From Paperwork Mountains to Digital Freedom: Building an IDP Solution with Kiro

Challenge: Office Staff Drowning in Paperwork

Every morning, Mai arrives at the government office where she works. Her desk is already piled high with paper documents - citizen applications, official reports, meeting minutes, and forms that need to be digitized.

Like thousan...

Challenge: Office Staff Drowning in Paperwork

Like thousands of office workers, Mai faces an exhausting daily routine:

💢Type for hours: Manually transcribing each document into Word
💢 Hunt for errors: Reviewing for typos and formatting mistakes
😫 Work overtime: Staying late to finish the backlog
😫 Feel exhausted: Repeating the same tedious task every single day

A single 5-page official document takes 30-45 minutes to transcribe. With dozens arriving daily, Mai is overwhelmed.

What if there was a better way?

The Vision: AI-Powered Document Processing

I wanted to build a solution where office staff could:

Take photos with their smartphone camera
Wait 30 seconds while AI processes them
Download perfectly formatted Word documents
Done! Ready to review and distribute

But I had a problem: I didn't know where to start.

How do I use AWS Bedrock for OCR?
How do I create properly formatted Word documents?
How do I preserve Vietnamese document headers?
How do I build a web interface?
How do I deploy on AWS?

That's when I turned to Kiro — my AI coding assistant.

Building with Kiro: The Journey

Step 1: The Initial Request

I started with a simple question to Kiro:

Me: "Given the AWS Bedrock Converse API and Claude Sonnet 4, build an AI solution to OCR images from a folder and convert them to Word DOCX files. Prefer Python. Search the internet for references."

Kiro immediately got to work:

Within minutes, Kiro had:

Fetched AWS Bedrock Converse API documentation
Researched python-docx library
Created complete project structure
Generated working code

Step 2: Fine-Tuning for Vietnamese Documents

The first version worked, but Vietnamese official documents have a special two-column header format that wasn't captured correctly.

My Request:

Me: "The phrase 'CỘNG HÒA XÃ HỘI CHỦ NGHĨA VIỆT NAM' should be in a table with two columns. Left column has organization info, right column has the country header and date."

Kiro's Response:

Kiro immediately:

Updated the OCR prompt to detect two-column headers
Modified create_docx.py to parse structured markup
Created borderless tables for proper formatting
Tested the changes automatically

# Kiro's clever solution - Structured OCR prompt
STRUCTURED_OCR_PROMPT = """
For Vietnamese official document headers with two columns, output as:
[HEADER_TABLE]
[LEFT]
organization line 1
organization line 2
Số: xx /TB-xxx
[/LEFT]
[RIGHT]
CỘNG HÒA XÃ HỘI CHỦ NGHĨA VIỆT NAM
Độc lập - Tự do - Hạnh phúc  
Tp. xxx, ngày xx tháng xx năm xxxx
[/RIGHT]
[/HEADER_TABLE]
"""

Result: Perfect two-column headers!

Step 3: Intelligent Multi-Page Grouping

I wanted images with similar names (doc-1.png, doc-2.png) to be combined into one Word file (doc.docx).

My Request:

Me: "If images have names with the same prefix but different numbers after a hyphen (e.g. tb-1, tb-2), group them into one DOCX file (e.g. named 'tb') with multiple pages."

Kiro's Implementation:

Kiro created a smart filename parser:

def get_prefix_and_page(filename: str) -> tuple:
    """
    Extract prefix and page number from filename.
    Examples:
        'invoice-1.png' -> ('invoice', 1)
        'report_2.jpg' -> ('report', 2)
        'standalone.png' -> ('standalone', 0)
    """
    stem = Path(filename).stem
    match = re.match(r'^(.+?)[-_](\d+)$', stem)
<span class="k">if</span> <span class="n">match</span><span class="p">:</span>
    <span class="k">return</span> <span class="n">match</span><span class="p">.</span><span class="nf">group</span><span class="p">(</span><span class="mi">1</span><span class="p">),</span> <span class="nf">int</span><span class="p">(</span><span class="n">match</span><span class="p">.</span><span class="nf">group</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span>
<span class="k">return</span> <span class="n">stem</span><span class="p">,</span> <span class="mi">0</span>

Result: Automatic multi-page document creation!

Step 4: Building the Web Interface

Manual CLI was working, but I needed a user-friendly web interface.

My Request:

Me: "Deploy a website that accepts image uploads, stores them in a S3 bucket, processes with Bedrock, outputs DOCX files, and provides download links."

Kiro's Response:

Within minutes, Kiro built:

Complete Flask web application
Drag & drop upload interface
S3 integration for storage
Session management for multi-user support
Download functionality with presigned URLs
HTML templates

@app.route('/upload', methods=['POST'])
def upload_files():
    """Handle file upload and processing"""
    files = request.files.getlist('files')
    session_id = str(uuid.uuid4())[:8]
<span class="c1"># Upload to S3

    for file in files:
s3_key = f“images/{session_id}/{filename}”
s3_client.upload_file(local_path, S3_BUCKET, s3_key)
    <span class="c1"># OCR with Bedrock

        text = ocr_image_with_bedrock(local_path)
ocr_results[filename] = text
<span class="c1"># Create grouped DOCX files

    create_grouped_documents(ocr_results)

Step 5: UI/UX Enhancement

The first UI worked but looked basic. I wanted something modern.

