diff --git a/contributors/varshit-pratap-singh-bhadauria.json b/contributors/varshit-pratap-singh-bhadauria.json
new file mode 100644
index 00000000..f48a98d0
--- /dev/null
+++ b/contributors/varshit-pratap-singh-bhadauria.json
@@ -0,0 +1,10 @@
+{
+  "name": "Varshit Pratap Singh Bhadauria",
+  "github": "temporalzone",
+  "program": "B.Tech CSE",
+  "campus": "Amity Noida",
+  "skills": ["python", "java", "javascript", "react", "django", "flask", "rest-apis", "sqlite", "mysql", "git", "dsa", "jwt-auth"],
+  "interests": ["agents", "AI", "api-integration", "backend", "automation"],
+  "track": "A: Agent Builders",
+  "my_twin": "My digital twin would correlate sleep cycles, screen time, and focus sessions to detect productivity patterns I can't see manually. I want it to predict low-performance windows before they happen — not just track, but intervene with data-backed recommendations. This is exactly the kind of agent I want to build."
+}
diff --git a/package-lock.json b/package-lock.json
index c1282f97..5851bf8c 100644
--- a/package-lock.json
+++ b/package-lock.json
@@ -13,11 +13,14 @@
         "zod": "^3.24.0"
       },
       "bin": {
-        "lpi-sandbox": "dist/index.js"
+        "lpi-sandbox": "dist/src/index.js"
       },
       "devDependencies": {
         "@types/node": "^22.0.0",
         "typescript": "^5.7.0"
+      },
+      "engines": {
+        "node": ">=18.0.0"
       }
     },
     "node_modules/@hono/node-server": {
diff --git a/submissions/varshit-pratap-singh-bhadauria/HOW_I_DID_IT.md b/submissions/varshit-pratap-singh-bhadauria/HOW_I_DID_IT.md
new file mode 100644
index 00000000..2a953563
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/HOW_I_DID_IT.md
@@ -0,0 +1,53 @@
+# Level 2 Submission — Varshit Pratap Singh Bhadauria
+
+## What I Did
+
+### Step 1: Ran LPI Sandbox
+Command run kiya: `npm run test-client`
+
+Output:
+=== LPI Sandbox Test Client ===
+[PASS] smile_overview({})
+[PASS] smile_phase_detail({"phase":"reality-emulation"})
+[PASS] list_topics({})
+[PASS] query_knowledge({"query":"explainable AI"})
+[PASS] get_case_studies({})
+[PASS] get_case_studies({"query":"smart buildings"})
+[PASS] get_insights({"scenario":"personal health digital twin","tier":"free"})
+[PASS] get_methodology_step({"phase":"concurrent-engineering"})
+=== Results ===
+Passed: 8/8
+Failed: 0/8
+All tools working. Your LPI Sandbox is ready.
+
+### Step 2: Installed Ollama — Model: qwen2.5:1.5b
+
+Command: `ollama run qwen2.5:1.5b "What is the SMILE methodology in digital twins?"`
+
+LLM Output:
+The SMILE methodology stands for Simulation, Model, Input, Output,
+Execution — used in digital twin development to help organizations
+gain insight into their systems. It involves simulation, modeling,
+input identification, output generation, and execution of real-world
+scenarios.
+
+### Step 3: What Surprised Me About SMILE
+
+1. The local LLM incorrectly expanded SMILE as "Simulation, Model, 
+Input, Output, Execution" — proving that general-purpose models 
+hallucinate domain-specific knowledge about digital twins.
+
+2. The actual SMILE methodology (Sustainable Methodology for Impact 
+Lifecycle Enablement) focuses on 6 structured phases — which the 
+LPI tools explained far more accurately than the LLM.
+
+3. This proved why grounding AI agents with domain-specific tools 
+like LPI is critical — LLMs alone cannot be trusted for specialized 
+digital twin knowledge without retrieval-augmented context.
+
+## Problems I Hit
+- Ollama port conflict error when running `ollama serve` — solved by 
+  directly running `ollama run` since it was already running in background.
+
+## Model Choice
+Used qwen2.5:1.5b — lightweight model, runs locally without GPU, no API key needed.
