AI-POWERED SERVICE PROCESS MANAGEMENT, AUTOMATED SUPERVISION AND INSIGHT ANALYSIS SYSTEM

Abstract

The invention relates to a system for automating and optimizing interaction-based service processes, specifically enabling the recording of online coaching sessions, their analysis using artificial intelligence, and the generation of process insights through automated supervision. The system architecture and methods are adaptable to mentoring, consulting, and similar online professional service processes, not limited to coaching.

Description

AI-POWERED SERVICE PROCESS MANAGEMENT, AUTOMATIC. SUPERVISION AND INSIGHT ANALYSIS SYSTEM TECHNICAL FIELD The invention is aimed at automating and optimizing coaching processes. This relates to the system, including recording and analyzing conversations and the process. artificial intelligence and automated supervision methods that enable the generation of insights These methods include coaching, mentoring, and consulting. similar online interaction-based processes within the service sector It is practical. PREVIOUS TECHNIQUE In the current state of the art, there are various software systems for service process management. and rule-based automation tools are used. For example, IT service management. In the field of Information and Communication Technologies (ITSM), artificial intelligence-powered systems automate routine tasks and By applying data analytics, it can identify problems and offer solutions. this includes predictive improvement suggestions, automated error analysis, and continuous learning. The aim is to improve service quality with existing skills. However, the current solutions, guidance of service personnel and quality control of processes It is usually based on human supervisors or static rules. For example, in call center applications, managers manage the conversations of agents. providing feedback by listening through random sampling, or through software systems. It generates reports solely by analyzing text recordings after the interview. Ensuring consistency and quality control in distributed or remote teams is more important. This is becoming increasingly difficult. Current systems monitor every interaction in real time. Because they cannot intervene immediately, customers sometimes have different experiences from representative to representative. They can have experiences. Indeed, artificial intelligence support is used in call centers. Since real-time evaluation of each interview is not practical without this, Quality fluctuations can be unavoidable. 1 Furthermore, in known applications, artificial intelligence generally plays a reactive role: In other words, they only analyze and draw conclusions after a negative situation arises. An integrated artificial intelligence system that provides real-time proactive coaching and automated monitoring. An intelligence module is needed. To meet this need, instant artificial intelligence is required. It provides intelligence coaching and automated process monitoring. THE PURPOSE OF THE INVENTION The purpose of the invention is to provide assistance to personnel working in service operations during procedures. It enables the provision of immediate feedback and guidance to employees at that moment. by analyzing their interactions (e.g., customer conversations or task steps) Immediate suggestions, warnings, or corrective feedback are provided to the staff. This enables personnel to... By receiving the support it needs exactly on time, it can correct its mistakes immediately and It can improve your performance. Another purpose of the invention is to enable processes to operate continuously and automatically, 24 / 7. It is the monitoring. The automated supervision system introduced with the invention replaces human supervision. Without the need for further assistance, it monitors all service transactions tirelessly and impartially. Artificial intelligence detects deviations according to defined rules and criteria and takes action when necessary. It intervenes immediately or generates a warning. Thus, each operation is the same in every shift. It is monitored at a level of attention (unlike human monitoring, artificial intelligence never focuses attention). (It shows no signs of fatigue or tiredness, remaining constantly fully alert). This is the state of the service. by ensuring consistency in quality, every customer receives the same high standard every time. It aims to provide an experience. Another aim of the invention is to reduce the burden of manual supervision and training for humans. The goal is to minimize errors. AI coaching, routine checks, and feedback. by taking over their duties, allowing supervisors to focus only on critical situations. This provides managers with complete visibility and prioritization in process monitoring. This is ensured through the analysis panels and alerts provided by the system. Managers can intervene before problems escalate. 2 Another aim of the invention is to enable the artificial intelligence module to improve itself and adapt to processes. It is about adaptation. The system developed within the scope of the invention is based on past interactions. And it improves feedback algorithms by learning from the results. For example, a specific By identifying over time which suggestions improve performance for the given problem type, we can use them in the future. It prioritizes these suggestions in similar situations. This is how dynamic coaching works. by creating a mechanism to identify best practices specific to each institution or environment. It is adapted by the system. DETAILED DESCRIPTION OF THE INVENTION The invention aims to automate and optimize one-on-one online service processes, such as coaching. It relates to a system developed for this purpose. Specifically, recording of conversations, artificial intelligence is used