Training – AI That Evolves With Your Business

Depending on the tasks it needs to perform, the AI is trained using real, high-quality data—this may include customer interactions, past chat logs, user behavior, existing website content and images, company documentation, or external sources that closely align with your brand and audience.

The collected data is cleaned, structured, and categorized to avoid errors, remove duplicates, and ensure maximum accuracy. Any missing information is filled in where necessary.

Example: If training an AI to recognize clothing, all images must be labeled with categories such as “shirt,” “pants,” or “dress.”

It analyzes frequently asked questions and continuously improves its responses.

It remembers customer preferences and personalizes its replies.

It identifies recurring issues and optimizes processes.

Example: An online store uses AI that notices many customers asking, “What’s the return policy?” After a few interactions, the AI automatically enhances its response by adding more details and a direct link to the return policy.

You can review and edit AI responses in real time.

Add new phrases, scenarios, and query-handling logic.

Configure the AI to respond in specific ways for particular situations.

Example: A hotel manager notices the AI doesn’t recognize late check-in requests. From the admin dashboard, they add a new response, which the AI remembers and uses automatically with future guests.

AI analyzes customer reactions from conversations and continuously scans for incorrect or incomplete responses. When it detects an issue, it flags it, suggests improvements, and offers configuration options.

Example: In an insurance company, the AI receives a high number of negative reviews for a specific response. The admin panel displays a warning, allowing your team to revise the message and make it clearer.

When changes occur in your business—such as new products, offers, or policies—the AI automatically updates its knowledge base.

It can integrate with external sources to stay current and relevant.

It also suggests new recommendations and scenarios based on market trends.

Example: An e-commerce business adds a new product category. The AI automatically recognizes the new items, understands related queries, and begins delivering accurate answers immediately.