Robotic Process Automation
Intelligent Automation Center of Excellence
Intelligent automation, the seamless integration of Artificial Intelligence, Generative AI, Machine Learning, Analytics and Robotic Processes, heralds a transformative era across industries. This synergy empowers businesses to optimize efficiency and accuracy while reducing operational costs. By automating routine tasks, AI-driven systems enhance productivity, enabling employees to focus on higher-value, creative endeavors. Moreover, the synergy minimizes errors, maintaining a high standard of quality. Intelligent automation's real-time data analysis also facilitates informed decision-making, accelerating business growth. Ultimately, this technology reshapes workflows, fostering innovation, and propelling organizations towards a future of streamlined operations and heightened competitiveness.
Robotic Process Automation (RPA)
- RPA involves using software robots or "bots" to automate repetitive and rule-based tasks that were previously performed by humans
- It can automate data entry, data extraction, data processing, and other routine tasks across various applications
Hyper-Automation and Cognitive Intelligent Automation
- Cognitive Intelligent automation combines Al and machine learning to automate complex tasks that require human-like reasoning, understanding, and decision-making.
- It includes natural language processing (NLP), sentiment analysis, image recognition, and more
Chatbots and Virtual Assistants
- These are Al-powered tools that interact with users in natural language, providing information, answering questions. and performing tasks
- Chatbots can be used for customer support, information retrieval, and basic problem-solving
Machine Learning Solutions
- Machine learning algorithms analyze data to learn patterns and make predictions or decisions without explicit programming
- Applications include fraud detection, demand forecasting, recommendation systems, and more
- Predictive analytics uses historical data and statistical algorithms to forecast future outcomes and trends
- It's used for demand forecasting, risk assessment, and resource optimization
Intelligent Data Capture
- This involves automatically capturing data from various sources like documents,
- images, and emails, and converting it into usable formats Al helps extract and validate data accurately
Decision Support Systems
- These systems provide insights and recommendations to assist human decision-makers
- They often use Al to analyze complex data sets and provide actionable insights
- Al-driven workflow automation systems manage and optimize business processes, routing tasks to the right people or systems
- They ensure smooth coordination among different tasks and stakeholders
Analytics Process Automation (APA)
- It leverages advanced data analytics and automation techniques to streamline the data preparation, analysis, and reporting processes-
- It enables organizations to make data-driven decisions faster, improving their agility and responsiveness to market changes.
Process Mining and Optimization
- Process mining involves analyzing event logs to understand how processes are executed
- Al can help identify bottlenecks, inefficiencies, and areas for process improvement
Business Process Management (BPM) with Artificial Intelligence
- Integrating Al into BPM systems allows for intelligent process automation, predictive analytics, and optimization of workflows
- This helps in making processes more adaptive and efficient
Natural Language Processing (NLP) and Large Language Models (LLM)Solutions
- NLP technology enables machines to understand, interpret, and generate human language
- It powers applications like sentiment analysis, language translation, and text summarization
Intelligent Document Processing (IDP) and Extraction:
- Al-driven solutions can automatically extract and process information from unstructured documents like invoices, contracts, and forms
- This reduces manual data entry and improves accuracy
Robotic Process Automation (RPA) is a subset of Intelligent Automation software that mimics human behavior to execute rule-based processes with limited or no human intervention. If your organization has any operations that fall under the below categories are potential candidates for automation.
- manually done today
- involve highly repetitive tasks
- rule-based tasks
At Wissen, we take up robotic process automation engagement in a systematic way by following 3 step approach as described below:
In this step, we review proposed processes for automation and add qualified functions to the backlog. We identify data needed for the matrix and assign data collection.
Scoring and prioritization
In this step, we score and prioritize processes leveraging matrix data and kick off preliminary process flow design discussions.
In this step, we draft RPA automated functional design for selected sub-process, Identify opportunities to optimize before automation (time-boxed), and discuss automation progression/increments for end-to-end processes.A typical business robotic automation scenario before and after implementation of RPA in an organization:
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