Books, Courses & Certifications

The DIVA logistics agent, powered by Amazon Bedrock

Published

4 days ago

August 7, 2025

Rishi Sareen, Arunraja Karthick, Bakrudeen K

DTDC is India’s leading integrated express logistics provider, operating the largest network of customer access points in the country. DTDC’s technology-driven logistics solutions cater to a wide range of customers across diverse industry verticals, making them a trusted partner in delivering excellence.

DTDC Express Limited receives over 400,000 customer queries each month, ranging from tracking requests to serviceability checks and shipping rates. With such a high volume of shipments, their existing logistics agent, DIVA, was operated on a rigid, guided workflow, forcing users to follow a structured path rather than engaging in natural, dynamic conversations. The lack of flexibility resulted in increased burden on customer support teams, longer resolution times, and poor customer experience.

DTDC was looking for a more flexible, intelligent assistant—one that could understand context, manage complex queries, and improve efficiency while reducing reliance on human agents. To achieve a better customer experience, DTDC decided to enhance DIVA with generative AI using Amazon Bedrock.

ShellKode is an AWS Partner, born-in-the-cloud company specializing in modernization, security, data, generative AI, and machine learning (ML). With a mission to drive transformative growth, ShellKode empowers businesses through state-of-the-art technology solutions that address complex challenges and unlock new opportunities. Using deep industry expertise, they deliver tailored strategies that foster innovation, efficiency, and long-term success in an evolving digital landscape.

In this post, we discuss how DTDC and ShellKode used Amazon Bedrock to build DIVA 2.0, a generative AI-powered logistics agent.

Solution overview

To address the limitations of the existing logistics agent, ShellKode built an advanced agentic assistant using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and an API integration layer.

When customers interact with DIVA 2.0, they experience a seamless, conversational interface that understands and responds to their queries naturally. Whether tracking a package, checking shipping rates, or inquiring about service availability, users can ask questions in their own words without following a rigid script. DIVA 2.0’s enhanced AI capabilities allow it to understand context, manage complex requests, and provide accurate, personalized responses, significantly improving the overall customer experience and reducing the need for human intervention. The following high-level architecture diagram illustrates the application flow and the solution architecture with AWS services.

The DTDC logistics agent is designed using a modular and scalable architecture to provide seamless integration and high performance. This streamlined workflow demonstrates how a generative AI-powered serverless logistics agent using AWS App Runner, Amazon Bedrock Agents, AWS Lambda, and a vector-based knowledge base handles user queries ranging from tracking requests to serviceability checks and shipping rates intelligently and efficiently.

The logistics agent is hosted as a static website using Amazon CloudFront and Amazon Simple Storage Service (Amazon S3). The logistics agent is integrated with the DTDC website, which provides an intuitive and user-friendly interface for end-user interactions (see the following screenshot).

An end-user accesses the logistics agent through the DTDC website and submits queries like tracking shipments, checking service availability, calculating shipping rates, FAQs, and so on using natural language.The user requests are processed by App Runner, which helps run the web application (including API services, backend web services, and websites) on AWS. App Runner is hosted with multiple API services, such as the Amazon Bedrock Agents API and Dashboard API. App Runner initiates the Amazon Bedrock Agents API based on the user requests.

Amazon Bedrock is a fully managed service that offers a choice of industry leading foundation models (FMs) along with a broad set of capabilities to build generative AI applications, simplifying development with security, privacy, and responsible AI. With Amazon Bedrock, your content is not used to improve the base models and is not shared with any model providers. Amazon Bedrock Guardrails provides configurable safeguards to help safely build generative AI applications at scale. To learn more, see Build safe and responsible generative AI applications with guardrails. AWS Identity and Access Management (IAM) helps administrators securely control who can be authenticated and authorized to use Amazon Bedrock resources.