to analyze and generate insights into the coaching process. It includes intelligence and automated supervision methods. The matching module uses advanced artificial intelligence to identify the most suitable coach for the client. It uses an intelligence algorithm. The algorithm analyzes the client's demographic data and background. It gathers and analyzes information about people's lives, career goals, and personal interests. For example... client's age, gender, occupation, education level, work experience, future prospects Their goals and even personal preferences, such as their favorite movie / book, are included in this data pool. Additionally, a questionnaire consisting of multiple-choice questions is administered to the client at the beginning of the process. Expectations and needs are determined. This collected data is used for all coaches registered in the system. It is used to calculate a fitness score. The algorithm analyzes survey responses and By evaluating other profile information with specific weighting coefficients, a score is assigned to each coach. It produces scores. Among these scores, the one with the highest score (above a certain threshold value) is selected. The first three coaches (on top of the list) are selected, and one of them is assigned to the client. The matching algorithm has three uses to measure the accuracy of its results and to improve itself. It involves a phased verification process. The first phase is called the "Chemistry Interview". This is the so-called preliminary meeting; it is the first brief meeting between the client and the coach. The coaching process begins after the meeting, indicating that the matching was successful. This is the first indication. In the second stage, the coaching process is uninterrupted and successful. Completion (holding all foreseen sessions) of the algorithm's correct match 3 confirms what they did. In the third stage, at the end of the process, by the client... The average score of the completed satisfaction survey is evaluated; for example, 5 A satisfaction score of around 5 points indicates the effectiveness of the algorithm. It is accepted as proof. This feedback mechanism allows for matching. The module continuously improves itself based on real-world results. As a result, To maximize the rapport between client and coach, a learning and adaptive approach is essential. A matching infrastructure is provided. This matching module analyzes the content of the surveys and... By adapting the question structures to different usage scenarios; mentor- Various networking and professional matchmaking opportunities, including mentee relationships. It can be applied in their activities. The session recording module records each coaching session between the coach and the client. It stores the information digitally. The system records conversations as audio, written (text-based), or virtual. It allows audio calls to take place in virtual reality (VR) environments. With the client's permission, it is recorded and automatically transcribed into text (transcript of speech). (transcription). In coaching sessions in the form of written messaging, the texts are... It is already stored digitally. This ensures that everything discussed during the meeting is recorded digitally. It is archived as a continuous data set. The recording module not only stores raw data but also real-time data. It offers data processing capabilities. For example, instant text extraction from audio recordings and important data processing. Tasks such as identifying keywords can be done during the interview. The results obtained... The rich dataset will serve as input for future automated supervision analysis and recommendation systems. The system collects metadata such as duration, frequency of conversation, and the like for each interview. It also records it. The technical infrastructure of this module includes automatic speech recognition. Higher efficiency is achieved using (ASR) algorithms and natural language processing (NLP) techniques. The translation into text is carried out with accuracy. All interview data will be used for future reference. It is stored in the data pool with a timestamp for later retrieval. This ensures a complete digital record of the coaching processes, without any critical information being lost. is created. The recommendation system module acts like an AI coaching assistant during the interview. Real-time feedback and recommendations to improve the coach's performance. This module is equipped with both rule-based and learning algorithms, and It continuously monitors the flow of the coaching conversation. The analysis outputs produced by the module, 4 performance improvements over time for users providing coaching services monitoring and comparing these developments with reference data sets It can be used in a way that allows for evaluation. Based on specific triggers or... Depending on the needs, it intervenes and generates the following types of suggestions: ● Question Suggestions: The system analyzes the questions asked by the coach and provides feedback when necessary. It offers new question suggestions. These suggestions are from the ICF (International Coaching Federation). based on competency sets and rules derived from coaching tools like KOPP. This is done, for example, by asking contract questions at the beginning of the interview. can serve as a reminder or ask powerful questions to clarify the client's goal. This way, the coach can avoid skipping any critical stages of the interview. They can ask the right questions. ● Reflection Suggestions: The system shows when the coach last reflected (on the client's side). He follows up on what he said (summarizing and reflecting back). If for a long time If no mirroring occurs (e.g., ~7 minutes), mirror the coach again. It automatically suggests that the