Project Context

While the AI can see the columns and data, it doesn’t always know the broader “why” behind your project. Project Context allows you to provide high-level guidance to tune the AI’s personality and accuracy.

The Three Tiers of Context

You can provide descriptions in three specific categories to give the AI a complete picture:

1. Application Description

The “What and Why.” Describe the business purpose of the application.

Example: “This is a SaaS billing platform for a healthcare provider. We track monthly subscriptions, insurance claims, and patient billing cycles.”

2. Technical Description

The “How.” Describe naming conventions, architectural quirks, or technical mapping.

Example: “Our table names use the prefix m_ for master data and adm_ for admin logs. All timestamps are stored in UTC.”

3. Scope of Data

The “What’s Available.” Define the boundaries of what data is present and what is not.

Example: “The database contains sales data from 2020-2024. It does not include marketing spend or payroll data.”

Why Provide Context?

Reduced Hallucinations: By telling the AI what data is not there, it won’t try to guess or invent answers for missing data.
Better Naming Understanding: Technical descriptions help the AI map cryptic column names (like col_32x) to their real meanings.
Professional Persona: Application context helps the AI use the correct industry terminology in its responses.

How to Update Context

Go to Project Settings → Setup.
Locate the the Description fields.
You can type directly or Upload a File (Text, PDF, or Word) containing your project documentation.
AnalytAI will automatically process these documents to extract the most relevant context for the AI.