Save Time and Cost with Generative AI and RAG - for SMEs

Imagine if your small business could access the same insights and tools as corporate giants. That’s exactly what Retrieval Augmented Generation (RAG) and tools like AlfredAI are making possible, and at Palantir Consulting , we’re seeing the impact firsthand. With RAG, we’re breaking down barriers, enhancing our customer experience, and making more informed decisions faster than ever.

#ShoryuWill Newsletter #30 By William Zhang

Click below to Listen to this Newsletter Edition??

In case you missed previous Editions:

The 66 AI Tools I Have Tried That Save Me Thousands of Dollars a Month

AI Now Controls Your Desktop - Directly

Top Lessons I have learnt from some of Australia's High Performing Companies

What This Edition Will Cover:

• What RAG Is and How It Differs from Other AI Models: A straightforward breakdown of RAG and what makes it unique.
• Why RAG and AI Matter for SMBs: How these tools give small businesses the competitive edge in insight, content, and decision-making.
• Real-World Applications: RAG at Palantir Consulting: A look at how we’re using RAG and AlfredAI to drive efficiency, streamline operations, and support growth.
• Mindset Shift and AI Tools to Help You Get Started
• 3 Book Recommendations to build your understanding and drive your business forward.
• 1-2-3 Punch to inspire action and take your business to the next level.

What is RAG, and How Does It Compare to Other AI Models?

Retrieval Augmented Generation, or RAG, combines the strengths of large language models (LLMs) with relevant, external information from real-time databases. Retrieval augmented generation is a powerful and popular pipeline that enhances responses from a large language model.

Unlike traditional AI models, which rely on pre-trained knowledge alone, RAG brings in current, specific data that fits the context of each question. This makes responses more accurate and tailored—imagine having a research assistant always ready with relevant information.

At Palantir Consulting, I first explored RAG to help manage the influx of technical inquiries we get daily. By retrieving accurate, timely information from our project databases and industry documentation, RAG empowers our team to answer questions confidently and with precision, grounded in real-time data.

Why RAG Matters for SMBs Looking to Gain an Edge

Use Case #1 - Real Estate Agency:

Imagine a real estate agency that regularly fields client inquiries about local property trends, zoning regulations, and current market conditions. Traditional AI could answer general questions based on historical data, but it wouldn’t have real-time, location-specific insights. Here’s where Retrieval Augmented Generation (RAG) shines:

1. Client Inquiry on Market Trends: A client asks, "What are the current trends for property prices in Sydney’s northern suburbs?" The RAG-powered system doesn’t rely solely on general, pre-trained data; it connects to a live real estate database, pulling in recent sales data, property price trends, and local market analysis.
2. Contextualized Response: The system then generates a response that includes current price averages, recent trends, and notable market shifts. This answer is far more accurate and useful than a standard AI-generated response, as it reflects the latest market information, making it highly relevant for the client.
3. Regulation-Specific Queries: Another client might ask about zoning changes in a particular area. With RAG, the system could retrieve the latest zoning data from a government database and provide specific details about the regulations impacting that neighborhood.

In both cases, RAG acts like a real-time research assistant for the agency, instantly delivering tailored, context-specific insights that strengthen the agency’s customer service and decision-making capabilities. This enables them to answer inquiries confidently and stay competitive by offering clients timely and data-driven responses.

Use Case #2 - TAFE, Tutoring and Universities :

Consider a TAFE (Technical and Further Education) institute that offers a wide range of courses, each with specific requirements, job outcomes, and evolving industry standards. With students and prospective learners frequently seeking guidance on course options, job placements, and industry relevance, TAFE could implement a Retrieval Augmented Generation (RAG) system to elevate its student support and advisory services. Here’s how:

1. Student Inquiry on Career Pathways: A student interested in becoming a certified electrician asks, "What qualifications do I need, and what are the current job prospects in Sydney?" A RAG-powered system could pull recent data from industry job boards, government workforce projections, and internal course materials to generate an accurate response. The answer would include specific qualification requirements, relevant TAFE courses, and real-time data on local job openings and salary trends, tailored to the student’s location and career choice.
2. Real-Time Curriculum Updates: Suppose a prospective student wants to know if TAFE’s digital marketing course covers the latest in AI-driven marketing tools and strategies. With RAG, the system can retrieve the latest curriculum updates and pull relevant industry reports on AI in marketing. This ensures that the student receives a response that reflects both the current curriculum and industry relevance, helping them make an informed decision.
3. Scholarships and Funding: A student asks, "Are there any scholarships available for the nursing program, and what’s the eligibility criteria?" The RAG system could connect to TAFE’s internal scholarship database as well as state and federal funding sources to retrieve relevant scholarship information, including specific eligibility criteria, deadlines, and application requirements. This response is then enriched with detailed, up-to-date information that saves the student time and effort.

