Context Window

The maximum amount of text an AI model can process in a single request. It includes your instructions, the retrieved documents, conversation history, and the generated response.

Technical definition

The context window is measured in tokens and represents the model's maximum input + output capacity per inference call. GPT-4o supports 128K tokens; Claude 3.5 supports 200K. When the combined length of the system prompt, retrieved chunks, conversation history, and desired output exceeds this limit, the oldest or least relevant content must be truncated or omitted.

How Verabase uses Context Window

Verabase manages context windows automatically. When a conversation grows long, the system intelligently summarizes older messages to preserve the most relevant context within the model's token limit. RAG retrieval is also context-aware — Verabase retrieves only the most relevant chunks rather than dumping entire documents into the context, which maximizes the useful information per token.

Why it matters for support teams

A larger context window means the AI can consider more information when generating an answer — more conversation history, more document context, more nuance. But bigger isn't always better: filling the context window with irrelevant information can actually reduce accuracy. Smart context management (what Verabase does automatically) matters more than raw window size.

Related terms

How Verabase Handles Self-Healing Knowledge

The standard industry approach relies on support agents manually flagging stale content and technical writers updating documentation weeks later. Verabase completely upends this model through an autonomous AI platform that identifies knowledge gaps the moment an AI agent encounters a question it cannot answer.

Rather than requiring manual intervention, our visual RAG engine drafts a proposed fix. It analyzes the context of the user's question, reviews your existing knowledge base for conflicts, and creates a clear, structured article or snippet. All you need to do is click 'Approve'. This ensures your AI agents continually get smarter over time without adding to your support team's workload.

Security First Architecture

Many legacy platforms bolt AI onto their existing infrastructure, creating potential data leaks between tenants or exposing sensitive internal documents to end-users. Verabase is built from the ground up with a Bring Your Own Key (BYOK) architecture, enterprise-grade access controls, and strict semantic boundaries. This means your private engineering documents never accidentally leak into customer-facing agent responses.