business processes, including customer service, finance, human resources, and supply chain management.
With our enterprise intelligent automation approach, customers can go beyond reducing repetitive process and create end-to-end intelligent automation services all across the organisation.
Intelligent Automation Opportunities
Benefits of using Intelligent Automation RPA
Generate More Business with AI Powered Intelligent Automation Platform
Explore AutomationEdge Intelligent Automation Platform
DocEdge - Intelligent Document Processing
AutomationEdge’s DocEdge captures data across critical documents (e.g., email, text, PDFs, and scanned documents) to categorize and extract them for further processing. Using Machine/Deep Learning, computer vision, Optical Character Recognition (OCR), and Natural Language Processing (NLP) makes this all possible.
AI in the Cloud
AutomationEdge’s CogniBot for IT uses Natural Language Understanding (NLU) and Artificial Intelligence to understand employees’ natural context and effectively disambiguates confusing utterances while interacting with employees.
UI Automation
With UI integration technology, users can access most desktop interface elements programmatically. As well, it allows users to automate repetitive and cumbersome tasks with legacy applications that do not offer APIs.
Business Process Management (BPM)
BPM, in many ways, is the bedrock of any effective automation approach, which must be established, maintained, and enhanced. To avoid breakdowns that can have severe effects on their operations, organizations must build new workflows and test them before implementing them. A strong and straightforward tool for managing an organization’s hyperautomation strategies and initiatives is business process management software.
Machine Learning (ML)/ Artificial Intelligence (AI)
To find patterns in data, companies utilize both supervised and unsupervised AI/ML algorithms. Before making predictions on their own, supervised algorithms produce inputs and outputs. Pattern recognition is used by unsupervised algorithms to gain insights from structured data. AI and ML are some of the strongest automation techniques. As a result, achieving hyperautomation necessitates the strategic deployment of AI and machine learning.
Customer Success Stories
FAQs
Intelligent automation uses a combination of technologies like RPA and AI technologies like Machine Learning(ML), NLP, and OCR to create an intelligent ecosystem that can help in data collection, data analysis, decision-making, process automation, and continuous improvement.
No, AI and intelligent automation are not the same thing, but they are related concepts. AI refers to the development of computer systems that can perform tasks that typically require human intelligence.
On the other hand, intelligent automation combines AI technologies and automation technologies, such as robotic process automation (RPA), to automate business processes and tasks that previously required human intervention.
RPA is a type of automation technology that uses software robots or bots to automate routine, repetitive, and rule-based tasks such as data entry, form filling, and copying and pasting information between different systems.
Intelligent automation, on the other hand, is a broader concept that includes RPA as well as other automation technologies, such as artificial intelligence (AI), machine learning, and natural language processing. Intelligent automation uses these technologies to automate more complex tasks that require cognitive skills, such as decision-making, problem-solving, and pattern recognition.
Intelligent automation, on the other hand, is a broader concept that includes RPA as well as other automation technologies, such as artificial intelligence (AI), machine learning, and natural language processing. Intelligent automation uses these technologies to automate more complex tasks that require cognitive skills, such as decision-making, problem-solving, and pattern recognition.
Intelligent automation consists of several key components like RPA, AI, cognitive automation, chatbots, virtual assistants, and data visualization to automate complex business processes and offer better productivity and process efficiency.
To get started with intelligent automation first identify the process, define the objectives, select the intelligent automation platform, develop an automation strategy, implement the automation, and monitor the performance of the system.
Intelligent automation can be applied to chatbots to make them more effective in handling customer inquiries. For example, the chatbot can be integrated with an RPA system to automate routine tasks such as data entry and form filling. The chatbot can also be trained using ML algorithms to improve its ability to understand customer inquiries and provide accurate responses.
To make an informed decision, it’s important to consider several factors like understanding business requirements, ease of use, scalable platform, integration capability, implementation support and training, affordable pricing, and better security.
