AI Assistant, AI Call Center Solutions, Smart Marketing Systems

1. Phone Robots with IVR (Interactive Voice Response) or AI (Artificial Intelligence) - Smart Marketing

Such a phone robot is capable of calling a large number of clients (even multiple at the same time), performing the work of many people, to ask if they want to make an appointment.

• In the case of an IVR robot, the client responds to the robot’s questions by pressing keys on the phone keypad.
• In the case of an AI robot, the client speaks just like with a human, because the robot is capable of understanding human language (even multiple languages - Romanian, English, German, etc.), and the client’s responses are processed (speech to text), interpreted, and stored in a database.

The robot has several voices that can be used: male or female voice tone.
The entire IT system operates directly from the Cloud, so there is no need to install any hardware or software in the client’s infrastructure.

a) Example use case, IVR Robot:

Such a system is ideal for companies or public institutions that already have a customer database whose subscription is expiring, want to inform them of a new personalized offer, or want to contact them for scheduling purposes.
The robot can either call a phone list or receive incoming calls from clients.
Such systems are intended for:

• gas installation companies that already have a list of clients and need to notify them to renew their mandatory gas inspections for heating systems; the entire scheduling process can be done by the phone robot
• city halls or public institutions that want to notify citizens: taxes that need to be collected, appointment confirmations
• medical clinics that want to automatically confirm appointment attendance on a specific day and time
• those who want to implement smart marketing systems

b) Example use case, AI Robot (Artificial Intelligence):

Such a system is first trained to understand the company’s activity. It is trained on a relevant dataset in order to be able to answer multiple questions.
Training can be done in several ways:

• if there is little information the system needs to know, it is enough to provide this data through a comprehensive "context"
• if the system needs to be able to answer many questions, then fine-tuning is used, training an LLM model in the Cloud and generating a new domain-expert model
• another option, perhaps the most useful when the AI system needs to become an expert in a field with many procedures, rules, laws, etc., that change frequently, is to use the RAG (Retrieval-Augmented Generation) technique. In this case, non-relational databases capable of indexing and extracting semantically similar information quickly (e.g., Pinecone or PostgreSQL + pgvector) are typically used and stored in Cloud systems (AWS or others).

The PhoneBot answers a client’s phone call, understands the conversation (in Romanian, English, Spanish, and others), and effectively communicates with the client. The client asks, the robot understands the meaning of the question, performs a database search, and then responds with relevant information.

Such an AI-based IT system is aimed at:
- those who want to provide an AI Assistant outside working hours, allowing clients to call 24/7
- institutions that want to offer public information services (city halls, companies)
- companies that perform services requiring prior appointments. Clients call, speak to the AI Assistant, and schedule an appointment. Example: medical clinics, installation companies
- companies that provide call center services, especially when those services rely on a well-defined set of technical procedures that can be used to train the model

Advantages:
- reduces costs by enabling rapid calling of a very large number of clients, replacing numerous employees who would otherwise be needed to perform this task. The robot handles the work of many employees. It doesn’t require salaries or bonuses and doesn’t mind working non-stop...
- the system can generate reports showing contacted people, call status (answered, not answered, hung up, appointment scheduled), call date, call time, etc.
- the phone robot can automatically reschedule for the next day if the client doesn’t answer



2. AI Expert Systems in a Specific Field Created Through Fine-Tuning an LLM or Using the RAG (Retrieval-Augmented Generation) Method.

These types of AI systems represent the present and near future of artificial intelligence development. Until now, databases allowed searches by certain keywords, but the answers weren’t intelligent — they simply provided raw information to the human operator.
Now, we can generate systems that truly understand both the question and the search texts, identify relevant information, retrieve data from multiple sources, and then generate a final response.

Example:
• 1. Such systems can be extremely useful for companies with many internal procedures. These can all be grouped into a dataset used to train a Large Language Model (LLM) through Fine-Tuning or implement the RAG method. Then, by querying the model — through a web interface or voice (e.g., when calling a phone number and being answered by an AI Assistant) — users can receive relevant information on the desired topic. In this case, the question can be asked just as you would ask a human!

For example, we developed an AI system that combines the RAG method with fine-tuning and uses top LLMs (OpenAI’s GPT-4o, GPT-4o-mini, DeepSeek R3, DeepSeek R1, Mistral) to answer questions about the Traffic Code and Road Regulations. You can access it here.
It is interesting to observe that the answers differ depending on the reasoning capabilities of the used model. There are also cases where one model cannot provide the right answer to a complex question, while another one can.
• 2. Legal field: such systems can be trained on specific legal areas (sets of laws), useful for legal professionals, lawyers, or specialists in fields where fast and accurate responses are crucial — just like consulting with a human expert.


It’s important to understand that this field of AI assistants and artificial intelligence-based systems is still very new and rapidly expanding. Those who implement such systems early will gain a competitive advantage. These systems are not infallible and cannot yet fully replace humans (nor is that the goal), but they can help companies reduce costs and offer high-tech services to their clients. Based on the examples above, feel free to contact us so we can discuss how AI systems can be integrated into your company’s operations.

For all the examples above (IVR robot that calls, IVR robot that can be called, AI robot that can be called, intelligent system that can be queried on a specific legal topic), we can provide functional demos that you can test.