diff --git a/llm-rca/ReadMe.md b/llm-rca/ReadMe.md
index 56facb8..498d154 100644
--- a/llm-rca/ReadMe.md
+++ b/llm-rca/ReadMe.md
@@ -8,8 +8,8 @@ This project delivers multi-source data analysis with Model Chaining (Classic-AI
**Options:**
-[1] Use of OpenAI backend for GenAI part: Select -> [llm-ml-rca.ipynb](https://github.com/tme-osx/TME-AIX/blob/main/llm-rca/llm-ml-rca.ipynb)
-[2] Option-A: Open-AI's ChatGPT or Option-B: Use of Red Hat Openshift AI Model as a Service backend for GenAI part: Select -> [maas-rca.ipynb](https://github.com/tme-osx/TME-AIX/blob/main/llm-rca/maas-rca.ipynb)
+[1] Option-A: Use of OpenAI backend for GenAI part: Select -> [llm-ml-rca.ipynb](https://github.com/tme-osx/TME-AIX/blob/main/llm-rca/llm-ml-rca.ipynb)
+[2] Option-B: Use of Red Hat Openshift AI Model as a Service backend for GenAI part: Select -> [maas-rca.ipynb](https://github.com/tme-osx/TME-AIX/blob/main/llm-rca/maas-rca.ipynb)
## Metric file processing
It starts with a processing a telecom metric file. The following is an example set of the metric data:
diff --git a/starlink/readme.md b/starlink/readme.md
index 7398b1e..0b6cdd7 100644
--- a/starlink/readme.md
+++ b/starlink/readme.md
@@ -1,5 +1,15 @@
# Starlink Internet Service Quality of Experience Predictions
-We have trained a neural network transformer model to predict Satellite Internet Service QoE.
+
+Objective: Nomadic users, such as RV campers, often face challenges accessing the internet in remote locations. While mobile cellular radio access solutions may sometimes prove inadequate due to limited coverage or suboptimal price-to-performance ratios, satellite internet offers a compelling alternative.
+
+With Starlink emerging as a robust option, providing improved coverage and connection speeds, its Quality of Experience (QoE) remains variable across different geographic locations. Factors such as altitude, the number of visible satellites, weather conditions, and potential obstructions affecting satellite line-of-sight significantly influence service quality.
+
+To empower travelers with insights into Starlink's internet service quality at their destination, we have developed and trained a neural network transformer model. This model predicts QoE by analyzing key parameters, offering nomadic users a AI-Tool to anticipate and plan their connectivity needs effectively.
+
+
+
+
## API