With the E1F.AI system, the processing and response to customer service inquiries can be transformed into an AI-powered process, significantly increasing efficiency. The system continuously monitors incoming inquiries, identifies the sender, and then gathers the information needed for a response from specialized systems, background policies, and the knowledge base, generating a ready-to-send response suggestion that the agent can review and send from a single interface. Even complex, time-consuming tasks can be completed in a fraction of the time, significantly reducing the workload on staff members. A key principle is that artificial intelligence does not replace but rather supports employees: every outgoing response is sent only after human approval.
Automatic processing of incoming emails
The system continuously monitors the customer’s dedicated mailboxes, automatically imports every new email into its own database, and handles attachments as well. During processing, it extracts the email’s key metadata and displays the emails in a structured, tabular format on the user interface. Messages can be tracked by status, freely filtered, and sorted, allowing the administrator to immediately see all open inquiries.
A ready-made suggested response with just one click
The system consolidates search results and data retrieved from specialized databases into a single context, and then—using a freely configurable model—formulates a user-friendly response based on this context. Response generation can be initiated with a single click from the interface. The generated text can be freely edited, saved as a draft, and finally sent directly from the application to the requester or even to multiple recipients at once, with the option to attach files.
Central interface and access control
Our solution consolidates all incoming inquiries, the associated data, and the AI-suggested responses into a single, easy-to-navigate web interface. Access is role-based, communication with specialized systems takes place over an encrypted channel, and the system retrieves only the data that is actually necessary for the task.
Semantic search
Based on the content of an incoming query, the system searches for relevant information in preloaded documents—such as current legislation, regulations, and guidelines. It is capable of handling multiple, separate document sets: based on the channel through which the query was received and the query tags, it automatically draws from the knowledge base corresponding to the specific subject area. Thanks to AI-based semantic search, results are returned not only based on keywords but also on the meaning (context) of the query.
Interdisciplinary connections
The system is capable of communicating with any selected specialized systems via custom-developed connectors. It checks uploaded documents on a scheduled basis, without human intervention, and writes the results back to the connected system. The integration supplements the responses with verified data (e.g., company name, contact information, liability insurance details, status information), making the generated responses more accurate and personalized.