Normalized claim
Classification and extraction accuracy: 85%
85% classification and extraction accuracy across diverse marketing materials
Competiscan IDP at scale using Amazon Bedrock + Amazon Textract (GenAI IDP Accelerator example)
Use case typeIntelligent document processingUpdated Jun 13, 2026
Competiscan, a competitive marketing intelligence company, needed to process 35,000–45,000 marketing campaigns daily while maintaining a searchable archive of 45 million campaigns spanning 15 years. The article describes the GenAI IDP Accelerator, a serverless document-processing solution on AWS that combines Amazon Bedrock Data Automation, Amazon Textract, and AWS Step Functions for OCR, classification, extraction, validation, and evaluation. Competiscan used the accelerator to automate intelligent document processing for diverse marketing materials and deployed the solution in production in 8 weeks from concept.
- Organization
- Competiscan
- Industry
- Professional Services
- Location
- United States
- Published
- August 2025
Reported outcomes
Daily campaign processing capacity: 35–45 campaigns/day
Productivity & throughput
Daily campaign processing capacity upper bound: 35–45 campaigns/dayArchive size: 45,000,000 campaignsDeployment time: 8 weeks
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Daily campaign processing capacity: 35-45 campaigns/day
handle 35,000–45,000 daily campaigns
Normalized claim
Daily campaign processing capacity upper bound: 35-45 campaigns/day
handle 35,000–45,000 daily campaigns
Normalized claim
Archive size: 45,000,000 campaigns
searchable archive of 45 million campaigns
Normalized claim
Deployment time: 8 weeks
Production deployment in 8 weeks from initial concept
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Competiscan
- Provider
- AWS
- Maturity
- Scaled Production
- Linked source
- AWS Machine Learning Blog
Scaled to handle 35,000–45,000 daily campaigns
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1Intelligent Document Processing
- 2Workflow Automation
- 3Content Classification
- Deployed the GenAI IDP Accelerator on AWS to automate intelligent document processing.
- Used Amazon Bedrock Data Automation and Amazon Textract for OCR, classification, and extraction.
- Ran the workflow in a serverless pipeline with AWS Step Functions and Amazon S3.
- Used evaluation and human review capabilities to improve accuracy and operational control.
Removed critical bottlenecks, facilitating business growth.
Architecture
The solution is a modular, serverless document-processing architecture built on AWS. It uses Amazon Bedrock Data Automation or Bedrock pipeline mode for document understanding and extraction, Amazon Textract for OCR, AWS Step Functions for orchestration, Amazon S3 for storage, and optional human-in-the-loop review, testing, and custom model integration via Lambda hooks.
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Quantified outcome available
- Technical implementation details available
Type: Blog PostPublished: Aug 22, 2025Publisher: AWSEvidence: VendorConfidence: Medium
AI-generated summary. Verify important details with the linked sources before relying on this case.
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