Scaled productionEvidence: Medium65/100

Indian Institute of Hotel Management (IIHM): Generative AI for recruitment interviews and learning on Amazon Bedrock

The Indian Institute of Hotel Management (IIHM) worked with Workmates to implement an AWS generative AI solution based on Amazon Bedrock. The platform supports interview management, candidate evaluation, personalized learning content, quizzes, mock tests, and content review. It also uses Amazon Transcribe for speech-to-text and Amazon Textract to digitize and analyze printed or handwritten educational materials. AWS guardrails and evaluation metrics were used to help control output quality and compliance.

Industry
Education
Location
India
Published
May 2026

Reported outcomes

+50%

timeTime & speed

90%accuracy20-30%quantified impact95%accuracy+75%quantified impact

Strategic outcomes

Speed & agilityFaster interview processBetter decisions & insightMore consistent candidate evaluationNew product / capabilityPersonalized learning at scaleRisk & complianceMore secure AI content interaction

Catalog median for time & speed deployments: +60% across 143 reported metrics. Compare benchmarks →

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Time: 50% increase

AWS Customer StoriesMay 27, 2026Customer storyInferred claimMedium evidence strength

50% faster interviews.

Normalized claim

Accuracy: 90%

AWS Customer StoriesMay 27, 2026Customer storyInferred claimMedium evidence strength

90% hiring accuracy.

Normalized claim

Quantified impact: 20-30% increase

AWS Customer StoriesMay 27, 2026Customer storyInferred claimMedium evidence strength

20-30% higher student job placement rates.

Normalized claim

Accuracy: 95%

AWS Customer StoriesMay 27, 2026Customer storyInferred claimMedium evidence strength

95% accuracy in content generation.

Normalized claim

Quantified impact: 75% increase

AWS Customer StoriesMay 27, 2026Customer storyInferred claimMedium evidence strength

75% of educators and students feel more secure interacting with AI-generated content.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
Indian Institute of Hotel Management, IIHM
Provider
AWS
Maturity
Scaled Production

Improve creation and review of educational content and provide personalized learning at scale

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 5

  • 1Interview Automation
  • 2Recruitment
  • 3Content Generation
  • Streamline hospitality recruitment interviews and make candidate evaluation more consistent.
  • Improve creation and review of educational content and provide personalized learning at scale.
  • Support a scalable, secure learning and interview platform as student demand grows.
  • Built a new application platform on AWS with Amazon EC2, Amazon S3, AWS Auto Scaling, IAM, and KMS.
  • Used Amazon Bedrock with Anthropic Claude 3.5 Haiku for chatbot and content generation capabilities, with guardrails for output control.
  • Integrated Amazon Transcribe for interview speech-to-text and Amazon Textract for analyzing educational materials.
  • Deployed Talent Talker and TutorWise workflows for interviews, quizzes, mock tests, and real-time learning engagement.
  • 50% faster interviews.
  • 90% hiring accuracy.
  • 20-30% higher student job placement rates.
  • 95% accuracy in content generation.
  • 75% of educators and students feel more secure interacting with AI-generated content.
Architecture

IIHM built a secure AWS-hosted application platform using Amazon VPC, Amazon EC2, Amazon S3, AWS Auto Scaling, IAM, and KMS. The solution uses Amazon Bedrock with Anthropic Claude 3.5 Haiku, Bedrock guardrails, Amazon Transcribe for interview speech-to-text, and Amazon Textract for document and handwriting extraction. Workmates helped implement the platform, which powers interview management, personalized learning, quizzes, and content review through Talent Talker and TutorWise workflows.

Implementation partners1
Sources & evidence1
Evidence: Medium65/100Evidence strength
  • Customer explicitly identified
  • Deployment status explicitly supported
  • Primary source available
  • Quantified outcome available
  • Technical implementation details available
Type: Customer StoryPublished: May 27, 2026Publisher: AWSEvidence: VendorConfidence: Medium

AI-generated summary. Verify important details with the linked sources before relying on this case.

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