The Amazon Bedrock agents are configured in Amazon Bedrock. An Amazon Bedrock agent receives the request and interprets the user’s intent using its natural language understanding capabilities. Based on the interpreted intent, the agent triggers an appropriate Lambda function, such as:

Tracking consignments
Pricing information
Location serviceability check
Support ticket creation

The triggered Lambda function calls the following client APIs, retrieves the relevant data, and returns the response to the agent:

Tracking System API – Retrieves real-time status and provides updates on consignment shipment tracking
Delivery Franchise Location API – Checks the service availability to deliver the parcels between the locations
Pricing System API – Calculates the shipping rates based on shipment details provided by the user
Customer Care API – Creates a support ticket for the end-users

The agent passes the response to the large language model (LLM), in this case Anthropic’s Claude 3.0 on Amazon Bedrock, which understands the context of the retrieved data, processes it, and generates a meaningful response for the user.

The knowledge base contains web-scraped content from the DTDC website, internal support documentation, FAQs, and operational data, enabling real-time updates and accurate responses. The knowledge base contents are stored as vector embeddings in Amazon OpenSearch Service, providing quick and relevant responses. For general queries, the logistics agent fetches information from Amazon Bedrock Knowledge Bases, providing accuracy and relevance. Using semantic similarity search, relevant chunks of information are retrieved from the knowledge base based on the user’s query, which Amazon Bedrock then uses to generate a context-aware response. If no relevant data is found in the knowledge base, a fallback response (preconfigured in the Amazon Bedrock prompt) is returned, indicating that the system couldn’t assist with the request.

The logistics agent queries and associated responses are stored in Amazon Relational Database Service (Amazon RDS) for PostgreSQL for enhanced scalability and relational data handling. App Runners initiates the Dashboard API call to update the queries and associated responses in Amazon RDS. We discuss this in more detail the following section.

Throughout the process, Amazon CloudWatch Logs captures key events such as intent recognition, Lambda invocations, API responses, and fallback triggers for auditing and system monitoring. AWS CloudTrail records and monitors activity in the AWS account, including actions taken by users, roles, or AWS services. It logs these events, which can be used for operational auditing, governance, and compliance.

Amazon GuardDuty is a threat detection service that continuously monitors, analyzes, and processes AWS data sources and logs in your AWS environment. GuardDuty uses threat intelligence feeds, such as lists of malicious IP addresses and domains, file hashes, and ML models to identify suspicious and potentially malicious activity in the AWS environment.

Logistics agent dashboard

The following high-level architecture diagram illustrates the logistics agent dashboard, which captures the end-user interactions and its associated responses.

The logistics agent dashboard is hosted as a static website using CloudFront and Amazon S3. Dashboard access is allowed only for the DTDC admin team.

The dashboard is populated through API calls using Amazon API Gateway with Lambda as a backend, which retrieves the dashboard data from Amazon RDS for PostgreSQL.

The dashboard provides real-time insights into the logistics agent performance, including accuracy, unresolved queries, query categories, session statistics, and user interaction data (see the following screenshot). It provides actionable insights with features such as heat maps, pie charts, and session logs. Real-time data is logged and analyzed on the dashboard, enabling continuous improvement and quick issue resolution.

Solution challenges and benefits

When implementing DIVA 2.0, DTDC and ShellKode faced several significant challenges. Integrating real-time data from multiple legacy systems was crucial for providing accurate, up-to-date information on tracking, rates, and serviceability. This was likely addressed through the robust API integration capabilities of Amazon Bedrock Agents. Another major hurdle was training the AI to understand complex logistics terminology and multi-step queries, which was overcome by using Amazon Bedrock LLMs and Amazon Bedrock Knowledge Bases, fine-tuned with industry-specific data. The team also had to navigate the delicate process of transitioning from the old rigid DIVA system while maintaining service continuity and preserving historical data, potentially employing a phased approach with parallel systems. Finally, scaling the solution to handle over 400,000 monthly queries while maintaining performance was a significant challenge, addressed by using the cloud infrastructure of Amazon Bedrock Agents for optimal scalability and performance. These challenges underscore the complexity of upgrading to an AI-powered system in a high-volume, data-intensive industry like logistics, and highlight how AWS solutions provided the necessary tools to overcome these obstacles. DTDC realized the following benefits from powering the logistics agent with generative AI using Amazon Bedrock:

