Successfully Deploy AI in Your Company with Terminology
As terminology has been our domain for decades, we see enormous opportunities for AI to finally give terminology the importance it deserves. Terminology can thus serve as a "guard rail" to steer the weaknesses and risks of the various AI models in an orderly fashion.
But why do we even need these guard rails? LLMs, AI, GenAI, ChatGPT, Gemini, et al are all based on a vast amount of data harvested primarily from the Internet. The problem here is that the models all provide answers that are, at best, factually correct but terminologically rather unpredictable—and at worst, are completely fictitious and demonstrably false (hallucinations). But thanks to our "terminology-augmented generation (TAG)" approach, you can use AI efficiently in your company.
Retrieval-augmented generation with terminology
Approaches such as retrieval-augmented generation (RAG) work relatively well to enrich LLMs with up-to-date knowledge based on documents, but they fall short when it comes to structured knowledge such as terminology. RAG systems try to find relevant text passages based on semantic similarity, leading to unpredictable retrievals and inefficient token usage.
To access structured data sources such as termbases more efficiently, our AI team has created a specialized form of RAG: TAG – Terminology-augmented Generation.
However, TAG is not just some abstract concept, but a real solution that has already been realized as a retrieval endpoint in Quickterm, much to the delight of IT departments everywhere. Once a termbase has been set up by your terminology team, TAG makes it easy and convenient to use and opens up a wide range of applications.
Die Terminologie bildet eine grundlegende Ebene, die der KI dabei hilft, aussagekräftige und vertrauenswürdige Ergebnisse zu liefern. Um diesen Mehrwert zu erschließen, sind menschliche Aufsicht, strukturierte Daten und Systemintegration erforderlich.
Advantages of TAG for your company
Terminology-augmented generation has numerous benefits for businesses. Chief among them is that TAG turns your corporate terminology into a robust and reliable data source that can be easily integrated into various applications—even without extensive expertise in terminology. Further advantages include:
AI in our terminology software
In addition to the retrieval endpoint, Kalcium Quickterm has other helpful AI functions:
Terminology verification and replacement
- Can be enhanced with AI to grammatically adapt texts as necessary.
Metadata usage through AI
- Suggestions for definitions, word type (noun, etc.), grammatical gender, example sentences, and synonyms.
Customization of prompts
- Possibility to customize prompts yourself or with the support of the Professional Services team to adapt termbase content to comply with your corporate language.
Integration of external AI services
- Connect your own AI model via OpenAI or Azure OpenAI ("bring your own key").
- Planned integration of other service providers such as Google, Mistral, or Huggingface.
The image below shows what a translation with terminology-augmented generation (TAG) looks like compared to the normal gpt-4o output. As we can see, TAG has correctly applied the preferred corporate terminology.
AI workshops and training courses
We are also happy to share our AI expertise through our popular training courses. Please contact us for a customized training package proposal for your company.
Terminology extraction with TermCatch and AI
Even before the rest of the world had even heard of ChatGPT, we at Kaleidoscope were very excited about the possibilities of artificial intelligence. Our partner Fodina uses its TermCatch term extraction software to identify and extract terminology from a wide variety of sources with outstanding quality thanks to AI and LLMs. As the official reseller of TermCatch, speak to us if you're interested in procuring TermCatch for your own organization.
Terminology extraction with TermCatch and AI
Learn more about AI and terminology:
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