diff --git a/README.md b/README.md
index 56d7ac4..558bd45 100644
--- a/README.md
+++ b/README.md
@@ -9,12 +9,14 @@ DS Task Tag Scan is an AI-powered clothing tag identification and similarity sea
 * **Tag Identification**: Uses computer vision to identify clothing tag brands from images
 * **Text-Based Matching**: Implements TF-IDF and cosine similarity for tag name matching
 * **Image Similarity Search**: Uses CLIP embeddings to find visually similar tag images
+* **LLM Enhancement**: Optional LLM analysis for improved similarity filtering
 * **Metadata Extraction**: Provides appraisal values, years, and status information for similar tags
 
 ## Tech Stack
 
 * **Computer Vision**: CLIP or ViT models (free from Hugging Face)
 * **Text Processing**: TF-IDF vectorization and cosine similarity
+* **LLM Enhancement**: Groq LLaVA (optional)
 * **Backend**: Flask
 * **Image Processing**: Pillow, OpenCV
 * **Data Processing**: Pandas, NumPy, scikit-learn
@@ -128,13 +130,15 @@ def identify_tag(image_url):
 1. **Tag Identification**: Implement vision-based tag recognition using free models
 2. **Text Matching**: Use TF-IDF and cosine similarity for tag matching
 3. **Image Similarity**: Implement CLIP-based image embedding and search
-4. **Data Processing**: Handle image downloads and metadata extraction
-5. **API Design**: Create clean Flask endpoints with proper error handling
+4. **LLM Enhancement**: Add optional LLM analysis for better results
+5. **Data Processing**: Handle image downloads and metadata extraction
+6. **API Design**: Create clean Flask endpoints with proper error handling
 
 ## Data Sources
 
 * `tag_guides_clean.json`: Contains tag information with historical images and year ranges
 * `expert_data.csv`: Contains tag images with appraisal values, status, and metadata
+* `community_data.csv`: Contains tag images with appraisal values, status, and metadata
 
 ## Vision Model Options
 
@@ -144,4 +148,13 @@ You can use any of these free models from Hugging Face:
 - EasyOCR (text extraction)
 - ResNet (image classification)
 
-All models are available for free to use
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+## What Success Looks Like
+- ✅ Can extract text from tag images
+- ✅ Can match brands using TF-IDF similarity
+- ✅ Can find visually similar images
+- ✅ Optional: LLM enhances similarity analysis
+- ✅ Returns properly formatted JSON response
+- ✅ Response time under 60 seconds
+
+
+All models are available for free to use. Good Luck !
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