coach do what the client says. This feature allows the coach to... Quiet spaces for contemplation that allow for understanding and deeper reflection. It encourages creativity. ● Silence Recommendations: The speaking rates of the parties are monitored during the meeting. The suggestion module can help if the coach talks too much or continues the dialogue incessantly. If so, it reminds them that they need to take a conscious break from silence. Especially. If continuous talking occurs without a deep silence (for example, more than 5 seconds) (if there are no long pauses), the system will notify the coach of this situation after a short time. It suggests that the coach remain silent, giving the client space to think. This mechanism is called coaching. It helps to ensure a balanced distribution of conversation during the meeting. ● Appreciation Suggestions: The system supports the appreciation statements (praise and motivation) used by the coach. (expressions of disapproval) are collected in a pool and their frequency of use is monitored. If If the coach's rate of appreciation for the client is low or prolonged during the session If the coach hasn't given appreciative feedback for a while, the system will notify the coach within a suitable interval. It suggests that the client appreciate something they have shown. For example, an effort the client has made. If the opposing coach remains silent, the system coach "praises the client for their effort". This can provide warnings about the issue. In this way, the client's motivation is kept high. The suggestion system module, with its functions described above, aims to increase the coach's immediate awareness and It aims to optimize the quality of the conversation. The AI ​​assistant works in the background. By constantly working, he / she both performs linguistic analysis of speech and works in the field of coaching. It generates recommendations based on best practices. The technical basis of this module is the interview. NLP models and rule-based triggers that analyze data in real time There are mechanisms in place. The recommendation system provides important insights into the coach's performance. metrics (e.g., how long it has been since they reflected, how many questions they asked, (such as whether or not a word of appreciation is used) it monitors and intervenes when necessary. Thanks to real-time feedback, the coach can adjust their method instantly; this allows As a result of the consultation, the client gains deeper insights and the process It contributes to its efficient progress. The automated supervision module is central to this invention and improves the quality of coaching. It is a critical component that evaluates using objective criteria. This module covers each coaching session. By subjecting the transcript of the meeting to a detailed analysis, the coach's coaching It automatically assesses the extent to which you have demonstrated your skills. Specifically, Eight core coaching competencies defined according to international standards (for example) (active listening, powerful questioning, action planning, ethical awareness, etc.) system It is monitored by the automated supervision algorithm, which analyzes the interview content. a set of rules that identifies the moments and examples where each of the competencies is demonstrated It has. For example, a coach reflecting the client's feelings is "active listening". This serves as an example of her competence; asking the client goal-oriented questions is "powerful". This is interpreted as an indicator of "questioning" competence. The module analyzes these types of patterns. It searches the dialogue text and assigns a score for each competency category. Technically, this evaluation process uses natural language processing and machine learning. It is carried out using a combination of techniques. In the first stage, the interview text is prepared in advance. The results are scanned for defined keywords, phrase patterns, and emotional tones. For example, sentences that repeat the client's statements are key indicators of empathy. The phrases and clues, such as questions related to goal setting, are captured. At a more advanced level... as, a trained artificial intelligence model (e.g., a deep learning-based text (classifier), overall assessing the quality and competency of this interview. It evaluates. Thousands of coaches who previously scored highly have been selected for the model's training. Labeled data from the interview was used. In this data pool, human "Examples of good practice" labeled by supervisors or expert coaches. It can be found; for example, with a tag indicating which competency a particular sentence exemplifies. 6 It is marked. The automatic supervision module is new in light of this learned information. It evaluates the interviews and provides rapid, consistent, and impartial oversight. A supervision report and scorecard are generated by the module for each meeting. As well as an overall performance score, a separate score was assigned for each of the eight competencies. This can also be calculated. For example, if the coach's "active listening" skill was 80% in that session... While the percentage of "powerful questioning" skills displayed was high, the system may have remained at 60%. This information is reported as numeric scores. In addition, the module analyzes the interview. It also generates various quantitative data on: the rate of conversation between coach and client (for example (It's like the client did 70% of the talking, and the coach did 30%), during the session. total number of questions asked, number of reflections given by the coach, discretion used details such as the number of expressions, the most frequently repeated words and their frequencies It is automatically removed. For example, the system says "A total of 30 