Impressive, but not always right
Anyone who has ever worked with ChatGPT or similar tools will be familiar with the phenomenon: the answers sound convincing - but sometimes there is no reference to reality. Technical terms are mixed up, figures are invented, sources are not substantiated. These so-called "hallucinations" occur because classic AI models are only based on their training data. They give statistically probable answers, not necessarily correct ones.
This is a problem for SMEs that depend on reliability on a day-to-day basis. Our contribution to the ROI of AI.
What is behind RAG
The solution is called Retrieval Augmented Generation (RAG). Instead of simply responding from the memory of the language model, the AI also draws on external, verified data sources. It "fetches" the relevant information (retrieval) and incorporates it into its response (generation).
This results in answers that are not only fluently formulated, but also factually correct, up-to-date and contextualised.
An example from practice
An employee asks the AI: "What leave days apply in our company for the Christmas period?"
- Without RAG: The AI advises - perhaps on the basis of general public holidays, but without reference to your company.
- With RAG: The AI searches the internal document on holiday regulations, finds the valid specifications and delivers the exact answer - customised for your company.
You can also find out more about this practical added value in the article on Cross-Agent Collaboration.
Why RAG is indispensable for SMEs
Precision is particularly important in the SME sector. If information is unclear or incorrect, it costs time, money and, in the worst case, trust. RAG prevents AI from working blindly. It ensures that answers not only sound good, but are also accurate. Relevant and verifiable are.
Amaiko: RAG integrated into everyday life
With Amaiko RAG is not a theoretical concept, but a fixed component:
- Internal dataGuidelines, protocols or project documents are integrated.
- External sourcesCurrent knowledge from specialised portals or public databases is consulted.
- Contextualised answersAI delivers results that are not only correct, but also precisely match the question.
This makes Amaiko more than just an assistant: it is a Reliable buddythat does not leave employees in the lurch, but provides answers that can be used directly.
Conclusion: No future without a factual basis
AI without RAG is like driving a car without headlights - you're moving, but blind. With RAG, AI becomes a tool that not only inspires, but also enables well-founded decisions.
See Amaiko in action:
Book your personal consultation now and see how RAG can transform your AI applications from insecure to reliable.
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