In each scenario, RAG acts like an advanced “virtual advisor” for TAFE, offering students highly relevant, specific, and accurate responses in real time. This not only enhances the student experience but also allows TAFE staff to focus on more complex inquiries, helping the institute provide high-quality, accessible support while keeping students informed and engaged with the latest opportunities and industry trends.

Use Case #3 - Recruiting:

For recruiting professionals, Retrieval Augmented Generation (RAG) can be a game-changer, particularly in helping recruiters provide precise and personalized guidance to job candidates and hiring managers. Here’s how a recruiting agency could use RAG to enhance their services:

1. Candidate Skills Matching: A candidate reaches out and asks, "What technical skills are currently most in-demand for data analysts in Sydney?" With RAG, the recruiting system can pull up-to-date information from industry job boards, professional network trends (e.g., LinkedIn data), and internal placement success metrics. The system could respond with specific skills—such as proficiency in SQL, Python, or data visualization tools—backed by recent demand trends and salary expectations for these skills in Sydney’s market.
2. Personalized Job Market Insights: A recruiter wants to guide a candidate transitioning from finance to tech. The candidate wonders, "How easy would it be for me to pivot into a data science role, and what would be an appropriate entry-level salary?" Here, RAG pulls from sources like recent salary surveys, job listings, and even TAFE or online courses for reskilling options. The response generated is a tailored roadmap: the necessary skills to gain, certification courses, and salary expectations for entry-level data science roles in the region.
3. Optimizing Job Descriptions for Clients: A hiring manager asks for insights on creating an attractive job description to attract top engineering talent. Using RAG, the system could analyze recent job descriptions in similar roles and locations, identify keywords or benefits that attract higher application rates, and suggest enhancements for the description. This would help the hiring manager craft a compelling job ad aligned with market trends.
4. Addressing Candidate FAQs on Company Culture and Benefits: A candidate asks about a specific company’s culture, remote work policies, or benefits package. Instead of providing a generic response, RAG taps into publicly available employee reviews, the company's own recent posts, and anonymized feedback from the agency’s internal database to generate a relevant, nuanced response.

By providing real-time, context-rich insights, RAG transforms the recruiting process into a more responsive, personalized, and data-driven experience for both job seekers and hiring clients. This enables recruiting professionals to spend more time on high-value tasks like building relationships and interviewing candidates, knowing that RAG has the data retrieval and context-covered.

Use Case #4 - Technical Advisory:

At Palantir Consulting , where we specialise in high-rise structural engineering, clients rely on us for quick and accurate responses—especially when it comes to navigating the stringent regulations set by the National Construction Code (NCC) and meeting compliance requirements outlined in the Design and Building Practitioners Act (DBPA). Traditionally, achieving this level of accuracy required manual searches through complex codes, standards, and internal documentation, which consumed time and valuable resources.

With Retrieval Augmented Generation (RAG), however, we can now access up-to-date data instantly, enabling us to provide answers that are as timely as they are accurate. For example, when a client asks about specific NCC compliance measures for fire safety or the DBPA’s requirements for a structural engineering design, RAG allows us to retrieve precise regulatory guidelines and relevant documentation on demand. This saves hours previously spent cross-referencing documents and standards, and it ensures that every answer is fully backed by the latest regulations and industry standards.

This level of responsiveness was once only available to large corporations with dedicated data teams. Now, with RAG, even small teams like ours can deliver top-tier insights at a fraction of the cost and time. For Palantir Consulting, that translates to fewer bottlenecks, more efficient use of resources, and, ultimately, greater value for our clients as they navigate the regulatory landscape with confidence.

Real-World Applications: Implementing RAG to Enhance Customer Experience, Streamline Operations, and Drive Growth at Palantir Consulting

Here’s how we’re seeing tangible improvements in three core areas of our business with RAG:

1. Customer Experience: When a website visitor asks a specific question, whether it’s about structural engineering code requirements or project updates, RAG allows us to pull up-to-date information directly from our technical knowledge base. AlfredAI helps us integrate these responses into our customer support flow, so clients get immediate answers, improving satisfaction and building trust. Instead of searching through documents, our consultants receive the relevant information, ready to share with clients.
2. Operations Efficiency: For consulting firms like Palantir, operational efficiency is essential. RAG helps us identify patterns in project data, optimizing workflows and managing resources more effectively. For example, when coordinating on-site inspections, RAG enables us to pull historical data on similar projects, helping us predict potential obstacles and allocate resources more precisely. This streamlines our planning and saves valuable time.
3. Strategic Growth and Marketing: Using RAG, we’ve been able to enhance our marketing efforts with more targeted, data-backed content. AlfredAI supports this by helping us automate content creation, generating insights that resonate with our clients’ needs. We’re able to produce posts and updates that are informed by industry trends, regulatory updates, and client interests, all powered by RAG’s contextual insights. This approach makes our marketing more impactful and allows us to connect with our audience meaningfully.

