DocAI Lowers Customer’s Document Processing Cost by 60 Percent. Learn How

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Some of the most important data at your company isn’t living in databases, but in documents, and most business processes begin, involve or end with a document.
Yet most companies are still manually entering data and reliant on guesswork to make sense of it all as the volume and variety of data explodes. Organizations are also leaving heaps of value on the table in the form of new and better customer experiences that can be unlocked with artificial intelligence (AI) applied to documents.
The latest releases of Document (Doc) AI platform, Lending DocAI and Procurement DocAI, built on decades of AI innovation at Google, bring powerful and useful solutions to these challenges. Under the hood are Google’s industry-leading technologies:
- Computer vision (including OCR) and Natural Language Processing (NLP) that creates pre-trained models for high-value, high-volume documents.
- Google Knowledge Graph to validate and enhance the fields in your documents.
- Training and creation of your own custom document models.
- Human interaction with AI to ensure accuracy where needed.
Google Cloud DocAI platform, Lending DocAI and Procurement DocAI are now generally available. Thousands of customers have tried these products in the preview phase—and DocAI has already processed tens of billions of pages of documents across lending, insurance, government and other industries.
“The vast majority of enterprise content still resides in unstructured sources like documents. Google Cloud’s Document AI brings a fresh new perspective to the problem informed by the company’s decades of experience making sense of the largest unstructured corpus in the world—the world wide web.” —Ritu Jyoti, VP of AI Research, IDC
Cut document processing costs by up to 60%
Lending DocAI helps banks, mortgage brokers and other lending institutions fast track the loan application process from weeks to days, dramatically reducing the cost of issuing a loan. And Procurement DocAI enables companies to automate procurement data capture at scale, lowering processing costs by up to 60%.
These solutions are built on DocAI platform, a unified console for document processing that lets you quickly access all parsers and tools. From the platform, you can automate and validate documents to streamline workflows, reduce guesswork, and keep data accurate and compliant.
Get more value from AI with DocAI’s industry-specific solutions
According to Accenture’s AI: Built to Scale report: “Companies that scale successfully see 3x the return on their AI investments compared to those who have not fully rolled out AI capabilities.”
Core to our strategy at Google Cloud is the creation of industry-specific solutions that help companies get maximum value out of their investments in AI. We announced Lending DocAI, our first solution designed specifically for the financial services industry, at the Mortgage Bankers Association convention last year. It processes borrowers’ income and asset documents using a set of specialized machine learning (ML) models, and automates routine document reviews so that mortgage providers can focus on more important work.
Lending DocAI is now generally available and includes more specialized parsers for critical loan documents including paystubs, bank statements, and more. Our goal is to provide the right tools to help borrowers and lenders have a better experience and close home loans faster. For more, watch this video.
Procurement DocAI is also now generally available. This solution helps companies accelerate document processing for invoices, receipts, and other valuable documents in the procurement cycle.
Automating data capture is helping our customers increase accuracy and also lower their procure-to-pay processing costs. We are continually expanding the types of documents Procurement DocAI can process—the latest is a utility parser for electric, water and other bills. In addition, Procurement DocAI leverages Google Knowledge Graph to validate and enrich parsed information to make the data even more useful. Check out this overview video for more details.
One company that lives and breathes AI-enabled document management is AODocs. It uses Procurement DocAI to simplify invoice processing for enterprise customers and launched a new Gmail add-on, Invoice to Sheet, for SMB customers who just want to track their invoices in Google Sheets.
“Google Cloud’s Procurement DocAI service allows our document management platform to better automate the processing of invoices; AODocs customers who have tested our new account payables workflow estimate that the productivity of their A/P team has more than doubled, thanks to the reduction of manual data input brought by the Procurement DocAI.”—Stéphan Donzé, Founder and CEO, AODocs
The new specialized parsers for Lending and Procurement DocAI can be used alongside our existing AutoML Text & Document Classification and AutoML Document Extraction services. These technologies provide a state-of-the-art toolset for creating new document models and have been widely deployed by customers in financial services and other industries.
Partner to accelerate your AI deployment and results
Having the right partner to ease the complexity of rolling out your AI-strategy in mortgage document processing is critical to transforming your customers’ experience. We’re excited to announce a partnership with Mr. Cooper, a leader in mortgage servicing, to provide customers with more automation and workflow tools throughout their entire mortgage life cycle. As part of this agreement, both companies will collaborate on digitizing Mr. Cooper’s core mortgage platform, creating a more personal customer experience utilizing AI, and driving a broader culture of innovation to imagine and develop services and solutions that will transform the mortgage experience for American homeowners.
“Over the last few years, we have made substantial investments in our servicing technology and core mortgage platform that have revolutionized the customer experience, while providing dramatic efficiencies in operating cost. Our partnership with Google Cloud AI will build on those advances and help make these technologies available for the mortgage industry.” —Jay Bray, Chairman and CEO, Mr. Cooper Group
This builds upon the robust partner ecosystem we’re creating to help customers revolutionize the home loan experience, which includes last year’s partnership announcement with Roostify.
Integrate human review into ML predictions
Next up is the general availability of Human-in-the-Loop AI, a new DocAI feature that will help companies achieve higher document processing accuracy with the assurance of human review. Adding human review can increase accuracy and help businesses interpret predictions using purpose-built tools to enable those reviews.
Processing documents quickly and cost-effectively is important. But it’s often necessary to have a high level of assurance on data accuracy for compliance. CIOs and IT decision-makers need highly accurate ML predictions to fulfill compliance requirements, improve employee experience (e.g. less rework), and raise customer satisfaction (e.g. fewer data errors). Including human participation in ML processes allows AI and humans to work together for the best possible results.