My Request:

Me: "The dashboard icons and colors look unacceptable. Search for modern color schemes and upgrade the UI."

Kiro transformed the interface with:

Modern dark theme with purple/blue gradients
Glassmorphism effects on cards
Animated background patterns
Mobile-responsive design
Success animations for feedback

/* Kiro's modern design system */
:root {
    --primary: #6366f1;
    --secondary: #0ea5e9;
    --accent: #8b5cf6;
    --gradient: linear-gradient(135deg, #6366f1 0%, #8b5cf6 50%, #0ea5e9 100%);
}

Result: Beautiful professional interface!

You can upload 2 image files with naming convention such as - and click Convert to DOCX.

It will take a while, around 1 minute to complete.

Demo

Please watch this demo at https://haianh-sing.s3.ap-southeast-1.amazonaws.com/2026-01-06+21-56-16.mp4.

What We Built Together

After working with Kiro for just 1 hour, we had a complete, production-ready Intelligent Document Processing platform that would have taken days to build manually.

The Power of AI-Assisted Development

Features Kiro Built

AI-Powered OCR: Claude Sonnet 4 with 95%+ accuracy
Mobile-First: Works with any smartphone camera
Vietnamese Support: Preserves official document formatting
Multi-Page: Automatic grouping by filename
Web Interface: Beautiful, responsive dark theme design
Cloud-Native: AWS S3, Bedrock, EC2 Graviton (ARM64)
Secure: IAM roles with least-privilege access
Cost-Effective: $0.003 per page
Production-Ready: Deployed to AWS with monitoring

Getting Started: Deploy Your Own System

Prerequisites

AWS Account Setup:

AWS Account with Bedrock access in us-west-2
Enable Claude Sonnet 4 model in Bedrock console
Create IAM user with admin access (for initial setup)

Local Development:

Python 3.9 or higher installed
AWS CLI configured (aws configure)
Git installed

Quick Start (5 Minutes)

Deployment on EC2

Step 1: Create IAM Role

# Create role with trust policy aws iam create-role \ --role-name Image2Docx-EC2-Role \ --assume-role-policy-document file://iam-trust-policy.json # Attach permissions policy aws iam put-role-policy –role-name Image2Docx-EC2-Role –policy-name Image2Docx-Policy –policy-document file://iam-policy.json # Create instance profile aws iam create-instance-profile –instance-profile-name Image2Docx-EC2-Profile

# Add role to profile aws iam add-role-to-instance-profile –instance-profile-name Image2Docx-EC2-Profile –role-name Image2Docx-EC2-Role

Step 2: Launch EC2 Instance

# Launch Graviton instance (ARM64 - cost efficient)
aws ec2 run-instances \
    --image-id ami-xxxxxxxxx \  # Amazon Linux 2023 ARM64
    --instance-type t4g.micro \
    --key-name your-key-pair \
    --security-group-ids sg-xxxxxxxxx \
    --iam-instance-profile Name=Image2Docx-EC2-Profile \
    --tag-specifications 'ResourceType=instance,Tags=[{Key=Name,Value=Image2Docx-Server}]'

Step 3: Configure Security Group

# Allow inbound HTTP on port 8080 aws ec2 authorize-security-group-ingress \ --group-id sg-xxxxxxxxx \ --protocol tcp \ --port 8080 \ --cidr 0.0.0.0/0

# Allow SSH for administration aws ec2 authorize-security-group-ingress –group-id sg-xxxxxxxxx –protocol tcp –port 22 –cidr your-ip-address/32

Step 4: Deploy Application

# SSH to instance ssh -i "your-key.pem" ec2-user@<EC2-PUBLIC-IP> # Update system sudo yum update -y # Install dependencies sudo yum install -y git python3-pip # Clone repository git clone https://github.com/PNg-HA/Image2Docx.git cd Image2Docx # Install Python packages pip3 install -r requirements.txt # Run application in background nohup python3 app.py > app.log 2>&1 &

Step 5: Access Your Application

Open browser and navigate to:

http://<EC2-PUBLIC-IP>:8080

Success! Your intelligent documentation platform is live.

Conclusion: From Vision to Reality in 1 Hour with Kiro

We started with a simple question: "Can we help office staff escape the paperwork trap?"

The answer is a resounding YES. But what's even more remarkable is HOW we did it.

This platform is my contribution to eliminating paperwork drudgery and freeing office workers. But more importantly, this project proves that anyone with vision and AI assistance can build transformative solutions.

What will you build with Kiro?

Challenge: Office Staff Drowning in Paperwork

Challenge: Office Staff Drowning in Paperwork

The Vision: AI-Powered Document Processing

Building with Kiro: The Journey

Step 1: The Initial Request

Step 2: Fine-Tuning for Vietnamese Documents

Step 3: Intelligent Multi-Page Grouping

Step 4: Building the Web Interface

Step 5: UI/UX Enhancement

Demo

What We Built Together

The Power of AI-Assisted Development

Features Kiro Built

Getting Started: Deploy Your Own System

Prerequisites

Quick Start (5 Minutes)

Deployment on EC2

Conclusion: From Vision to Reality in 1 Hour with Kiro

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