Great AI answers have always depended on one thing: the right information at the right time. When we launched, we cracked that with RAG. Now, we’re taking it to the next level.
We made our agents context-aware.
These agents just know.
They don’t simply respond to a message – they understand the person who sent it. They can see the page the user is on, take in live details you provide (like user’s name or order status), and even explain not only what they know, but how they know it.
Webpage awareness
Your agent can now “read” up to 500 words directly from the exact page it’s embedded on and use that knowledge to its advantage.
This means your customers interact with an agent that uses the article, product, or policy they’re viewing to anticipate their intent and deliver relevant, helpful answers right away, eliminating irrelevant responses and reducing needless back-and-forth.
If you use Live Chat, your agent can now also greet visitors with a highly specific Starter Question tailored to that page – increasing engagement from the very first message.
User information
You can now feed your agent valuable, user-specific details that only you know (first-party data) – the kind of insights that make interactions feel personal and proactive.
With this context, your agent can anticipate needs, offer more relevant solutions, and build stronger connections with your users.
Self-knowledge
We’ve boosted your agent’s awareness of its own knowledge base.
It can now confidently answer questions like “What are you knowledgeable about?” and explain its capabilities with greater certainty – helping users understand exactly how it can assist them.
Don’t forget about the Persona!
The agent’s Persona has always been there, but now it’s more important than ever.
By defining who your agent is and who it works for, you give it a consistent voice and tone that amplifies every other feature, from page-specific knowledge to personalized responses.
Experience Context Awareness Today
Context-Aware Agents represent the next step in intelligent, adaptive AI. They read the page, understand the user, and respond with precision, empathy, and purpose.
Enable Context Awareness now and let your agents truly know your customers.
👉 Enable Context Awareness Now!
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Frequently Asked Questions
Why do AI chatbots still give generic answers even with RAG?
RAG improves retrieval, but answers can still sound generic when the agent lacks runtime context about the exact page, the user, or its own knowledge boundaries. Context-aware agents address that by reading up to 500 words from the current page, using live first-party details you choose to send, and stating what they are knowledgeable about. That combination helps reduce irrelevant replies and unnecessary back-and-forth.
How is context engineering different from prompt engineering?
Prompt engineering mainly defines instructions, tone, and role. Context engineering determines what information the agent can use when the question is asked, such as the current webpage, live user details, and awareness of its knowledge base. In practice, prompts shape how an agent answers, while context shapes whether it can answer specifically instead of generically. Michael Juul Rugaard, Founding Partner & CEO, The Tokenizer, said, “Based on our huge database, which we have built up over the past three years, and in close cooperation with CustomGPT, we have launched this amazing regulatory service, which both law firms and a wide range of industry professionals in our space will benefit greatly from.”
If one agent is embedded across my whole site, can it answer differently on each page?
Yes. One site-wide agent can respond differently on each page because it can read up to 500 words directly from the exact page where it is embedded. That lets the same agent use local article, product, or policy content as context and even generate a page-specific live chat starter question.
Can I send only basic client context and let users opt in to deeper personalization?
Yes. You control which user-specific details are sent to the agent, so you can start with basic first-party fields such as a user’s name or order status and avoid sharing sensitive data by default. Relevant trust signals include GDPR compliance, data not used for model training, and SOC 2 Type 2 certification.
Can a context-aware agent tell users what it knows and why it answered that way?
Yes. A context-aware agent can explain both what it knows and how it knows it by distinguishing between knowledge from the current page, your uploaded sources, and live user details you provided. That self-knowledge helps users understand the agent’s scope and makes answers easier to trust. Elizabeth Planet, Nonprofit Leadership Coach & Advisor, said, “I added a couple of trusted sources to the chatbot and the answers improved tremendously! You can rely on the responses it gives you because it’s only pulling from curated information.”
Does persona still matter if the agent already knows the page and the user?
Yes. Persona still matters because context decides which facts are relevant, while persona controls voice, role, and audience. The same policy answer may need a different tone for an HR guide, a legal assistant, or a sales coach. Barry Barresi, Social Impact Consultant, described that role-specific setup this way: “Powered by my custom-built Theory of Change AIM GPT agent on the CustomGPT.ai platform. Rapidly Develop a Credible Theory of Change with AI-Augmented Collaboration.”