sentences were created, for a session, One could generate statistics like this: "20 of these were questions, 5 were appreciation questions, and 3 were reflection questions." These types of parameters numerically reveal the structure of the coaching session. It provides developmental tracking. One of the most important outputs of the automated supervision module is that it provides a guideline for each meeting. This involves creating a digital logbook (interview log). This logbook records the relevant session. Automated supervision includes the date, duration, client and coach information. It also includes a summary of the analysis. It shows which competencies were demonstrated at which moments. The log outlines areas for improvement, the coach's strengths, and areas for development. The system compiles these logs over time to track the coach's performance improvement. It also tracks things like the coach's average "active listening" score over the last 10 meetings, etc. Trends such as whether it has increased or decreased compared to the previous period can be determined from logbook data. It is removable. This module replaces the classic human supervision process with an objective, repeatable, and It provides scalable supervision. In manual supervision, each session is handled individually. While it can be both time-consuming and subjective for an expert coach to read and evaluate, Thanks to automated supervision, the system processes many interviews in a very short time. It can evaluate and score data according to a standard set of criteria. This is also part of coaching services. to enable large-scale monitoring of its quality, to provide training, and when necessary It enables instant feedback. The module adapts itself as new data arrives. It is a constantly evolving structure by updating both the rule set and the artificial intelligence model. It is designed so that new trends, questions, or techniques in the coaching world are incorporated into the data. 7 As these are added to the pool, the system learns about them and includes them in the evaluation criteria. does. In conclusion, automated supervision reliably improves the quality of coaching sessions. By measuring in this way, it provides coaches with the opportunity to see their own development, as well as It ensures clients receive more consistent service. Generated by the system. supervision scores and performance indicators are prepared to be presented to clients. It is customizable, allowing clients to analyze their coaching service providers' past experiences. It can be selected based on performance data and has a high level of reliability. This module allows the coaches to stand out. This module is the most distinctive feature of the invention. one of the elements is maintaining and improving standards in the coaching profession. It brings a significant innovation to the name. The insight generation module processes the large volume and diverse coaching data collected within the system. It is the component that derives strategic insights by analyzing. This module is particularly useful for long-term projects. emerging from coaching processes consisting of long-term and numerous meetings It is designed to examine trends and their effects. Technically, data mining, using statistical analysis and machine learning methods to analyze data It looks for meaningful correlations. First, the client's awareness and behavioral changes are analyzed. Each Feedback received from the client at the end of the session, completed questionnaires, or There are assessments that are made. The system determines which client is evaluated after each session. text that they have reached new awareness or which action steps they have adopted It extracts this data through analysis. This data is anonymized and then used to compare it with other clients in similar situations. It is evaluated together with the data. The aim is to determine the effectiveness of a particular coaching technique or approach. The goal is to understand the impact it has on the client. The module performs correlation analysis between data of different sizes. For example, coaching. topics (the main problem or goal the client is addressing), coaching used in the interview tools (such as vision boards, election wheels, etc.) at the end of the interview survey results (client's satisfaction score with the session or self-perception) the progress observed) and the tangible changes that occur at the end of the process (the client's Statistical relationships are investigated between (whether or not they have achieved their goals). In this way, It can be shown which types of approaches are more effective under which conditions. For example... Analyses may show that in coaching focused on "gaining self-confidence," the most... Successful results have been obtained when regular homework assignments have been followed, or 8 The most commonly used tool for the "inability to say no" problem: the election wheel. It has been observed that the application increased client satisfaction scores by 20%. Indeed, the system is most commonly focused on the topic of "I Can't Say No" coaching. The tool used is the election wheel, and the insights gathered from it are used for coaching. He cites as an example that it is of such value that it can even be transferred to schools. The insights gained are used for two main purposes: First, to create new coaching sessions. To provide recommendations. The system is designed for clients with similar profiles and problems. By learning what worked in the past, you can strategize with the coach for the next meeting. They can offer suggestions. For example, if the client's goal is weight loss, they can share previous successful experiences. to suggest the "journal keeping" technique that emerges in cases or a specific week If motivation decreases