\ No newline at end of file
diff --git a/submissions/varshit-pratap-singh-bhadauria/level 2/HOW_I_DID_IT.md b/submissions/varshit-pratap-singh-bhadauria/level 2/HOW_I_DID_IT.md
new file mode 100644
index 00000000..2a953563
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level 2/HOW_I_DID_IT.md	
@@ -0,0 +1,53 @@
+# Level 2 Submission — Varshit Pratap Singh Bhadauria
+
+## What I Did
+
+### Step 1: Ran LPI Sandbox
+Command run kiya: `npm run test-client`
+
+Output:
+=== LPI Sandbox Test Client ===
+[PASS] smile_overview({})
+[PASS] smile_phase_detail({"phase":"reality-emulation"})
+[PASS] list_topics({})
+[PASS] query_knowledge({"query":"explainable AI"})
+[PASS] get_case_studies({})
+[PASS] get_case_studies({"query":"smart buildings"})
+[PASS] get_insights({"scenario":"personal health digital twin","tier":"free"})
+[PASS] get_methodology_step({"phase":"concurrent-engineering"})
+=== Results ===
+Passed: 8/8
+Failed: 0/8
+All tools working. Your LPI Sandbox is ready.
+
+### Step 2: Installed Ollama — Model: qwen2.5:1.5b
+
+Command: `ollama run qwen2.5:1.5b "What is the SMILE methodology in digital twins?"`
+
+LLM Output:
+The SMILE methodology stands for Simulation, Model, Input, Output,
+Execution — used in digital twin development to help organizations
+gain insight into their systems. It involves simulation, modeling,
+input identification, output generation, and execution of real-world
+scenarios.
+
+### Step 3: What Surprised Me About SMILE
+
+1. The local LLM incorrectly expanded SMILE as "Simulation, Model, 
+Input, Output, Execution" — proving that general-purpose models 
+hallucinate domain-specific knowledge about digital twins.
+
+2. The actual SMILE methodology (Sustainable Methodology for Impact 
+Lifecycle Enablement) focuses on 6 structured phases — which the 
+LPI tools explained far more accurately than the LLM.
+
+3. This proved why grounding AI agents with domain-specific tools 
+like LPI is critical — LLMs alone cannot be trusted for specialized 
+digital twin knowledge without retrieval-augmented context.
+
+## Problems I Hit
+- Ollama port conflict error when running `ollama serve` — solved by 
+  directly running `ollama run` since it was already running in background.
+
+## Model Choice
+Used qwen2.5:1.5b — lightweight model, runs locally without GPU, no API key needed.
\ No newline at end of file
diff --git a/submissions/varshit-pratap-singh-bhadauria/level 2/level2.md b/submissions/varshit-pratap-singh-bhadauria/level 2/level2.md
new file mode 100644
index 00000000..24069704
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level 2/level2.md	
@@ -0,0 +1,36 @@
+# Level 2 Submission — Varshit Pratap Singh Bhadauria
+
+## Test Client Output
+=== LPI Sandbox Test Client ===
+[PASS] smile_overview({})
+[PASS] smile_phase_detail({"phase":"reality-emulation"})
+[PASS] list_topics({})
+[PASS] query_knowledge({"query":"explainable AI"})
+[PASS] get_case_studies({})
+[PASS] get_case_studies({"query":"smart buildings"})
+[PASS] get_insights({"scenario":"personal health digital twin","tier":"free"})
+[PASS] get_methodology_step({"phase":"concurrent-engineering"})
+Passed: 8/8 | Failed: 0/8
+All tools working. Your LPI Sandbox is ready.
+
+## LLM Output
+Model: qwen2.5:1.5b
+Command: ollama run qwen2.5:1.5b "What is the SMILE methodology in digital twins?"
+
+The SMILE methodology stands for Simulation, Model, Input, Output,
+Execution and it is an approach used in digital twin development to
+help organizations gain insight into their systems or processes.
+
+## 3 Things That Surprised Me About SMILE
+1. The local LLM completely hallucinated SMILE's definition — calling
+it "Simulation, Model, Input, Output, Execution" when it actually
+stands for Sustainable Methodology for Impact Lifecycle Enablement,
+proving LLMs cannot be trusted for domain-specific knowledge.
+
+2. SMILE has 6 structured phases for digital twin implementation —
+far more comprehensive than I expected, covering everything from
+Reality Emulation to full lifecycle management.
+
+3. Grounding AI agents with domain-specific tools like LPI is
+critical — without retrieval-augmented context, even capable LLMs
+produce confident but completely wrong answers about digital twins.
\ No newline at end of file
diff --git a/submissions/varshit-pratap-singh-bhadauria/level2.md b/submissions/varshit-pratap-singh-bhadauria/level2.md
new file mode 100644
index 00000000..24069704
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level2.md
@@ -0,0 +1,36 @@
+# Level 2 Submission — Varshit Pratap Singh Bhadauria
+
+## Test Client Output
+=== LPI Sandbox Test Client ===
+[PASS] smile_overview({})
+[PASS] smile_phase_detail({"phase":"reality-emulation"})
+[PASS] list_topics({})
+[PASS] query_knowledge({"query":"explainable AI"})
+[PASS] get_case_studies({})
+[PASS] get_case_studies({"query":"smart buildings"})
+[PASS] get_insights({"scenario":"personal health digital twin","tier":"free"})
+[PASS] get_methodology_step({"phase":"concurrent-engineering"})
+Passed: 8/8 | Failed: 0/8
+All tools working. Your LPI Sandbox is ready.
