ADVANCED ANALYTICS AND INTELLIGENT AUTOMATION
The combination of artificial intelligence (AI) and automation to bolster mission effectiveness through analytics and reporting
WHAT IS INTELLIGENT AUTOMATION?
Intelligent automation includes all facets of data analytics including data collection and report generation, automated analytics, and Robotic Process Automation (RPA). These functions leverage existing data and processes within an organization to transform decision making and reducing the strain on staff to repeat intensive but mundane tasks.

Artificial Intelligence
Artificial intelligence (AI) algorithms are used to automate business processes that otherwise rely on human judgment. AI is used to find patterns in data, gain insights, and offer data-centric prediction models. Unlike traditional software development where the logic and rules are all fixed within a program’s backend, with AI, the machine learns the appropriate rules to follow from data, either during training or adaptively in production.

Machine Learning
Machine learning (ML), a subset of AI that includes powerful methods like deep learning neural networks, random forest, and gradient boosting algorithms, often relies on large amounts of data and provides fast and accurate solutions to challenges that are difficult to manually compute or analyze.

Robotic Process Automation
Robotic Process Automation (RPA) is a discipline that is tailor-made for the operational challenges that Federal Agencies face today. RPA solutions can streamline processes at any level and can unlock operational efficiencies by reducing the time employees spend on rote, repetitive, or predictable tasks. Bots can pull data, reconcile data, and prepare data for analysis in dashboards or other reports.

Intelligent Automation
Intelligent automation is the powerful combination of RPA with AI and cognitive capabilities. It enables organizations to automate end-to-end process workflows, streamlining processes to quickly produce and provide the needed valuable insights to your organization's decision-maker From the efficient collection of data to its synthesis and analysis, intelligent automation processes can adapt and optimize over time with the help of machine learning techniques.