Enhanced conversations and real-time data access with customer support agents – Powered by Amazon Bedrock Agents, the solution improves natural language understanding, enabling more fluid and engaging conversations. With multi-step reasoning, it can handle a broader range of queries with greater accuracy. Additionally, by integrating seamlessly with DTDC’s API layer, the logistics agent provides real-time access to vital information, such as tracking shipments, service availability, and calculating shipping rates. The combination of advanced conversational capabilities and real-time data provides fast, accurate, and contextually relevant responses.
Intelligent data processing and accurate FAQ responses – For complex queries, the logistics agent uses LLM technology to process raw data and deliver structured, tailored responses. This makes sure users get clear, actionable insights. For frequently asked questions, the logistics agent uses Amazon Bedrock Knowledge Bases to deliver precise answers without requiring human support, reducing wait times and enhancing the overall user experience.
Reduced live agent dependency and continuous improvement – Although the logistics agent hasn’t eliminated the need for customer support, the number of queries handled by the customer support team has reduced by 51.4%. The system provides valuable insights into key performance metrics like peak query times, unresolved issues, and overall engagement through integrated real-time analytics, helping refine and improve the assistant’s capabilities over time.

Results

The generative AI-powered logistics agent has reduced the burden on customer support teams and shortened resolution times, resulting in better customer experience:

Powered by Amazon Bedrock, DIVA 2.0 understands queries in natural language and supports dynamic conversations with a response accuracy of 93%
Based on the last 3 months of dashboard metrics data, they observed the following:
- 71% of the inquiries were related to consignments (256,048), whereas 29.5% were general inquiries (107,132)
- 51.4% of consignment inquiries (131,530) didn’t result in a support ticket, whereas 48.6% (124,518) led to new support ticket creation
- Of the inquiries that resulted in tickets, 40% started with the customer support center before moving to the AI assistant, whereas 60% began with the assistant before involving the customer support center

DIVA 2.0 has reduced the number of queries handled by the customer support team by 51.4%. DTDC’s support team can now focus on more critical issues, improving overall efficiency.

Summary

This post demonstrated how Amazon Bedrock can transform a traditional chatbot to a generative AI-powered logistics agent that provides better customer experience through dynamic conversation. For businesses facing similar challenges, this solution offers a blueprint for modernizing your AI assistant while maintaining compliance with industry standards.

To learn more about this AWS solution, contact AWS for further assistance. AWS can provide detailed information about implementation, pricing, and how to tailor the solution to your specific business needs.

About the authors

Rishi Sareen – Chief Information Officer (CIO), DTDC is a seasoned technology leader with over two decades of experience in driving digital transformation, enterprise IT strategy, and innovation across the logistics and supply chain sector. He specializes in building agile, AI-driven, and secure technology ecosystems that enhance operational efficiency and customer experience. Rishi leads initiatives spanning system modernization, data intelligence, automation, cybersecurity, cloud, and artificial intelligence. He is deeply committed to aligning technology with business outcomes while fostering a culture of continuous improvement and purposeful innovation. A strong advocate for people-centric leadership, Rishi places high emphasis on nurturing talent, building high-performing teams, and mentoring future-ready technology leaders who can thrive in dynamic, AI-powered environments. Known for his strategic vision and disciplined execution, he has led large-scale digital initiatives and transformation programs that deliver lasting business impact.

Arunraja Karthick – Head – IT Services & Security (CISO), DTDC is a strategic IT and cybersecurity leader with over 15 years of experience driving enterprise-scale digital transformation. As the Head of IT Services & Security (CISO) at DTDC Express Limited, he leads the organization’s core IT, cloud, and security programs—transforming legacy environments into agile, secure, and cloud-native ecosystems. Under his leadership, DTDC has adopted a hybrid cloud architecture spanning AWS, GCP, and on-prem colocation, with a vision to enable dynamic workload mobility and vendor-neutral scalability. Arunraja has led critical modernization efforts, including the migration of key business applications to microservices and containerized platforms, while ensuring high availability and regulatory compliance. Known for his deep technical insight and execution discipline, he has implemented enterprise-wide cybersecurity frameworks—from Email DLP, Mobile Device Management, and Conditional Access to Hybrid WAF and advanced SOC operations. He has also championed secure access transformation through Zero Trust-aligned Secure WebVPN, redefining how internal users access corporate apps. Arunraja’s leadership is grounded in platform thinking, automation, and a user-first mindset. His recent initiatives include the enterprise rollout of GenAI copilots for customer experience and operations, as well as unified policy-based DLP and content control mechanisms across endpoints and cloud. Recognized as an Influential Technology Leader, Arunraja continues to challenge conventional IT boundaries—aligning security, agility, and innovation to power business evolution.