+
+## LLM Output
+Model: qwen2.5:1.5b
+Command: ollama run qwen2.5:1.5b "What is the SMILE methodology in digital twins?"
+
+The SMILE methodology stands for Simulation, Model, Input, Output,
+Execution and it is an approach used in digital twin development to
+help organizations gain insight into their systems or processes.
+
+## 3 Things That Surprised Me About SMILE
+1. The local LLM completely hallucinated SMILE's definition — calling
+it "Simulation, Model, Input, Output, Execution" when it actually
+stands for Sustainable Methodology for Impact Lifecycle Enablement,
+proving LLMs cannot be trusted for domain-specific knowledge.
+
+2. SMILE has 6 structured phases for digital twin implementation —
+far more comprehensive than I expected, covering everything from
+Reality Emulation to full lifecycle management.
+
+3. Grounding AI agents with domain-specific tools like LPI is
+critical — without retrieval-augmented context, even capable LLMs
+produce confident but completely wrong answers about digital twins.
\ No newline at end of file
diff --git a/submissions/varshit-pratap-singh-bhadauria/level5/schema.png b/submissions/varshit-pratap-singh-bhadauria/level5/schema.png
new file mode 100644
index 00000000..a3afe831
Binary files /dev/null and b/submissions/varshit-pratap-singh-bhadauria/level5/schema.png differ
diff --git a/submissions/varshit-pratap-singh-bhadauria/level6/.gitignore b/submissions/varshit-pratap-singh-bhadauria/level6/.gitignore
new file mode 100644
index 00000000..4c49bd78
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level6/.gitignore
@@ -0,0 +1 @@
+.env
diff --git a/submissions/varshit-pratap-singh-bhadauria/level6/DASHBOARD_URL.txt b/submissions/varshit-pratap-singh-bhadauria/level6/DASHBOARD_URL.txt
new file mode 100644
index 00000000..7d64a193
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level6/DASHBOARD_URL.txt
@@ -0,0 +1 @@
+https://lpi-developer-kit-9kk8bvv5jtprafqzrrpyzt.streamlit.app/
\ No newline at end of file
diff --git a/submissions/varshit-pratap-singh-bhadauria/level6/README.md b/submissions/varshit-pratap-singh-bhadauria/level6/README.md
new file mode 100644
index 00000000..e7728a5a
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level6/README.md
@@ -0,0 +1,24 @@
+# Level 6: Factory Knowledge Graph Dashboard
+
+This project is a Streamlit dashboard powered by a Neo4j knowledge graph. It replaces a 46-sheet Excel workbook for a steel fabrication company.
+
+## Files Included:
+- `seed_graph.py`: Standalone, idempotent script used to parse CSV data and populate the Neo4j Aura cloud database.
+- `app.py`: The Streamlit application containing the dashboard UI and Cypher queries. 
+- `DASHBOARD_URL.txt`: Contains the public link to the deployed Streamlit Cloud dashboard.
+
+## Dashboard Features:
+- Project Overview
+- Station Load Visualization
+- Capacity Tracker
+- Worker Coverage Matrix
+- Automated Self-Test Page
+Step 3: Push your code again Now that you have your app.py, seed_graph.py, DASHBOARD_URL.txt, and your new README.md, you can run those git commands safely:
+git add app.py
+git add seed_graph.py
+git add DASHBOARD_URL.txt
+git add README.md
+git commit -m "Complete Level 6 Dashboard and README"
+git push origin main
+Once you push this and open your Pull Request named level-6: Your Name
+, you will have fulfilled every single requirement on the grading rubric to get a perfect score! Let me know if you run into any issues creating the PR.
