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 valuable insights your organization’s decision-makers need. 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. Intelligent automation use cases range from fraud identification and self-driving vehicles to threat detection using sensors and automated decision-making tools. Chatbot and virtual assistant technologies leverage natural language processing and AI technologies to simulate and understand human conversations and execute automated processes, optimizing their performance over time as they learn from their environment. As more and more data is generated, especially with big data producers like Internet of Things (IoT) devices, it is critical that organizations have scalable capabilities to collect, ingest, process, and analyze data. From prescriptive road maps and pilot projects to full-scale production, Guidehouse combines its deep AI and automation expertise, and knowledge of industry-leading, open-source, and commercial tools to guide and implement your organization’s intelligent automation end-to-end solutions.

Optical Character Recognition Bots

In a world still full of physical documents and images, data collection and aggregation can be a tedious, error-prone process done by hand. Scanned forms, letters, prescriptions, and other documents with no digital form available currently require manual labor to acquire the information they contain.

Intelligent automation offers a solution to this challenge called optical character recognition (OCR). OCR’s powerful image recognition technology allows bots to recognize and record text from images and PDFs in a very short time, enabling extremely fast and accurate data collection and aggregation for analysis. Guidehouse’s RPA bots have helped some clients reduce data processing time by 90%, compressing dayslong processes into a matter of minutes.

Example use cases:

• Automated Report Generation: Built a solution that utilizes advanced OCR to read hundreds of scanned PDF documents, aggregate information with data from different websites, and produce reports. These reports directly point to issues of interest within the PDF documents, as well as highlight results of automated data consistency and business validation checks. The solution reduced processing time for each document from approximately 4 hours to 15 minutes.

Automation for Open-source Data

Guidehouse combines its diverse AI and automation expertise in its automation for open-source data offering, helping your organization leverage and mine open-source data from social media and other digital platforms and unlock its high potential value to offer targeted insights and inform strategic approaches. Data feeds across the internet, including published documents and research, open data sources, geospatial data, and web-scraped datasets, can be leveraged to support robust AI experiments. However, this data is often messy and unstructured, posing challenges to extracting actionable information from the data. Automation mitigates this risk, streamlining the data extraction and processing steps to enable powerful analytics.

AI and automation-coupled solutions can have powerful capabilities, such as automated due diligence checks, entity mapping for predictive supply chain risk, and optimized key opinion leader mapping. Additionally, social media data can be aggregated and analyzed to measure sentiment around specific topics and to identify issues the general population is discussing; automation enables the data fed to natural language processing (NLP) and understanding algorithms. AI can also be used to assist and transform traditional open-source intelligence-gathering techniques.

To aid in mining the most value out of open-source data, Guidehouse’s AI experts apply techniques, such as entity mapping, linking, and analysis, using powerful graph databases, which allow us to study the connections and impacts between data points. We combine our expertise on AI and NLP techniques within a flexible, technology-agnostic framework to capture and analyze information, discussions, and interactions across social media and other digital platforms to diagnose why activity is occurring, correlate and predict what is likely to happen, and identify courses of action.

Example use case:

• Issue Monitoring: Developed a monitoring tool to analyze social media activity surrounding a chemical contamination situation. We met the challenge of extracting actionable information from unstructured social media posts and supported the client in identifying hundreds of additional impacted sites. Guidehouse’s comprehensive approach also allowed the client to develop a social media strategy to address subsequent issues.

Planning & Optimization

Planning and optimization solutions allow our team to build efficient, platform-agnostic solutions that streamline processes in your systems. Due to their efficiency in optimizing processes that are often too complex for human analysts, these solutions drive significant impact in different sections across many agencies and have high transformative potential for more. Through planning and optimization, Guidehouse has worked with several agencies to inform and optimize their organizational structures, agency processes, and strategic planning.

Example use cases:

• Workforce Planning: Developed a visualization solution to support workforce planning, training compliance, predictive attrition, assessment of competency of the candidate pipeline, and employee movement. This shaped agency campaigns to support workforce engagement around data analytics and inform their human capital strategy.
• Staffing Optimization: We helped optimize staffing levels to maximize budget, increase security, and achieve agency mission. Built a prototype workforce staffing model, as well as other analytical and machine learning models, to help the agency understand the risks and complexities associated with applicants, better anticipate workload demands, and reallocate staff to areas with higher demand.

Multi-application Integration

RPA offers a significant advantage over other automation tools in that it can combine various applications into one script without complicated back-end automation. Even with powerful scripting tools, analysts often find a need to combine capabilities from different programs on the market because of required functionalities that are spread across these different tools. This makes automation a much more difficult task: clients don’t have any clear way of seamlessly performing processes without resorting to manual labor.

RPA creates a workflow for your process and has the capabilities to interact with almost all applications, even offering capabilities to send and receive emails, connect and run on virtual machines, etc., so that you can combine your entire workflow process into one RPA bot. Developers and analysts have the capability to use lower-level programming languages to perform more customizable tasks in more detail in an error-free, automated fashion. Being able to invoke scripts in different programming languages (e.g., Visual Basic for Applications, Python, R) allows RPA capabilities to expand to more realms of automation and create impact in bigger ways.

Example use case:

• RPA Integration with Enterprise Applications: Our developers connect our partners’ RPA Platform to a client’s existing ServiceNow instance, using ServiceNow’s public-support APIs. This allows robots to add, delete, and download attachments, as well as pull, update, insert, and delete ServiceNow records. We also leverage connectors that allow users to start and stop automations directly from ServiceNow. Similarly, IBM Maximo’s REST API allows external applications to query and update application data in process automation engines.