Chatbots have evolved significantly over the years. Not a long time ago, a chatbot resembled a model script in which the “Press 1 for help” kind of bots left users frustrated. These chatbots were the rule-based chatbots. Currently, thanks to advancements in modern AI, there are smarter bots, understanding context, searching up and having a natural conversation.
If you have a rule-based chatbot and you are wondering whether it is time for an upgrade, you are not alone. Let us take a look at how to move to an RAG (Retrieval-Augmented Generation)-based or agentic chatbot with a few examples to understand it better.
What is the Rule-Based Chatbot?
A Rule-based Chatbot works on pre-set rules or decision trees. For example, if the user says “Hi,” respond by corresponding: “Hello! How can I help?” If the user asks about pricing, show a fixed list. Such simple bots are good for simple tasks like FAQs and booking appointments. But they just don’t know what to do when the user asks a question they never expected or they can’t sense if users are seeking a personalized reply.
Example:
A travel agency rule-based bot might only answers the question: “What are your travel packages?” But if a user says, “Can I get a weekend trip from Bengaluru under ₹10,000?”, it will not have an idea about the answer to this.
So, enters the RAG-Based Chatbots. What does this mean?
RAG means Retrieval-Augmented Generation. Such bots do not reply with pre-written sentences, they:
- Fetch documents/relevant data from a knowledge base (FAQs, websites, PDFs, etc.).
- Frame Human-generated sophisticated answers (large language models like GPT or similar).
Because of this, the chatbot can process new information and give a natural reply to users.
For Example: For the question “Can I get a weekend trip from Bengaluru under ₹10,000?” an RAG-based chatbot could actually search the travel database and analyse it with the company website and reply:
“Yes! We have a weekend trip from Bengaluru to Hampi for ₹9,500 including stay and transport. Would you like check out the itinerary?”
This seems like talking to a human rather than a robot.
What is an Agentic Chatbot?
It is an agent-based chatbot that goes one step further. It not only responds, but can also take actions, make decisions and complete all simple tasks across systems.
They can:
- Book a meeting and add it to your calendar.
- Extract data from CRM’s.
- Send out follow-up messages.
- Complete a user’s data from an input in a form.
Agentic chatbots behave more like digital assistants (Digital PA) or junior team members.
For Example: A customer service chatbot on an e-commerce site can understand a complaint and retrieve their order history, process a return or refund and email them the return bill all during the chat.
Why Should You Transition from Rule-Based to RAG or Agentic?
Here are some really important reasons to support for the transition:
| Features |
Rule-Based (Old style) |
RAG-Based | Agentic |
| Handles complex queries | X | ✅ | ✅ |
| Learns from stored content | X | ✅ | ✅ |
| Actions (bookings, updates, etc.) | X | X | ✅ |
| Conversations feel natural | X | ✅ | ✅ |
| Scale easily | X | ✅ | ✅ |
Steps to Switch
- Audit your current bot: List all the individual typical user questions and where your current chatbot fails in serving its purpose.
- Organize your knowledge base: Collect all FAQs, policy documents, manuals and web-content, since RAG models require the support of good data to be retrieve from.
- Decide on a framework: Tools such as LangChain or LlamaIndex or OpenAI along with Hugging Face can help you build RAG or agentic bots.
- Integrate with systems: For agentic bots, you will require APIs or access to the system such as CRMs, booking engines, etc. so that the bot can perform these actions.
- Trial run with real users: Start with a beta test, monitor where it does well and where it gets confused, and keep refining and improving.
From a rule-based to a RAG-based or agentic chatbot is just upgrading from a basic calculator to a smart gadget. It doesn’t help you in just finding answers, but it helps you solve problems, act on it and then build real value for the end user.
With increased expectations from end users, these chatbots are becoming must haves! So, if your current chatbot has gone ancient, maybe now is the time to give it a brain and turn it in to smart bot.
We are a Business Performance Improvement company, helping organizations traverse their Data to Insights journey and beyond and leverage curated Analytics Technology such as Tableau & Alteryx. With over 550 customers worldwide including world leading companies, CRG Solutions is trusted around the world to deliver expert services and innovative solutions to help businesses thrive. Contact us today!
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