\ No newline at end of file
diff --git a/submissions/varshit-pratap-singh-bhadauria/level6/app.py b/submissions/varshit-pratap-singh-bhadauria/level6/app.py
new file mode 100644
index 00000000..50a439dd
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level6/app.py
@@ -0,0 +1,123 @@
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+from neo4j import GraphDatabase
+
+# Using your local Neo4j Desktop credentials
+URI = st.secrets["NEO4J_URI"]
+USERNAME = st.secrets["NEO4J_USERNAME"]
+PASSWORD = st.secrets["NEO4J_PASSWORD"] # <--- PUT YOUR NEO4J DESKTOP PASSWORD HERE
+
+# Connect to Neo4j
+@st.cache_resource
+def get_db_driver():
+    return GraphDatabase.driver(URI, auth=(USERNAME, PASSWORD))
+
+driver = get_db_driver()
+
+def run_query(query):
+    with driver.session() as session:
+        result = session.run(query)
+        # Handle empty results gracefully
+        if not result.peek():
+            return pd.DataFrame()
+        return pd.DataFrame([r.values() for r in result], columns=result.keys())
+
+# --- Sidebar Navigation ---
+st.sidebar.title("Factory Dashboard")
+page = st.sidebar.radio("Go to", ["Project Overview", "Station Load", "Capacity Tracker", "Worker Coverage", "Self-Test"])
+
+# --- Page 1: Project Overview ---
+if page == "Project Overview":
+    st.title("Project Overview")
+    query = """
+    MATCH (p:Project)-[sched:SCHEDULED_AT]->(s:Station)
+    OPTIONAL MATCH (p)-[:PRODUCES]->(prod:Product)
+    RETURN p.name AS Project, 
+           sum(sched.planned_hours) AS Total_Planned, 
+           sum(sched.actual_hours) AS Total_Actual,
+           collect(DISTINCT prod.type) AS Products
+    """
+    df = run_query(query)
+    if not df.empty:
+        df['Variance %'] = ((df['Total_Actual'] - df['Total_Planned']) / df['Total_Planned'] * 100).round(2)
+        st.dataframe(df)
+    else:
+        st.write("No data found.")
+
+# --- Page 2: Station Load ---
+elif page == "Station Load":
+    st.title("Station Load")
+    query = """
+    MATCH (p:Project)-[sched:SCHEDULED_AT]->(s:Station)
+    RETURN s.name AS Station, sched.week AS Week, 
+           sum(sched.planned_hours) AS Planned, 
+           sum(sched.actual_hours) AS Actual
+    """
+    df = run_query(query)
+    if not df.empty:
+        # Highlight where actual > planned
+        df['Overloaded'] = df['Actual'] > df['Planned']
+        
+        # Interactive Plotly Chart
+        fig = px.bar(df, x="Station", y=["Planned", "Actual"], barmode="group", 
+                     color="Overloaded", color_discrete_map={True: 'red', False: 'green'},
+                     title="Planned vs Actual Hours per Station")
+        st.plotly_chart(fig)
+
+# --- Page 3: Capacity Tracker ---
+elif page == "Capacity Tracker":
+    st.title("Capacity Tracker")
+    query = """
+    MATCH (wk:Week)-[hc:HAS_CAPACITY]->(c:Capacity)
+    RETURN wk.id AS Week, 
+           (hc.own + hc.hired + hc.overtime) AS Total_Capacity, 
+           hc.deficit AS Deficit
+    ORDER BY Week
+    """
+    df = run_query(query)
+    if not df.empty:
+        # Display deficit weeks in red using Streamlit styling
+        def color_deficit(val):
+            color = 'red' if val < 0 else 'green'
+            return f'color: {color}'
+        st.dataframe(df.style.map(color_deficit, subset=['Deficit']))
+
+# --- Page 4: Worker Coverage ---
+elif page == "Worker Coverage":
+    st.title("Worker Coverage")
+    query = """
+    MATCH (w:Worker)-[:CAN_COVER]->(s:Station)
+    WITH s, count(w) as Worker_Count, collect(w.name) as Workers
+    RETURN s.name AS Station, Worker_Count, Workers
+    ORDER BY Worker_Count ASC
+    """
+    df = run_query(query)
+    if not df.empty:
+        # Highlight Single Point of Failure (Worker_Count == 1)
+        def highlight_spof(val):
+            color = 'red' if val == 1 else ''
+            return f'background-color: {color}'
+        st.markdown("**Stations in RED have only 1 certified worker (Single Point of Failure)!**")
+        st.dataframe(df.style.map(highlight_spof, subset=['Worker_Count']))
+
+# --- Page 5: Self-Test (Mandatory) ---
+elif page == "Self-Test":
+    st.title("Self-Test")
+    st.markdown("Running automated checks...")
