Update README.md

README.md

@@ -1,14 +1,51 @@
 ---
-title: GroundTruth AI
-emoji: 🏃
+title: GroundTruth
+emoji: 🏠
 colorFrom: blue
-colorTo: pink
+colorTo: blue
 sdk: gradio
-sdk_version: 6.6.0
+sdk_version: 5.16.0
 app_file: app.py
-pinned: false
+pinned: true
 license: apache-2.0
-short_description: Ground Truth is a spatial awareness platform
+tags:
+- real-estate
+- spatial-reasoning
+- robotics-ai
+- gemini-api
+- proptech
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# GroundTruth: Temporal Property Sentinel
+**A High-Fidelity Spatial Reasoning Engine for Real Estate Analysis**
+
+## Project Overview
+GroundTruth is an analytical platform designed to provide "Spatial Truth" in property valuation and assessment. By utilizing the **Google Gemini Robotics-ER 1.5** model, this application moves beyond standard object detection to perform forensic, multi-period structural audits.
+
+## Why Robotics-ER 1.5?
+Standard Vision-Language Models (VLMs) are trained to identify *what* is in an image (e.g., "a house with a lawn"). GroundTruth uses the Robotics-ER 1.5 API because it is specifically optimized for **Embodied Reasoning**—the ability to understand physical structure, depth, and spatial relationships as they unfold across time.
+
+### Key Technical Advantages:
+* **Spatial Accuracy:** Outperforms standard models (like Gemini Flash) in 3D detection and precise pointing tasks, which is critical for identifying specific structural defects like roof sagging or foundation cracks.
+* **Temporal Reasoning:** Natively understands cause-and-effect relationships and sequences of events. It doesn't just see two photos; it reasons about the *maintenance trajectory* between them.
+* **Physical World Logic:** Trained on robotic interaction data, the model understands "affordances"—the physical possibilities of a space (e.g., whether a wall is likely load-bearing based on its position).
+
+## Features
+* **Side-by-Side Forensic Audit:** Compare historical and present-day imagery to identify capital improvements or systemic neglect.
+* **Maintenance Trajectory Scoring:** Automated classification of a property as "Improving," "Stable," or "Declining" based on visual structural evidence.
+* **High-Budget Thinking:** Utilizes the model's tunable thinking budget to prioritize forensic accuracy over simple latency for complex structural questions.
+
+## Intended Use
+* **Real Estate Agents:** Automating "Pride of Ownership" reports for listing presentations.
+* **Investors:** Remote due diligence and asset condition monitoring over time.
+* **Compliance Officers:** Identifying unauthorized additions or zoning violations via historical imagery comparison.
+
+## Limitations & Disclaimers
+* **Vision-Only:** Analysis is based on exterior visual data; it cannot "see" internal structural integrity or hidden plumbing/electrical issues.
+* **Safety:** While optimized for physical reasoning, all AI outputs should be verified by a licensed human inspector before financial or safety decisions are made.
+
+## License
+This project is licensed under the **Apache License 2.0**, providing explicit patent protection and commercial flexibility for the Real Estate tech ecosystem.
+
+---
+*Created by Evan Bench — Google AI Architect*