LuminAI

LuminAI is a platform for creating AI assistants for businesses that operate based on the information and business rules of a specific company.

Unlike simple chatbots that work through fixed buttons and predefined scenarios, an AI assistant can analyze user requests in free-form language, consider conversation context, and generate responses based on a connected knowledge base.

It acts as the first line of communication: providing consultations, qualifying requests, collecting information, and performing configured actions while transferring only those cases that require specialist involvement to a human employee.

The platform is useful for companies that receive a large volume of requests through websites, messengers, social networks, or email. These include online stores, service companies, educational projects, sales departments, and support teams.

For businesses, this means instant responses to customer requests 24/7 and a reduced risk of losing inquiries outside working hours.

The assistant handles routine responses and initial contact collection, allowing employees to spend less time repeating the same information and focus on complex, non-standard tasks that require human involvement.

Connection does not require changes to the website code itself. The assistant can be added through an online chat widget or connected to messengers and social networks.

The main task during implementation is creating a knowledge base (information about products, prices, delivery, company rules, and communication scripts).

Integration with a chatbot and CRM allows the assistant not only to answer questions but also to participate in business processes: creating or updating customer records, saving conversation details, and transferring collected data to managers so they do not need to ask customers for the same information again.

For such situations, a dialogue transfer scenario to an employee is configured. The assistant identifies when a request goes beyond its knowledge base, requires an individual solution, or needs specialist involvement.

The operator receives not only the request itself but also the full context of the previous conversation and collected data. The customer does not need to explain the situation again, and the employee can immediately start solving the issue with a complete understanding of the case.

The knowledge base used for automated customer support needs to be updated when prices, product ranges, delivery terms, or internal company rules change.

If the assistant is integrated with a CRM, catalog, or warehouse system, some information can be retrieved from these sources automatically.

It is also recommended to regularly analyze real conversations, identify questions where the assistant provides inaccurate responses, and expand the knowledge base with new scenarios based on real customer interactions.

It is recommended to start by analyzing current customer requests: create a list of 20–30 most common customer questions that will become the foundation of the knowledge base. Then test the demo assistant on the project website to evaluate its response logic and suitability for your needs.

After that, you can discuss a pilot launch on one channel (for example, only on the website or only in Telegram). This allows you to evaluate what share of requests the system can handle without operator involvement and then scale the solution to other channels and processes.