after a certain number of steps, measures should be taken to address this. like giving advice. In this way, the coaching process becomes a continuously improving cycle. The second objective is to improve the overall quality of coaching services and training. The goal is to produce the material. The module compiles anonymous data collected on specific topics. It generates reports that can be used for coaching trainings. For example, "Manager "The 5 most effective question types in coaching" or "In the first session of team coaching" Reports can be generated around themes such as "things to do / avoid". Reports are valuable for coaches, coaching schools, or corporate training departments. It provides insights. Furthermore, the extensive anonymous data collected by the system, and The conclusions drawn from these can also be used for the overall development of the coaching industry. (e.g., industry trend analyses, common challenges, etc.). Technically, the insights module is a cloud-based data processing module for handling big data. It uses its infrastructure. Thousands of interview and survey results accumulated in the data warehouse, With analysis scripts or artificial intelligence pipelines written in languages ​​like Python / R For example, association rule mining can be used to identify a specific coaching technique. Relationships can be found between a profile and success with a client. Time series The analysis monitors how a client's motivation score changes throughout the process. Critical moments of decline can be identified. All these technical processes result in... The information is presented to the relevant users in the system's Smart Reports interface. In summary, the insight generation module represents the collective learning of coaching processes. Trends and information too high-level to be gleaned from individual interviews. by revealing this, it enables both the more informed direction of individual coaching processes. It provides both recognition and data-driven development throughout the coaching profession. 9 The communication module connects the client even outside of the coaching sessions. It is designed to support and keep it engaged. This module, It manages automated personal communication channels. The coaching session ends. When completed, the system reinforces the process for the client and encourages reflection. For this purpose, they may send additional questions and materials. For example, at the end of the interview. the client, through an artificial intelligence tool, is given information about the topic discussed in that session. A thought-provoking question or a motivating image can be sent. This will help the client... based on how the system responds to communication (for example, based on its answer or emotional tone), continue to automatically send email or in-app notifications to the client. This ensures that the interaction remains fluid even during the time between the two coaching sessions. This process continues in this way; the client does not disengage from the process. In addition, the communication module helps clients achieve coaching goals in their daily lives. It offers push notification support to help the client focus. The system provides the client with... instantaneous at predefined times or when specific triggers occur. It sends notifications. These notifications include reminders (for example, "The task you set for this week"). Have you worked on it?"), motivational boosters (e.g., "Let's take even a small step today"). How about you throw it away?") or helpful content (e.g., a relevant article or quote) It is possible. The aim is to increase the client's commitment to the coaching process and the skills they acquire. The goal is to make it easier for them to integrate these awarenesses into their daily lives. Another function of the communication module is to track the client's actions and It is a reminder. Actions determined by the client themselves during the coaching session. steps (for example, "I will walk three days a week" or "I will teach my employees more (For example, "I will provide frequent feedback") is noted by the system. After the interview. These actions are automatically converted into a digital task tracking list. The defined From time to time, the system sends notifications reminding the client of these promises. For example, If the client committed to a task before the next meeting, during the interim period You might receive alerts like, "You have 3 days left to complete your task." This is automated. Follow-up involves the client taking responsibility and taking steps towards achieving their goals. It encourages. The communication module also enables the platform's multi-channel and multi-platform support. It also manages. The system allows coaching interaction via phone calls, video calls, It allows for conducting conversations in various environments, such as text-based chat or VR. Which Regardless of which platform is used, the module records all communications in an integrated manner and It communicates feedback through the appropriate channel. For example, coaching conducted in a VR environment. After the session, when the client leaves the application, a summary and a question are sent to their mobile phone. can be sent. This flexibility allows the user to choose the most suitable communication method according to their preference. This ensures their selection and contributes to a seamless coaching experience. In conclusion, the communication module transforms the coaching process into a 24 / 7 living experience. This allows the client to come. The client experiences artificial intelligence not only during the sessions but also afterwards. It continues to be guided and supported by the intelligence-assisted system. This This situation increases the client's motivation and the