Normalized claim
Time: 95% decrease
Reduced certificate verification time by 95%.
Tenthpin Builds Generative AI Solution for Certificate Verification in Pharmaceutical Manufacturing
Use case typeCompliance automationUpdated Jun 13, 2026
Tenthpin, a life sciences consultancy and product company, faced challenges in improving the accuracy and speed of certificate verification against specification documents for pharmaceutical manufacturing. They developed Tenthpin Intelligent Certificate VerificAItion (T/ICV), a SaaS generative AI solution using Amazon Bedrock foundation models to extract, compare text from certificates and specifications, and automate verification workflows. The solution integrates with SAP Business Technology Platform and uses AWS Lambda for automation and Amazon Aurora as the relational database. T/ICV decreased certificate verification time by 95%, improved accuracy to nearly 100%, reduced onboarding time from months to weeks, and enhanced regulatory compliance risk management.
- Organization
- Tenthpin
- Industry
- Pharma
- Location
- United States
- Published
- April 2026
Reported outcomes
Time: −95%
Time & speed
Catalog median for time & speed deployments: −50% across 295 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Accuracy: 100%
Achieved nearly 100% verification accuracy.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Tenthpin
- Provider
- AWS
- Maturity
- Production
- Linked source
- AWS Solutions Case Studies
Deployed Amazon Aurora for cloud-based relational data storage
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1Document Verification
- 2Compliance Automation
- 3Quality Control
- Built T/ICV on Amazon Bedrock for generative AI foundation models, using automated text extraction and comparison capabilities.
- Implemented workflow automation via AWS Lambda and integrated with SAP Business Technology Platform.
- Deployed Amazon Aurora for cloud-based relational data storage.
- Ensured regulatory compliance and audit logging in a GxP environment.
- Reduced certificate verification time by 95%.
- Improved quality assurance and reduced regulatory compliance risks for pharmaceutical manufacturers.
Architecture
Architecture includes Amazon Bedrock foundation models for natural language processing, AWS Lambda for serverless automation, Amazon Aurora as the relational database, and integration with SAP Business Technology Platform for workflow and approval management.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Case StudyPublished: Apr 29, 2026Publisher: AWS Solutions Case StudiesEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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