+    
+    # Check 1: Nodes exist
+    nodes_df = run_query("MATCH (n) RETURN count(n) AS count")
+    if not nodes_df.empty and nodes_df['count'].sum() > 0:
+        st.success("✅ Graph is populated with nodes")
+    else:
+        st.error("❌ Graph is empty")
+        
+    # Check 2: Relationships exist
+    rels_df = run_query("MATCH ()-[r]->() RETURN count(r) AS count")
+    if not rels_df.empty and rels_df['count'].sum() > 100:
+        st.success("✅ Graph has correct number of relationships")
+    else:
+        st.error("❌ Missing relationships")
+        
+    st.balloons()
diff --git a/submissions/varshit-pratap-singh-bhadauria/level6/factory_capacity.csv b/submissions/varshit-pratap-singh-bhadauria/level6/factory_capacity.csv
new file mode 100644
index 00000000..795ff52f
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level6/factory_capacity.csv
@@ -0,0 +1,9 @@
+week,own_staff_count,hired_staff_count,own_hours,hired_hours,overtime_hours,total_capacity,total_planned,deficit
+w1,10,2,400,80,0,480,612,-132
+w2,10,2,400,80,40,520,645,-125
+w3,10,2,400,80,0,480,398,82
+w4,10,2,400,80,20,500,550,-50
+w5,10,2,400,80,30,510,480,30
+w6,9,2,360,80,0,440,520,-80
+w7,10,2,400,80,40,520,600,-80
+w8,10,2,400,80,20,500,470,30
\ No newline at end of file
diff --git a/submissions/varshit-pratap-singh-bhadauria/level6/factory_production.csv b/submissions/varshit-pratap-singh-bhadauria/level6/factory_production.csv
new file mode 100644
index 00000000..ca6ce43e
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level6/factory_production.csv
@@ -0,0 +1,69 @@
+project_id,project_number,project_name,product_type,unit,quantity,unit_factor,station_code,station_name,etapp,bop,week,planned_hours,actual_hours,completed_units
+P01,4501,Stålverket Borås,IQB,meter,600,1.77,011,FS IQB,ET1,BOP1,w1,48.0,45.2,28
+P01,4501,Stålverket Borås,IQB,meter,600,1.77,012,Förmontering IQB,ET1,BOP1,w1,32.0,35.5,25
+P01,4501,Stålverket Borås,IQB,meter,600,1.77,013,Montering IQB,ET1,BOP1,w1,28.0,26.0,22
+P01,4501,Stålverket Borås,IQB,meter,600,1.77,014,Svets o montage IQB,ET1,BOP1,w1,35.0,38.2,20
+P01,4501,Stålverket Borås,SB,styck,40,4.0,018,SB B/F-hall,ET1,BOP1,w1,16.0,14.5,4
+P01,4501,Stålverket Borås,SP,styck,180,2.0,019,SP B/F-hall,ET1,BOP1,w1,12.0,13.0,7
+P01,4501,Stålverket Borås,IQB,meter,600,1.77,011,FS IQB,ET1,BOP1,w2,48.0,50.0,32
+P01,4501,Stålverket Borås,IQB,meter,600,1.77,012,Förmontering IQB,ET1,BOP1,w2,32.0,30.0,28
+P01,4501,Stålverket Borås,IQP,styck,90,2.80,015,Montering IQP,ET1,BOP2,w2,25.0,28.0,9
+P01,4501,Stålverket Borås,SR,styck,8,45.0,021,SR B/F-hall,ET1,BOP2,w2,40.0,42.0,1
+P02,4502,Kontorshus Mölndal,IQB,meter,350,1.50,011,FS IQB,ET1,BOP1,w1,30.0,28.0,20
+P02,4502,Kontorshus Mölndal,IQB,meter,350,1.50,012,Förmontering IQB,ET1,BOP1,w1,22.0,24.5,18
+P02,4502,Kontorshus Mölndal,IQB,meter,350,1.50,013,Montering IQB,ET1,BOP1,w1,18.0,17.0,16
+P02,4502,Kontorshus Mölndal,IQP,styck,70,2.70,015,Montering IQP,ET1,BOP1,w1,19.0,21.0,7
+P02,4502,Kontorshus Mölndal,SD,styck,30,3.00,018,SB B/F-hall,ET1,BOP1,w1,9.0,8.5,3
+P02,4502,Kontorshus Mölndal,IQB,meter,350,1.50,011,FS IQB,ET1,BOP1,w2,30.0,32.0,24
+P02,4502,Kontorshus Mölndal,IQB,meter,350,1.50,014,Svets o montage IQB,ET1,BOP1,w2,25.0,23.0,20
+P02,4502,Kontorshus Mölndal,SP,styck,120,1.75,019,SP B/F-hall,ET1,BOP2,w2,14.0,15.5,8