likelihood of achieving their goals. increases. The gamification module increases the participation of clients and even coaches in the process. It is a component that implements game mechanics to increase motivation. In human psychology, it is known that reward and competition increase motivation. This The module adds a fun element of competition and reward to the coaching process. The system identifies specific achievements or milestones of the client with badges, levels, and It recognizes clients with digital rewards, such as points. For example, if a client successfully completes their initial action plan... Upon completion, you can earn a "Starter Badge" by regularly attending five consecutive meetings. By participating, you can advance to the next level or achieve one of the defined goals. By completing these tasks, you can earn points. The collected points can be used to create an avatar within the platform. It can be designed to offer features such as customization or access to additional content. Badges and levels visually represent the client's progress; for example... The "Silver Level Client" badge indicates that you have made significant progress. Gamification elements can also be applied to coaches. A coach, High satisfaction ratings from clients and scores within the platform They can earn or receive titles such as "Expert Coach". This fosters a healthy relationship among coaches. It creates a competitive environment and promotes service quality. Technically, the gamification module triggers specific events that occur within the system. It is used in this way. For example, the event "the client completed the task on time". When this happens, this module is activated and assigns the relevant badge or points. These triggers are rule-based and related to user activity within the platform. It is integrated. Gamification data (which user earned which badge, points) (tables, etc.) are stored in the system database and integrated with the visualization module. It is displayed on the user interface as a result of operation. 11 In addition, the module includes motivational messages. It helps the client reach a certain level. Encouraging notifications like "One step left, keep going!" when they see you getting closer They can send it. In this way, users can participate in the process both rationally and emotionally. Commitment is increased. The overall effect of the gamification module is to transform the coaching process from a monotonous task into something more effective. The goal is to take it out and transform it into an interactive experience that gives a sense of progress. Clients are rewarded as they put in effort, just like in a game. By observing, they develop intrinsic motivation. This leads to behavioral change and goal achievement. It provides an additional impetus along the way. As a result, the module is filled with fun competitive elements. It adds an innovative dimension to coaching processes. The visualization module displays all data collected by the system and process progress. It is a component that offers these features through user-friendly interfaces. Thanks to this module, both Both coaches and clients monitor the progress and performance of the coaching journey. They can easily track their metrics. The system displays the data generated after each meeting and action as a digital indicator. It brings them together in a dashboard. In the interface offered to coaches, each It contains profile pages and statistics for the client. For example, the client's process. How many meetings have been completed since the beginning, what actions have been determined? Information such as completion rate and average satisfaction survey scores are presented in graphs. The data is presented in tables. The coach can also see data on his own performance; Competency score averages determined by the automated supervision module, time Trends within it, the coaching techniques it uses most and least, etc. This numerical feedback The feedback provides the coach with an opportunity for self-improvement. The visualizations offered to clients are primarily for goal tracking and motivation. It is focused on: the stage they are at in achieving their self-defined goals, their total scores, Information about the gamification process, such as the badges they earn and their level progress, is presented visually. is presented. In addition, important insights or the client's thoughts that emerge after each session are shared. The insights that the client expresses are also added to their profile as notes. This allows the client to... It allows him to see concretely how far he has come. The visualization module also includes reporting tools. For example, specific what happened during the coaching process within a specific time frame (e.g., the last month, the last three months) PDF / HTML reports summarizing the interview can be automatically generated. These reports include the interview. Summary information such as dates, supervision scores, survey results, and key notes are included. 