Business Problem

In today’s fast-paced work environment, team leaders face significant personal and professional development challenges that impact their ability to drive team productivity. Key issues include:

• Lack of Personalized Guidance: Traditional training and coaching methods often provide generic advice that may not address individual needs or situations.
• Limited Access to Coaching: High-quality coaching and development resources can be expensive and are not always accessible to all employees or individuals.
• Difficulty in Tracking Progress: There is often no straightforward way to measure the effectiveness of personal development efforts and track progress over time.

Solution

GoML addressed these challenges by developing SurePeople’s "Coach Me" feature, specifically designed to enhance team productivity by providing personalized coaching to team leaders.

Personalized Coaching Experience: Users receive tailored advice and strategies on various customizable topics, including communication, time management, and leadership. This is powered by Amazon EC2, Lyzr SDKs, and NLP algorithms for natural language understanding and response generation.

Cost-Effective Alternative: Leveraging AI technology on Amazon EC2 and MongoDB Atlas enables organizations to offer extensive development resources to a broader audience at a reduced cost, with Generative APIs automating response generation and reducing the need for human coaches.

Scalable and Accessible Solution: The AI-driven coach, hosted on Amazon S3 and managed through Amazon API Gateway, is available 24/7. It provides high-quality coaching to team leaders anytime and anywhere, reducing costs compared to traditional methods.

Progress Tracking and Analytics: The system monitors user interactions stored in MongoDB, collects feedback through surveys orchestrated by Apache Airflow, and analyzes improvements in skills and performance via Data Processing APIs to ensure effectiveness.

Architecture

• Amazon S3: Stores coaching guides, frameworks, and profiles.
• MongoDB: For data storage, Apache Airflow for workflow management, and Webhooks for real-time updates.
• Amazon EC2: Runs applications that handle data using Lyzr SDKs, RAG Pipeline, Docker, and Data Processing APIs.
• MongoDB: For semi-structured data and MongoDB Atlas for vector data.
• Meeting Module, Generative APIs, and Query Extraction APIs: For processing and responding to user queries.
• Data Refresh: From MongoDB/Airflow/Webhooks to Amazon S3; data processing and output handled by APIs and directed to the Static Data Warehouse and Meeting Module.