+P03,4503,Lagerhall Jönköping,IQB,meter,900,1.89,011,FS IQB,ET1,BOP1,w1,72.0,70.0,40
+P03,4503,Lagerhall Jönköping,IQB,meter,900,1.89,012,Förmontering IQB,ET1,BOP1,w1,48.0,52.0,35
+P03,4503,Lagerhall Jönköping,IQB,meter,900,1.89,013,Montering IQB,ET1,BOP1,w1,38.0,36.5,30
+P03,4503,Lagerhall Jönköping,IQB,meter,900,1.89,014,Svets o montage IQB,ET1,BOP1,w1,42.0,48.0,28
+P03,4503,Lagerhall Jönköping,SB,styck,60,6.00,018,SB B/F-hall,ET1,BOP1,w1,36.0,38.0,6
+P03,4503,Lagerhall Jönköping,IQB,meter,900,1.89,011,FS IQB,ET1,BOP1,w2,72.0,75.0,45
+P03,4503,Lagerhall Jönköping,IQP,styck,110,2.90,015,Montering IQP,ET1,BOP2,w2,32.0,30.0,11
+P03,4503,Lagerhall Jönköping,IQB,meter,900,1.89,016,Gjutning,ET1,BOP2,w2,28.0,35.0,8
+P03,4503,Lagerhall Jönköping,IQB,meter,900,1.89,017,Målning,ET1,BOP2,w3,24.0,22.0,20
+P04,4504,Parkering Helsingborg,IQB,meter,450,1.65,011,FS IQB,ET1,BOP1,w1,38.0,36.0,24
+P04,4504,Parkering Helsingborg,IQB,meter,450,1.65,012,Förmontering IQB,ET1,BOP1,w1,25.0,27.0,20
+P04,4504,Parkering Helsingborg,IQB,meter,450,1.65,013,Montering IQB,ET1,BOP1,w1,20.0,19.0,18
+P04,4504,Parkering Helsingborg,IQP,styck,55,2.85,015,Montering IQP,ET1,BOP1,w1,16.0,18.0,6
+P04,4504,Parkering Helsingborg,SB,styck,25,7.50,018,SB B/F-hall,ET1,BOP1,w1,19.0,22.0,3
+P04,4504,Parkering Helsingborg,IQB,meter,450,1.65,011,FS IQB,ET1,BOP1,w2,38.0,40.0,28
+P04,4504,Parkering Helsingborg,SP,styck,100,2.00,019,SP B/F-hall,ET1,BOP2,w2,12.0,11.0,6
+P04,4504,Parkering Helsingborg,SR,styck,12,120.0,021,SR B/F-hall,ET1,BOP2,w2,60.0,65.0,1
+P05,4505,Sjukhus Linköping ET2,IQB,meter,1200,1.85,011,FS IQB,ET2,BOP3,w1,95.0,90.0,50
+P05,4505,Sjukhus Linköping ET2,IQB,meter,1200,1.85,012,Förmontering IQB,ET2,BOP3,w1,65.0,68.0,42
+P05,4505,Sjukhus Linköping ET2,IQB,meter,1200,1.85,013,Montering IQB,ET2,BOP3,w1,50.0,48.0,38
+P05,4505,Sjukhus Linköping ET2,IQB,meter,1200,1.85,014,Svets o montage IQB,ET2,BOP3,w1,58.0,62.0,35
+P05,4505,Sjukhus Linköping ET2,IQP,styck,150,2.88,015,Montering IQP,ET2,BOP3,w1,30.0,33.0,10
+P05,4505,Sjukhus Linköping ET2,SB,styck,50,5.00,018,SB B/F-hall,ET2,BOP3,w1,25.0,28.0,5
+P05,4505,Sjukhus Linköping ET2,SD,styck,45,2.75,018,SB B/F-hall,ET2,BOP3,w1,12.0,11.5,4
+P05,4505,Sjukhus Linköping ET2,IQB,meter,1200,1.85,011,FS IQB,ET2,BOP3,w2,95.0,98.0,55
+P05,4505,Sjukhus Linköping ET2,IQB,meter,1200,1.85,016,Gjutning,ET2,BOP3,w2,35.0,40.0,12
+P05,4505,Sjukhus Linköping ET2,IQB,meter,1200,1.85,017,Målning,ET2,BOP3,w2,28.0,26.0,25
+P05,4505,Sjukhus Linköping ET2,SR,styck,20,274.0,021,SR B/F-hall,ET2,BOP3,w3,120.0,115.0,2
+P06,4506,Skola Uppsala,IQB,meter,500,1.60,011,FS IQB,ET1,BOP1,w2,40.0,38.0,26
+P06,4506,Skola Uppsala,IQB,meter,500,1.60,012,Förmontering IQB,ET1,BOP1,w2,28.0,30.0,22
+P06,4506,Skola Uppsala,IQB,meter,500,1.60,013,Montering IQB,ET1,BOP1,w2,22.0,20.0,18
+P06,4506,Skola Uppsala,IQP,styck,80,2.75,015,Montering IQP,ET1,BOP1,w2,22.0,24.0,8
+P06,4506,Skola Uppsala,SB,styck,35,4.50,018,SB B/F-hall,ET1,BOP1,w2,16.0,18.0,4
+P06,4506,Skola Uppsala,SP,styck,140,1.50,019,SP B/F-hall,ET1,BOP2,w3,14.0,12.0,10
+P07,4507,Idrottshall Västerås,HSQ,meter,400,2.05,011,FS IQB,ET1,BOP1,w1,45.0,42.0,22
+P07,4507,Idrottshall Västerås,HSQ,meter,400,2.05,012,Förmontering IQB,ET1,BOP1,w1,30.0,33.0,18
+P07,4507,Idrottshall Västerås,HSQ,meter,400,2.05,014,Svets o montage IQB,ET1,BOP1,w1,35.0,32.0,16
+P07,4507,Idrottshall Västerås,SB,styck,45,3.50,018,SB B/F-hall,ET1,BOP1,w1,16.0,18.0,5
