Software & AI Development

Here To Know About The Projects

This is my built AI tool. Please click on the link to go to the tool.

https://fliki.ai

1. Technical Challenges

1. Data Quality & Availability – AI models need large, clean, and representative datasets; collecting and preprocessing data is difficult.

2. Algorithm Complexity – Designing and tuning models (ML/DL) to produce accurate, reliable results is challenging.

3. Computational Resources – Training advanced AI models requires high-performance GPUs/TPUs and cloud infrastructure.

4. Integration with Existing Systems – Making AI tools work seamlessly with current software or workflows can be tricky.

5. Scalability & Performance – Ensuring the AI tool performs efficiently as the user base or data grows.

2. Design & User Experience Challenges

1. Interpretability & Transparency – Users need to understand AI decisions; black-box models can reduce trust.

2. User-Friendly Interfaces – Designing intuitive tools that non-technical users can use effectively.

3. Customization & Flexibility – Adapting AI solutions to different industries or specific business needs.

3. Ethical & Business Challenges

1. Bias & Fairness – Preventing biased outputs caused by skewed data or model design.

2. Privacy & Security – Protecting sensitive user data used in AI training and predictions.

3. Regulatory Compliance – Meeting legal requirements for AI applications in healthcare, finance, etc.

4. Cost & ROI – High development and maintenance costs can be a challenge for businesses.