Human-in-the-Loop AI provides the workflow to manage human review tasks and produces a percentage confidence score of how “sure” it is that the AI ingested the document correctly. Document AI extracts data from documents with ML, and when paired with Human-in-the-Loop AI, human reviewers are able to verify the data captured. This system is customizable, providing the flexibility to set different thresholds and assign individual groups of reviewers to various stages of the workflow. With Human-in-the-Loop AI, developers can choose trusted reviewers to assign to the task; these reviewers can be from within their own or partner organizations.
More Document AI resources
To learn more, check out the Document AI webpage and watch a demo of how to process sample forms in AI Platform notebooks to inspect data extraction and confidence scores. For more on how customers and partners like Workday, AODocs, and Mr. Cooper are using Document AI, listen to our fireside chat. And stay tuned for the exciting evolution of these technologies in future releases of DocAI.

Google’s Lesson on Leveraging AI and More to Optimize Cloud Value for Innovation
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Google has managed to stay ahead of the curve and demonstrate its ‘growth while staying innovative’ approach using advanced open technologies, AI/ML based analytics solutions, as well as tools for team collaboration and skill development, automation and storage security. Businesses too can achieve the same by deriving maximum value from its people and technology by following Google’s simple guide to stay innovative. Download to learn more.
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Video: How AI is Helping Biologists Protect Wildlife
According to the World Wildlife Fund, vertebrate populations have shrunk an average of 60 percent since the 1970s. And a recent UN global assessment found that we’re at risk of losing one million species to extinction, many of which may become extinct within the next decade.
To better protect wildlife, seven organizations, led by Conservation International, and Google have mapped more than 4.5 million animals in the wild using photos taken from motion-activated cameras known as camera traps. The photos are all part of Wildlife Insights, an AI-enabled, Google Cloud-based platform that streamlines conservation monitoring by speeding up camera trap photo analysis.
With photos and aggregated data available for the world to see, people can change the way protected areas are managed, empower local communities in conservation, and bring the best data closer to conservationists and decision-makers.
Camera traps help researchers assess the health of wildlife species, especially those that are reclusive and rare. Worldwide, biologists and land managers place motion-triggered cameras in forests and wilderness areas to monitor species, snapping millions of photos a year.
But what do you do when you have millions of wildlife selfies to sort through? On top of that, how do you quickly process photos where animals are difficult to find, like when an animal is in the dark or hiding behind a bush? And how do you quickly sort through up to 80 percent of photos that have no wildlife at all because the camera trap was triggered by the elements, like grass blowing in the wind?
Watch this video to find out.

Upgrade Your Contact Center with Knowlarity’s AI-powered Speech Analytics for Higher CX
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Did you know, everyday about 56 million hours worth of phone conversations, equalling to 420 billion spoken words are handled by contact centers? Knowlarity, a renowned cloud business communication service provider with nearly 6,000 customers and over a million virtual users, leverages AI-powered speech analytics that offer insights to gauge customer preferences and emotions, campaign performance, agent’s effectiveness and much more. Knowlarity’s programmatic speech analytics platform is built with Google Cloud to optimize contact center performance by transcribing and analyzing millions of calls to impact savings, operations, CX, customer loyalty and retention, and revenue generation.
Download the e-Book to learn more about Knowlarity’s speech analytics for your business’ contact centers and elevate your agents’ performance by leveraging ML, natural language processing (NLP) and AI capabilities.

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AI has the power to revolutionize every industry—from retail to agriculture, and education to healthcare. Yet many businesses still haven’t begun to adopt AI.
There are a number of factors, including the need for specialized talent and hardware, the right types and quantities of data for training and refining machine learning models, and of course, the broader complexities of introducing a new way of working inside an organization.
But above all, AI can be challenging to apply to very specific business needs.
Google wants to change that, which is why it’s introducing a number of AI solutions aimed at making it easier for businesses to use AI to address many of these specific use cases.
Google’s AI solutions fall into two categories. The first is a set of pre-packaged AI solutions that can be easily integrated into existing workflows. To make these solutions as easy to implement as possible, Google works with popular, trusted enterprise partners who have deep-domain expertise in these workflows.
The majority of Google’s pre-packaged solutions will be delivered through these partners, although it will be offering some
The second category of AI solutions is comprised of reference architectures that businesses can use to create highly-custom AI tools. These require more development work than Google’s pre-packaged
Additionally, businesses can build on these architectures and deploy them to market more quickly, helping your business take advantage of AI, faster.
Learn more about all Google’s AI solutions. Download the whitepaper now!
Leave the Tax Filing to ML: Lending Doc AI’s Automation Classifying and Parsing IT Documents

