How context windows can increase your company's success with AI

What is a context window and why does it matter?

A context window is comparable to an AI model's short-term memory. Just as people have both a short-term and a long-term memory, AI works in a similar way:

• Long-term memory: The AI model itself, which is based on billions of data points and training. This determines the AI's general knowledge and skills and serves as the fundamental source of understanding.
• Short-term memory: The context window, which determines how much information the AI model can process at any given moment. This is the amount of data AI can work with directly to generate answers and provide contextually relevant output.

Picture the context window as a lens through which AI interprets your question. The more information you make available through that lens, the more focused and more relevant the AI's answers will be. Without that lens, AI would understand only fragments, whereas a well-filled context window allows the model to give contextually relevant and in-depth answers.

The context window also plays an important role in processing longer dialogues and complex documents. A smaller window can lead to limits in understanding, while a larger window allows AI to make connections between different pieces of information.

Context windows in business operations: the secret behind smarter, AI-driven interactions

The size of the context window determines how well AI can handle complex questions or extensive datasets. That is particularly valuable for companies that want to use AI in combination with their existing systems such as ERP, CRM or PIM.

By connecting these systems to an AI model through a database, you can feed the context window with specific user information. That allows you to:

1. Make targeted recommendations: Advice on specific products based on customer history from your ERP and CRM, for example. That can give a significant boost to cross-selling and up-selling and increase customer satisfaction.
2. Improve technical support: Manuals and fault information can be looked up and applied quickly. That speeds up problem solving and raises customer satisfaction considerably.
3. Generate efficient quotations: By automatically linking spare parts and relevant product information to customer questions. That minimises manual effort, reduces errors and maximises accuracy.

Context windows can also contribute to better internal processes, such as automated workflows and predictive analysis. By integrating the right data into the context window, an organisation can gain insight into trends and respond proactively to customer needs.

A practical example: how the context window improves interactions between people and companies.

Let us sketch a concrete scenario:

A B2B company sells spare parts through a customer portal. They have:

• An ERP system: Historical project information that gives insight into work carried out previously and into customer projects.
• A CRM system: Detailed customer data, such as contacts, buying behaviour and preferences.
• A PIM system: Extensive product information, including technical specifications, prices and availability.

By connecting these systems to a central database and integrating that with an AI model, customers can ask questions such as:

• "Which spare parts do I need for machine X?"
• "What is the maintenance history of my products?"
• "Can you generate a quotation for replacing product Y?"

The AI answers these questions by retrieving relevant data from the database within the context window. That increases not only efficiency but also user satisfaction. Customers experience more personalised service and companies save time and resources through automated processes.

An additional advantage is that the system can learn continuously from interactions. That means the AI gets better over time at delivering relevant and valuable answers, which further strengthens the overall customer experience. Companies can also extend these AI solutions into other areas, such as predicting future customer needs or streamlining internal operations.

How does the context window work? A closer look

The context window is determined by the number of tokens an AI model can process. A token can be a word, a character or even part of a word. Larger context windows offer more room for:

• Deeper understanding: AI can analyse longer passages of text and tailor answers better to complex questions. That is especially useful in scenarios where extensive documentation is needed, such as technical manuals or legal documents.
• Extended memory: The model can better remember earlier parts of a conversation, which makes the conversation more consistent and more fluent. That matters a great deal in applications such as customer service and interactive tools.
• Advanced applications: Such as processing long documents or generating in-depth analyses and reports. That gives companies a competitive advantage when dealing with large volumes of data.

Current AI models vary widely in the size of their context windows. ChatGPT can process up to 128,000 tokens, while some models can handle millions of tokens. For companies that means larger context windows offer more scope for solving complex, data-specific problems. Choosing the right model depends on the specific needs and goals of your organisation.

The quality of the data that fills the context window also plays a crucial role. Only relevant and accurate information guarantees that the AI can give usable and reliable answers. Companies must therefore invest in data quality and integration in order to make optimal use of context windows.

Conclusion: the future of AI lies in clean data and integration to improve the context window

The context window forms the lens through which AI sees the world. By supplying that lens with specific and relevant information from your ERP, CRM and PIM systems, you can use AI not only to understand better what your users need, but also to offer value proactively. That makes it possible to serve customers more effectively, streamline processes and stimulate innovation.

The possibilities of AI only become truly clear once you understand how the context window works and how you can use it for your organisation. With the right combination of technology and strategy, exploiting this technology can deliver a significant competitive advantage. In an increasingly data-driven world, understanding and applying context windows is not a luxury but an absolute necessity. With a well-configured context window and a considered approach, companies can embrace the future of AI and strengthen their position in the market.