Mindset Shift: Embracing AI Tools to Supercharge Growth

I’ll admit, when I first looked into AI, it seemed like uncharted territory. But I’ve learned that AI isn’t as daunting as it seems—it’s just another tool, like any software or system upgrade. The key is having the right guide. At Palantir, AlfredAI acts as our AI “Butler,” integrating smoothly into our daily processes and enhancing how we work without overwhelming us. With the right mindset, you’ll see that AI is less about complexity and more about unlocking efficiency and precision in your business.

Why AlfredAI Can Make AI Easy for Your Business

If you’re curious about AI but worried about complexity, AlfredAI is an ideal starting point. It’s built with businesses like ours in mind, offering easy-to-use tools that make AI feel approachable and practical. AlfredAI isn’t just a chatbot; it’s like a personal assistant for your business, handling tasks like data retrieval, customer interactions, and even personalised recommendations—all while you stay focused on growth. Having AlfredAI guide our implementation at Palantir has made AI accessible and actionable, allowing us to realise the benefits of RAG without a steep learning curve.

AlfredAI's Solution Packages are designed to address a wide range of business needs, making AlfredAI a versatile addition to any team. Here’s what AlfredAI can do:

• Onboarding and Training: Smooth, efficient onboarding experiences for new hires and training support for staff.
• Job Application: Guides applicants through job processes, ensuring a streamlined experience.
• Lead Generation: Captures and qualifies leads automatically, maximizing conversion opportunities.
• Marketing Content Creation: Assists in generating engaging, targeted content for marketing purposes.
• Event-Specific Engagements: Customizes interactions around events, providing tailored information and support.
• General Enquiries: Handles customer questions with ease, freeing up team resources.
• Appointment Booking: Schedules appointments seamlessly, minimizing scheduling conflicts.
• Sales Assistant (or Assistant to Sales Assistant): Supports sales teams by answering FAQs, nurturing leads, and assisting in conversions.
• Researching: Retrieves relevant information quickly, aiding decision-making and problem-solving.
• Product/Service Recommendations and Information: Provides customers with accurate, up-to-date information and suggestions.
• Troubleshooting: Helps customers resolve issues efficiently, improving satisfaction.
• Survey Collection: Collects feedback and insights from customers for better data-driven decisions.

3 Book Recommendations to Deepen Your Understanding:

1. “AI Superpowers: China, Silicon Valley, and the New World Order” by Kai-Fu Lee – Discover how AI is shaping industries and gain insight into leveraging it for SMBs.
2. “Human + Machine: Reimagining Work in the Age of AI” by Paul R. Daugherty and H. James Wilson – Learn how AI can integrate into everyday business functions, an essential mindset for implementing RAG and AlfredAI.
3. “The Lean Startup” by Eric Ries – This book isn’t about AI specifically, but it’s a valuable guide on iterating and adapting quickly, which is crucial when bringing new technologies like RAG into your business.

1-2-3 Punch to Get You to the Next Level of Success

1 Quote:

“In the new world, it is not the big fish which eats the small fish, it’s the fast fish which eats the slow fish.” – Klaus Schwab

2 Questions:

Where could real-time insights make the biggest difference in your business?

How could automated content generation improve your client communication?

3 Actions:

Test out a RAG-based tool like AlfredAI in one area of your business, such as customer support or content creation.

Identify two high-impact areas where AI could save time or improve accuracy, like project coordination or customer response.

Set a 30-day goal to integrate AI-enhanced processes and evaluate the difference in efficiency and client satisfaction.

Final Words

AI might seem complex, but with tools like AlfredAI, it’s surprisingly accessible. At Palantir Consulting, AlfredAI has made it easy for us to integrate RAG into our workflows, improving our efficiency, precision, and client service. If you’re ready to see what AI can do for your business, start small and see the impact firsthand. Remember, AI isn’t about being tech-savvy; it’s about using the right tools to get better results.

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About Me: I'm William Zhang—an engineer, creator, and business strategist with a deep passion for AI technology and digital innovation. As a business owner in engineering consulting, I also focus on helping others with personal development, financial awareness, startup coaching, business strategy, AI implementation, and building effective teams and partnerships. I believe strong relationships and the advancement of technology can create a better future, and I'm excited to share my insights with you.

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Try for yourself:

Here are some versatile applications of the AlfredAI Chatbot , showcasing various customization and integration styles:

1. Chatbot with Comprehensive HTML Customization: https://www.palantirconsulting.com.au/chatmaster

2. Chatbot as a Floating Bubble on the Homepage: https://www.jcalifts.com.au/

3. Chatbot with Simple HTML Customization: https://www.tenderadvisory.com.au/chatbot/

4. Chatbot Loaded After Lead Qualification Form: https://www.winspro.com.au/ai-chatbot/

5. Chatbot as a Floating Bubble on the Homepage: https://www.xin.com.au

Want to know more about AlfredAI? Feel free to interact with AlfredAI itself directly through the chatbot: ?? Ask AlfredAI

Each example illustrates how AlfredAI can be tailored to fit various use cases, from embedded chat bubbles to standalone applications with or without lead generation. Explore these to see AlfredAI in action!