Creating a Knowledge Base

Aera’s Knowledge feature visualises each stage of the RAG pipeline, providing a user-friendly UI for application builders to easily manage personal or team knowledge.

Developers can upload internal company documents, FAQs, and standard working guides, then process them into structured data that large language models (LLMs) can query.

Compared with the static pre-trained datasets built into AI models, the content in a knowledge base can be updated in real time, ensuring LLMs always have access to the latest information and helping avoid issues caused by outdated or missing data.

When an LLM receives a user query, it first uses keywords to search within the knowledge base. Based on those keywords, the knowledge base returns content chunks with high relevance rankings, giving the LLM crucial context to generate more precise answers.

This approach ensures LLMs do not rely solely on pre-trained knowledge. Instead, they can also draw from real-time documents and databases, enhancing both the accuracy and relevance of responses.

Key Advantages

• Real-Time Updates: The knowledge base can be updated anytime, ensuring the model always has the latest information.

• Precision: By retrieving relevant documents, the LLM can ground its answers in actual information, reducing hallucinations.

• Flexibility: Developers can customise the knowledge base content to match specific needs, defining the scope of knowledge as required.

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You only need to prepare text content, such as:

• Long text content (TXT, Markdown, DOCX, HTML, JSONL, or even PDF files)

• Structured data (CSV, Excel, etc.)

• Online data sources (Web pages, Notion, etc.)

By simply uploading files to the Knowledge Base, data processing is handled automatically.

If your team already has an independent knowledge base, you can use the “Connect to an External Knowledge Base” feature to establish its connection with Aera.

Use Case

Imagine you are building a customer support assistant for a Web3 project based on Solana. Your team regularly updates its whitepapers, development progress, and frequently asked questions. You can upload those documents to the Knowledge Base in Aera, allowing the assistant to draw real-time, relevant data about Solana’s blockchain, tokenomics, and related updates.

Traditionally, developing and maintaining a support chatbot for such a niche, fast-evolving ecosystem could be time-consuming. But in Aera, this process is streamlined, allowing you to have the system up and running in minutes. With constant updates to your knowledge base, your AI support assistant will always be equipped with the most current and accurate information to answer user queries related to Solana, cryptocurrency trends, or Web3 development.

Knowledge Base and Documents

In Aera, a Knowledge Base is a collection of Documents, each of which can include multiple Chunks of content. You can integrate an entire knowledge base into an application to serve as a retrieval context, drawing from uploaded files or data synchronised from other sources.

If your team already has an independent, external knowledge base that is separate from the Aera platform, you can link it using the External Knowledge Base feature. This way, you do not need to re-upload all your content to Aera. Your AI app can directly access and process information in real time from your team’s existing knowledge.

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Let me know if this works for you!