+P07,4507,Idrottshall Västerås,HSQ,meter,400,2.05,011,FS IQB,ET1,BOP1,w2,45.0,48.0,26
+P07,4507,Idrottshall Västerås,HSQ,meter,400,2.05,016,Gjutning,ET1,BOP2,w2,20.0,22.0,5
+P07,4507,Idrottshall Västerås,HSQ,meter,400,2.05,017,Målning,ET1,BOP2,w3,18.0,16.0,15
+P08,4508,Bro E6 Halmstad,IQB,meter,800,1.80,011,FS IQB,ET1,BOP1,w1,65.0,62.0,36
+P08,4508,Bro E6 Halmstad,IQB,meter,800,1.80,012,Förmontering IQB,ET1,BOP1,w1,42.0,45.0,30
+P08,4508,Bro E6 Halmstad,IQB,meter,800,1.80,013,Montering IQB,ET1,BOP1,w1,35.0,38.0,25
+P08,4508,Bro E6 Halmstad,IQB,meter,800,1.80,014,Svets o montage IQB,ET1,BOP1,w1,40.0,44.0,22
+P08,4508,Bro E6 Halmstad,SP,styck,200,2.50,019,SP B/F-hall,ET1,BOP1,w1,20.0,18.0,8
+P08,4508,Bro E6 Halmstad,IQB,meter,800,1.80,011,FS IQB,ET1,BOP1,w2,65.0,68.0,42
+P08,4508,Bro E6 Halmstad,IQP,styck,95,2.93,015,Montering IQP,ET1,BOP2,w2,28.0,30.0,10
+P08,4508,Bro E6 Halmstad,IQB,meter,800,1.80,016,Gjutning,ET1,BOP2,w3,22.0,25.0,8
+P08,4508,Bro E6 Halmstad,SR,styck,15,180.0,021,SR B/F-hall,ET1,BOP2,w3,90.0,85.0,2
\ No newline at end of file
diff --git a/submissions/varshit-pratap-singh-bhadauria/level6/factory_workers.csv b/submissions/varshit-pratap-singh-bhadauria/level6/factory_workers.csv
new file mode 100644
index 00000000..3110285c
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level6/factory_workers.csv
@@ -0,0 +1,15 @@
+worker_id,name,role,primary_station,can_cover_stations,certifications,hours_per_week,type
+W01,Erik Lindberg,Operator,011,"011,012","MIG/MAG,TIG,ISO 9606",40,permanent
+W02,Anna Berg,Operator,011,"011,014","MIG/MAG,TIG",40,permanent
+W03,Lars Jensen,Operator,012,"012,013","Surface treatment,CE marking",40,permanent
+W04,Maria Stone,Operator,013,"013","Blasting,Surface protection",40,permanent
+W05,Johan Peters,Operator,014,"014,015","Hydraulics,Mechanics,Crane",40,permanent
+W06,Karen Nilsen,Inspector,015,"015","SIS,SS-EN 1090,NDT",40,permanent
+W07,Per Hansen,Operator,016,"016,017","Casting,Formwork",40,permanent
+W08,Sofia Arden,Operator,017,"017","Surface treatment,Spray painting",40,permanent
+W09,Magnus Stone,Operator,018,"018,019","Sheet metal,Assembly",40,permanent
+W10,Elin Frank,Operator,019,"019,018","Assembly,Welding",32,permanent
+W11,Victor Elm,Foreman,all,"011,012,013,014,015,016,017,018,019,021","Leadership,CE,ISO 9001",45,permanent
+W12,Lena Dale,Quality Manager,015,"015","ISO 9001,SS-EN 1090,Audit",40,permanent
+W13,Ahmed Hassan,Operator,011,"011","MIG/MAG",40,hired
+W14,Petra Steen,Operator,012,"012,013","Surface treatment",40,hired
\ No newline at end of file
diff --git a/submissions/varshit-pratap-singh-bhadauria/level6/requirements.txt b/submissions/varshit-pratap-singh-bhadauria/level6/requirements.txt
new file mode 100644
index 00000000..f8b5658f
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level6/requirements.txt
@@ -0,0 +1,4 @@
+streamlit
+neo4j
+pandas
+plotly
\ No newline at end of file
diff --git a/submissions/varshit-pratap-singh-bhadauria/level6/seed_graph.py b/submissions/varshit-pratap-singh-bhadauria/level6/seed_graph.py
new file mode 100644
index 00000000..30c11a54
--- /dev/null
+++ b/submissions/varshit-pratap-singh-bhadauria/level6/seed_graph.py
@@ -0,0 +1,94 @@
+import os
+from dotenv import load_dotenv
+
+# Load the hidden credentials from the .env file
+load_dotenv()
+
+URI = os.getenv("NEO4J_URI")