Bakrudeen K an AWS Ambassador, leads the AI/ML practice at Shellkode, focusing on driving innovation in artificial intelligence, especially in Generative AI. He plays a key role in building teams and advanced AI solutions, Agentic Assistants, and other next-gen technologies. Bakrudeen has made notable contributions to AI/ML research and development. In 2023 and 2024, he received the Generative AI Consulting Excellence Partner Award at the AI Conclave and the Social Impact Partner of the Year Award for Generative AI at AWS re:Invent 2024, both on behalf of Shellkode reflecting the team’s strong commitment to innovation and impact in the AI space.

Suresh Kanniappan is a Solutions Architect at AWS, handling Automotive, Manufacturing and Logistics enterprises in India. He is passionate about cloud security and Industry solutions that can solve real world problems. Prior to AWS, he worked for AWS customers and partners in consulting, migration and solution architecture roles for over 14 years.

Sid Chandilya is a Sr. Customer Relations Manager at AWS, responsible for tech led business transformation with Automotive, Manufacturing and Logistics enterprises in India. Sid is peculiarly passionate about challenging status quos, building a joint “Think Big” vision with customer CXOs and leveraging Ai infused tech to accelerate outcomes. He is known for his deep understanding of industry imperatives (working backward from customer) and translating the business pain points into tech solution.

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Books, Courses & Certifications

In a System That Wasn’t Built for Me, My Students Help Me Stay

Published

3 hours ago

August 11, 2025

Yolanda Wiggins

Academia is a high-stress, high-surveillance environment. Faculty are asked to do more with less: more students, more reporting, more unpaid labor — and less time, less support, and less say in decisions that shape our work. For many of us, the job has become a constant negotiation between our values and institutional priorities.

And yet, I stay. Not for the salary. Not for the endless meetings or initiatives that depend on faculty labor but often move forward without our input. I stay because of my students. They are the reason I continue to show up.

At the California State University where I teach, my students come from a wide range of racial, cultural and economic backgrounds. Many are the first in their families to attend college. Few have had Black professors before. And I am one of very few Black faculty on campus.

Yolanda Wiggins

It can be isolating. I attend meetings where no one else looks like me. I navigate policies that were not built with people like me in mind. Even well-intentioned efforts to foster belonging often feel top-down or disconnected from the everyday realities of teaching, mentoring and being visible.

But my students — across all backgrounds — support me in ways they may not even realize. It’s in the way they show up, engage with material, trust me with their stories, or quietly ask, “How are you doing?” They remind me: when Black professors are in the classroom, everyone benefits.

They understand that representation is about more than role models for Black students. It expands perspectives, deepens classroom trust, and allows for more honest, critical dialogue. Our presence in the academy challenges the status quo and makes space for voices that are too often ignored.

They are not my formal support system, but they are my community.

In a profession where recognition is rare and burnout is high, a thank-you note, a hallway chat, or a class conversation that sparks something real can carry me through weeks of feeling invisible in faculty spaces. My students remind me that this work — when stripped of the bureaucracy — still matters.

To be sure, students should never be expected to carry the emotional weight of supporting their professors. That is not their role. The gratitude I feel does not excuse the broader shortcomings of higher education. It simply underscores how powerful our relationships can be in the face of institutional neglect.

But universities must do more than celebrate diversity on their brochures. If they truly care about faculty success — especially for faculty of color — they need to listen to students. Students see us more than any task force or strategic plan. They witness our labor and our care firsthand.

Institutions should partner with students to co-create strategies for retaining faculty of color. That means going beyond traditional evaluations to foster real conversations about campus climate, mentorship and visibility. It means funding student-led efforts that recognize and uplift faculty who teach and build community — the very labor that fuels student success but often goes unrewarded.

Universities should also rethink what support looks like outside of formal structures. Sometimes what faculty need is not another committee, but a space to gather, breathe and feel seen. Student organizations often model this well. They create spaces that are joyful, inclusive and rooted in mutual care. Faculty can benefit from those spaces too — not as authority figures, but as participants in a shared community.

