diff --git a/data/_catalog/manifests/021ac283-883b-4b13-83ce-5395bacdc33a.json b/data/_catalog/manifests/021ac283-883b-4b13-83ce-5395bacdc33a.json
new file mode 100644
index 0000000..89d98ae
--- /dev/null
+++ b/data/_catalog/manifests/021ac283-883b-4b13-83ce-5395bacdc33a.json
@@ -0,0 +1,15 @@
+{
+  "id": "021ac283-883b-4b13-83ce-5395bacdc33a",
+  "name": "clients",
+  "schema_fingerprint": "auto",
+  "objects": [
+    {
+      "bucket": "data",
+      "key": "datasets/clients.parquet",
+      "size_bytes": 21971,
+      "created_at": "2026-03-27T13:15:18.000750302Z"
+    }
+  ],
+  "created_at": "2026-03-27T13:15:18.000757845Z",
+  "updated_at": "2026-03-27T13:15:18.000757845Z"
+}
\ No newline at end of file
diff --git a/data/_catalog/manifests/052cf81b-f5b6-4439-92d7-ecf09b24bd8b.json b/data/_catalog/manifests/052cf81b-f5b6-4439-92d7-ecf09b24bd8b.json
new file mode 100644
index 0000000..96de7c0
--- /dev/null
+++ b/data/_catalog/manifests/052cf81b-f5b6-4439-92d7-ecf09b24bd8b.json
@@ -0,0 +1,15 @@
+{
+  "id": "052cf81b-f5b6-4439-92d7-ecf09b24bd8b",
+  "name": "candidates",
+  "schema_fingerprint": "auto",
+  "objects": [
+    {
+      "bucket": "data",
+      "key": "datasets/candidates.parquet",
+      "size_bytes": 10592165,
+      "created_at": "2026-03-27T13:15:17.989860994Z"
+    }
+  ],
+  "created_at": "2026-03-27T13:15:17.989869155Z",
+  "updated_at": "2026-03-27T13:15:17.989869155Z"
+}
\ No newline at end of file
diff --git a/data/_catalog/manifests/0927b27a-80a9-4790-a34f-bda7ff176aac.json b/data/_catalog/manifests/0927b27a-80a9-4790-a34f-bda7ff176aac.json
deleted file mode 100644
index f2e6c91..0000000
--- a/data/_catalog/manifests/0927b27a-80a9-4790-a34f-bda7ff176aac.json
+++ /dev/null
@@ -1,15 +0,0 @@
-{
-  "id": "0927b27a-80a9-4790-a34f-bda7ff176aac",
-  "name": "job_orders",
-  "schema_fingerprint": "auto",
-  "objects": [
-    {
-      "bucket": "data",
-      "key": "datasets/job_orders.parquet",
-      "size_bytes": 225889,
-      "created_at": "2026-03-27T13:11:41.384341257Z"
-    }
-  ],
-  "created_at": "2026-03-27T13:11:41.384344032Z",
-  "updated_at": "2026-03-27T13:11:41.384344032Z"
-}
\ No newline at end of file
diff --git a/data/_catalog/manifests/0bf1eb1f-b182-4025-9b44-b8553e678bcf.json b/data/_catalog/manifests/0bf1eb1f-b182-4025-9b44-b8553e678bcf.json
deleted file mode 100644
index ed940e9..0000000
--- a/data/_catalog/manifests/0bf1eb1f-b182-4025-9b44-b8553e678bcf.json
+++ /dev/null
@@ -1,15 +0,0 @@
-{
-  "id": "0bf1eb1f-b182-4025-9b44-b8553e678bcf",
-  "name": "timesheets",
-  "schema_fingerprint": "auto",
-  "objects": [
-    {
-      "bucket": "data",
-      "key": "datasets/timesheets.parquet",
-      "size_bytes": 2458229,
-      "created_at": "2026-03-27T13:11:42.084209718Z"
-    }
-  ],
-  "created_at": "2026-03-27T13:11:42.084217486Z",