12 Coaches may share these reports with senior management or their supervisors; clients may also receive them. They can use it to see their own growth stories. Technically, the visualization module retrieves data from the database in the background, It converts visual elements into graphical representations using graphic libraries on the front end. bar graphs, line graphs, pie charts, timelines, and badge icons, etc. Various visual presentations are used. Interactive elements are employed to enhance the user experience. Features are also offered; for example, when a point on the graph is clicked, the relevant The details of the meeting can be examined. This module analyzes coaching interaction patterns through process monitoring dashboards. This also makes things easier. For example, a coach can tell all his clients which topics they are more likely to discuss. inferences such as which weeks a client or a working professional struggles the most, This can be achieved through the filtering and cross-tabulation features on the panel. The system is also critical. It provides visual alerts for parameters that reach a threshold; for example, client satisfaction. If the question-asking rate of the coach has dropped or decreased significantly, a warning icon will appear on the panel. They become apparent. Thus, abnormalities or points that require attention can be easily noticed. It is done. In summary, the visualization module makes all the key indicators of the coaching process understandable. and by presenting it in an attractive format, making data transparent and actionable. This allows users (both coaches and clients) to develop themselves. And they can concretely track the process performance. This awareness, regarding the process... more informed decisions are made and timely intervention is necessary. makes it possible. Module Integration and System Flow: All modules described above, They work together on an integrated platform. In a typical workflow, while the client is registering... The matching module assigns a suitable coach. The recording module is activated when the interview begins. The system logs in and data collection begins; simultaneously, the recommendation system provides real-time support to the coach. At the end of the interview, the recorded data is transmitted to the automated supervision module and Session analysis is performed. The results are written to a logbook and visualized. This is reflected in the panels and reports. The communication module is immediately activated, connecting both the coach and the other party. It sends questions to the client after the session and records the client's actions. In the following days, the communication module kept the process alive with notifications, while gamification was used. The module motivates users. As the process progresses, the insights module runs in the background. It collects and analyzes data and, when necessary, recommends other modules of the system (e.g., suggestions). 13 (the system or matching algorithm) is updated in light of new findings. All With the modules working together in an orchestral fashion, the coaching service is seamless from start to finish. It becomes a data-driven, customized, and continuously learning structure. This invention is for humans. By empowering a focused process with technology, it provides both scalability and... It creates a personalized, high-quality experience. 14

Claims

1. AI-powered service process management, automated supervision, and It is an insight analysis system; its feature is: - collecting and analyzing demographic, biographical, and interest data of clients at least one AI matchmaker that matches clients with coaches. module; - Digitally recording coaching sessions in audio or written form and using the audio content At least one interview recording module that converts the conversation to text; - By monitoring the interaction in real-time during the meeting, you can suggest questions to the coach. offering at least reflection reminders, silence warnings, and appreciation advice. a suggestion system module; − The transcripts generated after each session are prepared in advance by the coach. By analyzing each competency according to eight defined core competencies. Objective supervision evaluation that scores the level of display at least one automated supervision module that does so; - processing anonymized interview and survey data and coaching topics, the relationships between the tools used, satisfaction outcomes, and behavioral changes. by analyzing correlations, new approaches to interviews or general coaching practices at least one insight generation module that produces suggestions and predictions on the subject; - Automated to maintain interaction with the client outside of coaching sessions. Personalized questions, reminders, and motivation via email, message, or notification. at least one communication module that sends content; - By incorporating game mechanics into the coaching process, the client's task completion and session... Incentivize achievements such as participation with digital rewards such as points, badges or levels at least one gamification module; - collecting and processing process data in real time for the coach and client. performance indicators, interaction patterns, and progress status data visualization module that presents data in graphical interfaces It includes.

2. AI-powered service process management, automated, in accordance with Claim 1. It is a supervision and insight analysis system whose feature is; audio coaching sessions. by recording and transcribing written conversations and digitally storing them. by archiving, it enables automatic analysis of all interview content. It includes a call recording infrastructure.

3. AI-powered service process management, automated, in accordance with Claim 1. It is a supervision and insight analysis system; its characteristic feature is the relationship between the coach and the client. By scanning the interview transcripts in terms of eight core coaching competencies, each determining the extent to which the competency is applied and accordingly, competency-based It includes an automated supervision module that performs the scoring.

4. AI-powered service process management, automated, in accordance with Claim 1. It is a supervision and insight analysis system whose feature is; during the coaching interview giving the coach reminders to reflect at regular intervals and expressing appreciation Based on the frequency of use, the coach offers suggestions on how to appreciate the client. It includes a real-time recommendation system module. 16