the output

SmartResume: AI-Powered Resume Analyzer for HR Teams

🚀 Inspiration

We were inspired by how time-consuming and repetitive resume screening is for HR teams, especially in large organizations receiving hundreds of applications. We wanted to automate this tedious process using AI and serverless cloud infrastructure—giving HR professionals more time to focus on what really matters: people.

💡 What it does

SmartResume is an AI-powered resume analyzer that:

Automatically extracts key information (name, email, skills, and experience) from PDF resumes.
Uses AWS Textract to read resume contents from uploaded PDFs.
Triggers processing when a file is uploaded to an S3 bucket.
Summarizes the candidate’s background using Amazon Bedrock (Claude).
Stores structured resume data into DynamoDB for easy search and future integration.

🛠️ How we built it

We used the following AWS stack:

Amazon S3 – To store uploaded resume files.
Amazon Textract – To extract text from PDFs.
AWS Lambda – To run serverless processing logic.
Amazon Bedrock – To generate professional summaries of resumes.
Amazon DynamoDB – To store structured and searchable resume data.

The entire process is automatically triggered by an S3 upload event.

🧗 Challenges we ran into

Configuring IAM permissions for Bedrock access from Lambda was non-trivial.
Extracting accurate data from unstructured PDF layouts using Textract required experimentation.
Balancing Lambda limits (memory, time, payload size) when invoking foundation models.

🏆 Accomplishments we're proud of

Built a fully serverless resume analyzer that works end-to-end with no manual triggers.
Successfully integrated Claude via Bedrock into a Lambda function.
Built a fast, scalable backend ready for frontend integration.

📚 What we learned

Hands-on experience with AWS Bedrock, Textract, S3, Lambda, and DynamoDB.
How to chain services together with event-driven architecture.
The importance of graceful error handling when working with AI services.