Creating sustainable change in higher education doesn’t require reinventing the wheel. It requires valuing the relationships already happening on campuses every day. When students trust their professors, when faculty show up with care, when conversations extend beyond grades and the syllabus — those are the moments that build true community.

Academia doesn’t always recognize our full contributions. And for those of us at the intersections of race, gender and class, it can be especially isolating. But my students remind me every day that I belong — not just because I teach, but because I matter. That, more than anything, is why I keep going.

This isn’t just about one professor’s experience. It’s a reminder to higher-ed leaders, policymakers and educators that student-faculty relationships are powerful levers for change. If we want to build inclusive, thriving campuses, we must center the people who are already doing the work of belonging — even when no one is watching.

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Books, Courses & Certifications

5 Free Courses And Certificates To Put On Your Resume In 2025

Published

3 days ago

August 8, 2025

Rachel Wells

A course or certificate, even if in progress and not completed yet, can make all the difference between getting hired for your dream job and being passed off for another candidate

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An estimated 97% of employers are currently using, or about to implement, skills-based hiring, according to Coursera’s latest report.

That’s a significant 20% leap from 2023, when skills-based hiring was increasingly becoming a buzzword in HR circles, with the U.S. Department of Labor releasing recommendations and a guidebook for skills-based hiring a year later.

5 Free Courses And Career Certificates To Include In Your Resume

Short online courses and certificates are some of the best ways to demonstrate your skills and suitability, not just for the job, but also for the company culture, especially if it thrives on a growth mindset.

Here are some free courses and certificates you can study today and add to your resume to boost your chances of being hired (and help you negotiate for higher pay too):

1. Free Social Media Marketing Certification Course: Get Certified In Social Media Strategy

Free, by HubSpot Academy
Perfect for small business owners, marketing managers, and content creators/freelancers
Total completion time is five hours and 18 minutes

2. Data Landscape Of GenAI For Project Managers

Free for PMI members, by PMI (Project Management Institute)
Perfect if you’re already a project management professional
Total course length is five hours

(You can find other free beginner-friendly Gen AI courses here in my recent article.)

3. Practical Application Of Generative AI For Project Managers

Free, by PMI
Suitable for new and existing project management professionals
Total course length is five hours

4. IBM: Data Analytics Basics For Everyone Free Course

Free if you select the audit option, on edX
Perfect for beginners
You can gain a certificate, but only if you take the paid option; otherwise you can complete this for free
Takes approximately five weeks at three hours a week to complete

5. Getting Started With Python for Data Science, by Codeacademy

Free course by Codecademy
Includes three hands-on projects to flex your skills and demonstrate your knowledge
Is suitable for beginners

Is A Career Certificate Worth It?

Here are some other reasons why studying a course or career certificate is absolutely essential if you’re seeking to land a promotion, salary premium, high-paying client projects, or get hired faster:

About 96% of the 1,000 employers surveyed for the report indicate that a job candidate having a course or certificate on their resume strengthens their application and boosts their chances of being hired, up from 88% two years ago.
In the U.S. and Canada, 90% of employers say they’d offer a higher starting salary to candidates who’ve completed certificates and short courses.
Nearly a third of entry-level professionals who studied a course or certificate in the past year secured a salary raise.
An estimated 21% earned a promotion as a direct result of studying courses and certificates

(These stats are taken from Coursera’s Microcredentials Report 2025.)

I know from first-hand experience that studying an online course makes it easier to get hired faster.

In 2022, I was interviewed for a project management role that was a stretch outside of my comfort zone.

When it came time for the dreaded but much-anticipated interview question, “Tell us about one of your weaknesses,” I took this as an opportunity to relate one of my “weak” areas in project management, but then anchored my answer by sharing that I was currently studying the Google Career Certificate in Project Management (at the time this was free due to financial aid offered on Coursera).

I was hired that same day.

My manager later confided to me that even though I had less experiences than other candidates, this very detail (the course I was studying) was the deciding factor that made her take a bet on me and hire me for the job, because I had proven that I had a growth mindset and clearly had freshly updated skills that could be put to use in the role.

So yes, free online courses with certificates are absolutely worth it.

Where Can I Find Free Online Courses And Certificates?