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In the United States, Tax Season descends upon the country every April, requiring millions of Americans to spend hours deciphering cryptic documents and performing complex math just to figure out what they owe. Wouldn’t it be grand if there was a way for a computer to take all the relevant documents and extract out exactly what the IRS is looking for? Lending Document AI from Google Cloud supports common document types used for Income Tax Filing, such as W-2s and 1099s. These advancements in machine learning technology now makes it possible to alleviate some anxiety leading up to April 15th.
Lending Document AI is a Document Understanding solution that allows for classification and parsing of documents commonly used in the mortgage lending industry. The data in these unstructured files is then converted into a structured format, which can be stored in a database or used for analysis and calculations. You can read more about the product in the announcement blog post. For this tax filing use case, we will focus on automatically classifying and parsing the 2020 editions of the following forms:
W-2
1099-DIV
1099-INT
1099-MISC
1099-NEC
This sample application creates an automated pipeline where the user can bulk upload a collection of PDFs, the Lending Document Splitter & Classifier will classify each document and send each PDF to the appropriate specialized parser to extract the data, which can then be used to calculate an individual tax return and fill out a 1040 Form.
Overview
Let’s explore how this application works. You can check out the sample code in this GitHub Repository.
Here is an outline of the architecture of this application. As you can see, it utilizes Cloud Run and Firestore in Native Mode for the web application in addition to Document AI.

The User uploads multiple PDF files to the web application, hosted on Cloud Run.
An API call is made to the Lending Document Splitter & Classifier for each PDF file.
The output of the classifier (e.g. W-2, 1099-MISC, etc.) is then mapped to an appropriate specialized parser in the Google Cloud Project.
Each document file is sent to the appropriate specialized parser that matches the document type.
The entities are extracted by the parser processor and the data is written to Firestore.
The raw data is now retrieved from Firestore and displayed to the User showing the file classification and extracted values from each form.
The data values from all the forms are used together to calculate an individual income tax return.
The Calculated Tax Rates/Incomes/Deductions are displayed to the User in a Tabular Format matching the IRS Form 1040. The app also displays which form data was used for each field. (Some output fields use values from multiple forms, such as line 25b.)
Step-by-Step directions
Want to try this out for yourself? Here’s how you can deploy and run this application using a Google Cloud Project. You can run this in Cloud Shell (Quickstart) or on your local machine.
NOTE: The Lending Processors in this Demo are in Limited GA as of March 2022. If you have a business use case for these processors, you can fill out and submit the Document AI limited access customer request form.
Install dependencies
- Clone the GitHub Repository to get the sample code.
git clone https://github.com/GoogleCloudPlatform/document-ai-samples.git
- Enter the directory for the tax pipeline demo
cd document-ai-samples/tax-processing-pipeline-python
- Install Python and the Google Cloud SDK if they aren’t already installed.
- Install the python libraries:
pip install -r requirements.txt
- Create a new Google Cloud project, and enable billing if you don’t already have one.
- Enable the Document AI API:
gcloud services enable documentai.googleapis.com
- Setup application default credentials:
gcloud auth application-default login
Deploy demo application
- Edit the config.yaml file, adding your own Project Details docai_processor_location: us # Document AI Processor Location (us OR eu)
docai_project_id: YOUR_PROJECT_ID # Project ID for Document AI Processors
firestore:
collection: tax_demo_documents # Set with your preferred Firestore Collection Name
project_id: YOUR_PROJECT_ID # Project ID for Firestore Database - Run setup scripts to create the processors and Cloud Run app in your project. python3 setup.py
gcloud run deploy tax-demo –source . - Visit the Deployed Web Page (You should get a link from the deployment command)
Calculate Tax Returns Homepage

- Upload Documents. I created some sample documents you can download from the sample-docs folder of the repository.
This demo currently supports the following Document Types (2020 Editions)
W-2
1099-DIV
1099-INT
1099-MISC
1099-NEC
- Click “Upload” Button, wait for processing to complete.
The page will display the steps completed for each document file. These are also written to stdout for troubleshooting purposes.

6. View the extracted values from each file.

7. Click “Calculate Taxes” to see the tax calculation output

Conclusion
Warning: This is NOT financial advice, for educational purposes only.
Congratulations! You now have a fully functional tax processing application that can also be modified for use with other workflows that require data from multiple specialized documents.
The Document AI API is flexible and modular enough that most of the code in this example can be reused for any specialized processor.
Now tax returns can be filed with minimal manual effort!
If you want to learn more about Document AI, check out the Cloud Documentation and these videos:
- Getting started with the Document AI platform
- Process billions of pages and cut operational costs with DocAI
And if you want more hands-on experience, I recommend following these step-by-step codelabs to get started with the key features of Document AI:
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