Behind the AI – Automated Business Intelligence System
Integrates AI and data analytics to automate business intelligence processes. By automating reporting, trend analysis, and predictive insights, the system reduces manual effort.

Challenge / Problem Statement
The client faced multiple challenges:
- Manual feedback analysis was time-consuming and error-prone.
- Lack of structured reporting made it difficult to identify growth opportunities.
- Decision-making often lacked actionable insights from employees and leadership.
- Difficulty in translating raw feedback into strategic business decisions.
Objectives
- Automate feedback analysis and reporting.
- Provide leadership with data-driven insights.
- Improve decision-making with actionable recommendations.
- Enhance scalability by leveraging AI/ML-powered systems.
Our Solution
We designed and implemented an intelligent automated report generation system using Google Gemini and ChatGPT. The system:
- Collected structured and unstructured feedback from CEOs and employees.
- Preprocessed and cleaned data to ensure quality inputs.
- Applied prompt engineering to design contextual and strategic prompts.
- Leveraged Gemini and ChatGPT to generate high-quality, insight-driven reports.
- Delivered leadership-ready business intelligence with actionable recommendations.
Tools & Tech Used
- Google Gemini API
- Python
- Webhooks/API
- ChatGPT (OpenAI API)
- Pandas, NLTK
- Jinja2, Markdown
Results & Impact
- End-to-end automated system for report generation.
- Reduced manual effort by 80%+.
- Improved efficiency in gathering and interpreting feedback.
- Provided leadership with clear action points for scaling.
- Increased engagement by including employee insights in strategic planning.
- Delivered high-quality, tailored strategic reports powered by LLMs.
Key Takeaways
- AI/ML unlocks hidden business insights from employee and leadership feedback.
- Automated reporting significantly reduces time, cost, and manual effort.
- MoreYeahs’ AI expertise enables scalable, future-ready solutions for enterprise growth.
Project Duration & Team
- Duration: 6 weeks
- Team: 1 Project Manager, 2 AI/ML Engineers, 1 Frontend Developer