What challenges did King County Assessor's Office face before AI implementation?

Manual processing of diverse paper documents in a high-volume public sector environment caused delays, errors, poor response times, and compliance risks. Understaffing and regulatory compliance added to operational challenges for document processing.

What was the impact of the AI solution?

Substantial reduction in manual data entry and associated errors. Faster, scalable document processing workflows with enhanced data timeliness. Improved constituent service quality and operational transparency. Enabled staff to focus on more meaningful and analytical tasks rather than manual data handling.

Source

Enabling Digital Automation in Intelligent Document Processing (IDP) for Public Sector Partners and Customers Using AWS AI

Use case typeIntelligent document processingUpdated Jun 13, 2026

King County Assessor's Office in Washington faced high document processing delays and errors due to large volumes of diverse paper documents and manual processing constraints. They implemented an intelligent document processing (IDP) automation solution using AWS AI services including Amazon Textract, Amazon Comprehend, Amazon Augmented AI (A2I), AWS Lambda, S3, SQS, Step Functions, API Gateway, and Amazon Kendra to extract, classify, review, and search document data. The automated workflow reduced manual data entry errors, improved processing speed and scalability, enhanced transparency with human-in-the-loop reviews, and enabled staff to focus on higher-value work improving constituent services.

Organization: King County Assessor's Office
Industry: Public Sector
Location: United States
Published: November 2021

Reported outcomes

Strategic outcomes

Cost efficiencyReduced manual data entry and errorsSpeed & agilityFaster, scalable document processing workflowsCustomer experience & trustImproved constituent service qualityEmployee experienceEnabled higher-value analytical work

Primary read

Use case focus

Showing 2 of 2

1Intelligent Document Processing
2Automation

Manual processing of diverse paper documents in a high-volume public sector environment caused delays, errors, poor response times, and compliance risks.
Understaffing and regulatory compliance added to operational challenges for document processing.

Utilized AWS AI services such as Amazon Textract for extracting text/data from varied document types including handwritten and scanned records.
Amazon Comprehend was used for natural language classification and entity extraction.
Amazon Augmented AI (A2I) provided human review workflows for predictions with low confidence.
AWS Lambda, Step Functions, SQS, API Gateway orchestrated secure, scalable workflow integration and notifications.
Amazon Kendra enabled natural language enterprise search of document content and extracted data.

Technologies

Amazon Textract Amazon Comprehend Amazon Augmented AI (A2I)AWS Lambda Amazon Simple Storage Service (S3)Amazon Simple Queue Service (SQS)AWS Step Functions Amazon API Gateway Amazon Kendra

Substantial reduction in manual data entry and associated errors.
Faster, scalable document processing workflows with enhanced data timeliness.
Improved constituent service quality and operational transparency.
Enabled staff to focus on more meaningful and analytical tasks rather than manual data handling.

Architecture

The architecture involves ingestion of documents into an S3 bucket, processing message queues in SQS, invoking Lambda to drive Step Functions workflows that initiate Textract for extraction, Comprehend for classification, A2I for human review, and storing results back for search with Kendra and integration into downstream Records Management Systems.

Implementation partners1

Slalom

Sources & evidence1

Groundedness: 4/5

Primary source

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Customer evidence