Choose one free online course or certification from the list above, or find another one that’s more relevant to your career goals. You can find free online courses with certificates (and without certificates) from platforms like:

LinkedIn Learning (free to Premium members)
Codecademy
Great Learning
Alison
edX
IBM SkillsBuild
Microsoft Learn
HubSpot

And many more are just a tap away.

Once you’ve started, be consistent. Block out some time every week to study and practice, and share what you’re learning on LinkedIn. You can also add your course or certificate to your resume and include a progress note, like “currently studying,” or “due to complete by October 2025.” This is a positive sign to employers that you’re actively building yourself professionally, and it encourages them to invite you for interviews and offer you job and promotion opportunities.

About 97% of employers are adopting skills-based hiring, which means certificates are in greater demand than degrees

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You’re just a few weeks away from changing your entire career and income trajectory.

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Books, Courses & Certifications

Get AI Certified With edX

Published

3 days ago

August 8, 2025

Sue G

edX is again offering a discount of up to 30% on selected courses and program bundles until September 10th. Since AI is currently the hot topic we look at what is on offer.

Disclosure: When you make a purchase having followed a link to from this article, we may earn an affiliate commission.

Billed as the Top AI Program on edX, the Oxford Artificial Intelligence Programme is offered through the University of Oxford’s Saïd Business School. The current session started on August 6th and is open to late registrations until August 11th.

Offered in its Executive Education category, and thus and is included in the offer, the program is designed to provide a comprehensive understanding of AI for a diverse professional audience and there are no prerequisites. It consists of a welcome orientation module followed by six weekly modules that are released sequentially. Each module is estimated to take 7–10 hours per week. The curriculum covers a range of topics, from foundational concepts to real-world business applications and ethical considerations.

Module 1: Artificial Intelligence Ecosystem – Explores the history of AI and its place within the broader digital ecosystem.

Module 2: AI and Machine Learning – Delves into the mechanics of machine learning, including supervised, unsupervised, and reinforcement learning.

Module 3: Deep Learning and Neural Networks – Understands the function of deep learning and neural networks.

Module 4: Working with Intelligent Machines – Examines the impact of AI on the workforce and the concept of machine intelligence.

Module 5: The Ethics of Artificial Intelligence – Discusses the ethical, legal, and regulatory aspects of AI.

Module 6: How to Drive AI in Your Business – Focuses on identifying business opportunities for AI and building a business case for its implementation.

Upon successful completion, participants are expected to be able to:

Evaluate the potential impact of AI on their industry and develop a business case for its adoption.

Establish a framework for critically analyzing the social and ethical implications of AI.

Gain a conceptual understanding of machine learning, deep learning, and neural networks.

Receive a certificate of attendance from the Saïd Business School, University of Oxford.

Join the official Oxford Executive Education Alumni group on LinkedIn.

As already mentioned this programme is for business professionals. If you are a professional developer IBM now has a new microcredential, IBM:AI Developer starting on October 15th but still in the offer as long as you register by September 10th.

The six-week course consists of a welcome orientation module followed by six weekly modules estimated to take 10-12 hours per week:

Module 1: Introduction to AI, GenAI, and Prompt Engineering

Module 2: Introduction to Web Development

Module 3: Using Python for Data Science

Module 4: Python Fundamentals and Data

Module 5: Python Coding Practices and Web Application Development

Module 6: Capstone Project: Develop AI Applications Using Python

Over six weeks, participants will learn the building blocks of AI development while honing real-world job-ready skills that include:

Using Python, HTML, CSS, and JavaScript for web and software development

Applying Python programming fundamentals to collect data and drive business solutions

Creating and deploying web applications using Flask

Building generative AI applications using Python

Assessment is continuous and based on a series of practical assignments completed online.

edXIBM

The existing IBM Applied AI Developer Professional Certificate, comprising 7 courses over 6 months and the Generative AI Engineering Professional Certificate also from IBM and comprising 16 courses over 13 months, both of which are described in AI At edX With 30% Savings are also encompassed by the offer as long as you enroll in the full programs without any other discounts.

And of course edX Professional Certificates that we’ve previously explored in Brand New Data Science Courses on edX, Gain A Python Professional Certificate From edX and other articles are also part of the edX Back to School offer that runs until September 10, with the code SKILLSEDX25.