Automating repetitive tasks and business workflows frees up a workforce to add value. Automating data analytics changes the field of play, the makeup of team members and overall dynamics. Automatically identifying relationships and patterns in data reduces the reliance on human expertise and judgment while keeping intentionality in the hands of a human actor. This is the essence of augmented intelligence – Using data science to make sense out of large sums of data – in the context of a role (job to be done) deliver outcomes (defined value) that fulfill unmet needs and enable us to do more.
Automate vendor invoice data capture, save manual input effort, and digitize to enable downstream processing and accounts payable automation.
With over 600 vendors (construction sub-contractors), the invoice process was time-consuming and error-prone with manual tasks, data entry, manipulation, and reconciliation. The CFO wanted to automate and turn PDFs and various unstructured documents into usable data.
An AI-powered document extraction service that understands any forms
Automate information extraction customized to any vendor invoice. Applied advanced machine learning to accurately extract text, key-value pairs, tables, and structures from documents. Working with documents that deviate from traditional formats, like industry-specific materials, often requires a custom solution. The custom extraction capabilities of an AI-powered tool help overcome this challenge by training on a company’s data. Learning the structure of invoices to intelligently extract text and data.
Submit documents using a simple REST API. Pull data and organize information with prebuilt and custom features – no manual labeling required. Advanced machine-learning models extract and analyze form fields, text, and tables from documents that include the relationships within the original file and return a structured JSON output. Extracts information quickly, accurately, and tailored to the specific content, without heavy manual intervention or extensive data science expertise.
Turning documents into usable data at a fraction of the time and cost to focus more on acting on the information rather than compiling it. Translating these mined assets into actionable insights for the enterprise eliminates the cost-heavy, and error-prone manual tasks from the workflow, while providing tighter controls, accuracy, and improved straight-through processing.
These actions realize savings on effort, cost, time and reduce wastage. The time saved alone on data entry was equivalent to 1/3 FTE. However, an advantage to this solution is the interoperability and opportunity to deliver further automation. The functionality extends to any document, so it’s fundamental to tackling similar problems in the future and extend to novel challenges as circumstances change.
With the additional downstream accounts payable automation and reduction in management oversight, the fully-loaded costs savings were closer to 1 FTE with a substantial increase in productivity. The payback for this investment was less than six months, with a high ROI gained from ongoing automated operations and more effective OpEx.
The Possibilities are Endless
Unlock value from unstructured documents like texts, images, pdfs, emails, and much more, delivering measurable ROI impact across your enterprise and effective OpEx.
Automate – Template-free data extraction.
Upload invoices, purchase orders, contracts, legal documents, and more. Extract data, catalog/ sort.
Analyze – Document AI with self-learning capabilities.
Analyze unstructured data extract actionable business insights and intelligence with high accuracy.
Act – Integrate with relevant systems; SAP, Quickbooks, RPA & more.
Transform manual, inefficient processes into robust solutions to solve complex business processes & challenges.
Broad Business Application
AI enables organizations to automate non-cognitive tasks, solve complex problems and create systems of insight that deliver contextual business intelligence to the right people at the right time across the entire organization.
If companies want to thrive in the data science and AI era, they must find new ways to compete and address their resourcing gaps.