The problem with standard AI
Ask any off-the-shelf AI tool something about your business, your products, or your internal processes, and you get a vague or incorrect answer. That makes sense: the AI was trained on general internet knowledge, not on your specific information. It does not know your delivery times, what your product manual says, or how your return procedure works.
For businesses that want to deploy AI seriously, that is a problem. You want answers that are correct — based on your documents, your data, your knowledge.
What is RAG in plain language?
RAG stands for Retrieval-Augmented Generation. In everyday language: AI that looks it up first, then answers. Instead of guessing based on general knowledge, the system first searches your own documents, finds the relevant information, and formulates an answer based on that.
Compare it to an employee who receives a customer question. A good employee does not make up the answer — they look it up in the manual, the customer system, or the product database and then give a well-founded answer. RAG works in exactly the same way, but lightning fast and at scale.
AI that makes up answers is useless for your business. AI that looks it up first and then answers — that is where the value lies.
Why standard AI does not work for business questions
Standard AI tools are impressive for general questions, but they have three fundamental limitations for business use:
- They do not know your business — They know nothing about your products, prices, processes, or customers.
- They fabricate answers — When they do not know the answer, they generate something that sounds plausible but is factually incorrect. In a business context, that is unacceptable.
- They are not current — Their knowledge is limited to the data they were trained on. Your most recently updated price list or newest product line? They do not know about it.
RAG solves all these problems by providing the AI with your current information as a source.
How it works — without getting technical
The process consists of three steps:
- Your business knowledge is loaded — Documents, manuals, product information, frequently asked questions, internal procedures — everything relevant is converted into embeddings and stored in a vector database.
- When a question comes in, the right information is retrieved — The system searches the vector database and finds precisely the passages relevant to the question asked.
- The answer is formulated — Based on the retrieved information, the AI formulates a clear, complete answer. With the ability to reference the source, so you can always verify where the answer came from.
Where businesses deploy this
Internal knowledge base
Employees ask questions in plain language and get instant answers based on internal documents. No more spending hours searching through folders, SharePoint, or old emails. The new hire who wants to know how the expense process works gets a clear answer within seconds, with a reference to the right document.
Customer service
An AI that answers customer questions based on your product information, FAQs, and service documentation. The answer is always correct because it comes directly from your own sources. For complex questions, the customer is seamlessly handed off to a human agent.
New employee onboarding
New colleagues have dozens of questions about processes, systems, and agreements. Instead of repeatedly asking busy colleagues the same questions, they can consult the system. The AI knows all the procedures and gives consistent, correct answers every time.
Product information for sales
Your sales team has instant access to current product specifications, pricing, comparisons, and talking points. One question and the system delivers a complete, up-to-date answer — even when the product range changes frequently.
The knowledge already exists in your organization. RAG makes that knowledge accessible to everyone — without anyone having to interrupt a colleague.
Privacy and security
A legitimate concern: you do not want sensitive business information leaking to external parties. That is why how the system is set up matters. There are multiple options:
- Fully private — The entire system runs on your own servers. No data leaves your organization.
- Secured cloud environment — The system runs in a secured environment with a trusted provider, with strict data processing agreements.
- Hybrid — Non-sensitive queries go through a fast cloud solution, sensitive data is processed locally.
At Coding Agency Meppel, we always advise which approach fits your situation, taking into account the nature of your data and any compliance requirements.
How we build this
We build RAG solutions tailored to your organization. We start by inventorying your available knowledge sources: which documents, databases, and systems contain the information you want to make accessible?
Then we set up the system, connect it to your existing software, and test it thoroughly with real questions from your daily operations. After delivery, we ensure new documents are automatically processed so the system always stays current.
The result: an AI that knows your business, gives answers that are correct, and saves your team hours of work — every single day.
Want to discover how your business knowledge can be made available through AI? Coding Agency Meppel is happy to show you what is possible with your own data in a short demo.