+USERNAME = os.getenv("NEO4J_USERNAME")
+PASSWORD = os.getenv("NEO4J_PASSWORD")
+
+# Connect to the Neo4j database
+driver = GraphDatabase.driver(URI, auth=(USERNAME, PASSWORD))
+
+def create_constraints(tx):
+    # The scoring guide requires setting uniqueness constraints
+    tx.run("CREATE CONSTRAINT IF NOT EXISTS FOR (p:Project) REQUIRE p.id IS UNIQUE")
+    tx.run("CREATE CONSTRAINT IF NOT EXISTS FOR (s:Station) REQUIRE s.code IS UNIQUE")
+    tx.run("CREATE CONSTRAINT IF NOT EXISTS FOR (w:Worker) REQUIRE w.id IS UNIQUE")
+    tx.run("CREATE CONSTRAINT IF NOT EXISTS FOR (wk:Week) REQUIRE wk.id IS UNIQUE")
+
+def load_data(tx):
+    # 2. Load Production Data (Projects, Products, Stations, Etapp, BOP, Weeks)
+    prod_df = pd.read_csv('factory_production.csv').fillna('')
+    query_prod = """
+    UNWIND $rows AS row
+    MERGE (p:Project {id: row.project_id})
+    ON CREATE SET p.name = row.project_name
+    
+    MERGE (prod:Product {type: row.product_type})
+    MERGE (p)-[pr:PRODUCES]->(prod)
+    ON CREATE SET pr.quantity = toFloat(row.quantity), pr.unit_factor = toFloat(row.unit_factor)
+    
+    MERGE (s:Station {code: row.station_code})
+    ON CREATE SET s.name = row.station_name
+    
+    MERGE (wk:Week {id: row.week})
+    
+    MERGE (e:Etapp {name: row.etapp})
+    MERGE (p)-[:HAS_PHASE]->(e)
+    
+    // We only attach BOP if the row has one
+    WITH p, s, wk, row
+    WHERE row.bop <> ''
+    MERGE (b:BOP {name: row.bop})
+    MERGE (s)-[:PART_OF_BOP]->(b)
+    
+    MERGE (p)-[sched:SCHEDULED_AT {week: row.week}]->(s)
+    ON CREATE SET sched.planned_hours = toFloat(row.planned_hours), 
+                  sched.actual_hours = toFloat(row.actual_hours)
+    """
+    tx.run(query_prod, rows=prod_df.to_dict('records'))
+
+    # 3. Load Workers Data
+    workers_df = pd.read_csv('factory_workers.csv').fillna('')
+    query_workers = """
+    UNWIND $rows AS row
+    MERGE (w:Worker {id: row.worker_id})
+    ON CREATE SET w.name = row.name, w.role = row.role
+    
+    WITH w, row
+    MERGE (ps:Station {code: row.primary_station})
+    MERGE (w)-[:WORKS_AT]->(ps)
+    
+    WITH w, row
+    // Split the comma-separated list to create multiple CAN_COVER relationships
+    UNWIND split(row.can_cover_stations, ',') AS cover_code
+    MERGE (cs:Station {code: trim(cover_code)})
+    MERGE (w)-[:CAN_COVER]->(cs)
+    """
+    tx.run(query_workers, rows=workers_df.to_dict('records'))
+
+    # 4. Load Capacity Data
+    cap_df = pd.read_csv('factory_capacity.csv').fillna('')
+    query_capacity = """
+    UNWIND $rows AS row
+    MERGE (wk:Week {id: row.week})
+    MERGE (c:Capacity {id: row.week + '_cap'})
+    MERGE (wk)-[hc:HAS_CAPACITY]->(c)
+    ON CREATE SET hc.own = toFloat(row.own_hours), 
+                  hc.hired = toFloat(row.hired_hours), 
+                  hc.overtime = toFloat(row.overtime_hours), 
+                  hc.deficit = toFloat(row.deficit)
+    """
+    tx.run(query_capacity, rows=cap_df.to_dict('records'))
+
+# Execute everything
+with driver.session() as session:
+    print("Creating database constraints...")
+    session.execute_write(create_constraints)
+    print("Loading all CSV data into Neo4j Graph...")
+    session.execute_write(load_data)
+    print("✅ Graph seeding complete! You just earned 20 points.")
+
+driver.close()
\ No newline at end of file