-  "updated_at": "2026-03-27T13:11:42.084217486Z"
-}
\ No newline at end of file
diff --git a/data/_catalog/manifests/47756b77-9a2e-476c-8249-9b971f95fb2d.json b/data/_catalog/manifests/47756b77-9a2e-476c-8249-9b971f95fb2d.json
new file mode 100644
index 0000000..5ec264f
--- /dev/null
+++ b/data/_catalog/manifests/47756b77-9a2e-476c-8249-9b971f95fb2d.json
@@ -0,0 +1,15 @@
+{
+  "id": "47756b77-9a2e-476c-8249-9b971f95fb2d",
+  "name": "call_log",
+  "schema_fingerprint": "auto",
+  "objects": [
+    {
+      "bucket": "data",
+      "key": "datasets/call_log.parquet",
+      "size_bytes": 35951077,
+      "created_at": "2026-03-27T13:15:26.607093971Z"
+    }
+  ],
+  "created_at": "2026-03-27T13:15:26.607099665Z",
+  "updated_at": "2026-03-27T13:15:26.607099665Z"
+}
\ No newline at end of file
diff --git a/data/_catalog/manifests/4be87c74-10b4-463c-b69d-f20c9cd18ed7.json b/data/_catalog/manifests/4be87c74-10b4-463c-b69d-f20c9cd18ed7.json
deleted file mode 100644
index 66bae07..0000000
--- a/data/_catalog/manifests/4be87c74-10b4-463c-b69d-f20c9cd18ed7.json
+++ /dev/null
@@ -1,15 +0,0 @@
-{
-  "id": "4be87c74-10b4-463c-b69d-f20c9cd18ed7",
-  "name": "candidates",
-  "schema_fingerprint": "auto",
-  "objects": [
-    {
-      "bucket": "data",
-      "key": "datasets/candidates.parquet",
-      "size_bytes": 2003395,
-      "created_at": "2026-03-27T13:11:41.341589905Z"
-    }
-  ],
-  "created_at": "2026-03-27T13:11:41.341599187Z",
-  "updated_at": "2026-03-27T13:11:41.341599187Z"
-}
\ No newline at end of file
diff --git a/data/_catalog/manifests/75bb6855-488b-4300-89c2-970871bd99cc.json b/data/_catalog/manifests/75bb6855-488b-4300-89c2-970871bd99cc.json
deleted file mode 100644
index 42e9bd8..0000000
--- a/data/_catalog/manifests/75bb6855-488b-4300-89c2-970871bd99cc.json
+++ /dev/null
@@ -1,15 +0,0 @@
-{
-  "id": "75bb6855-488b-4300-89c2-970871bd99cc",
-  "name": "email_log",
-  "schema_fingerprint": "auto",
-  "objects": [
-    {
-      "bucket": "data",
-      "key": "datasets/email_log.parquet",
-      "size_bytes": 1873775,
-      "created_at": "2026-03-27T13:11:42.757205427Z"
-    }
-  ],
-  "created_at": "2026-03-27T13:11:42.757211105Z",
-  "updated_at": "2026-03-27T13:11:42.757211105Z"
-}
\ No newline at end of file
diff --git a/data/_catalog/manifests/ad393eee-ba0c-4338-9a8b-236bba3816ac.json b/data/_catalog/manifests/ad393eee-ba0c-4338-9a8b-236bba3816ac.json
deleted file mode 100644
index 965ad63..0000000
--- a/data/_catalog/manifests/ad393eee-ba0c-4338-9a8b-236bba3816ac.json
+++ /dev/null
@@ -1,15 +0,0 @@
-{
-  "id": "ad393eee-ba0c-4338-9a8b-236bba3816ac",
-  "name": "placements",
-  "schema_fingerprint": "auto",
-  "objects": [
-    {
-      "bucket": "data",
-      "key": "datasets/placements.parquet",
-      "size_bytes": 217395,
-      "created_at": "2026-03-27T13:11:41.433628136Z"
-    }
-  ],
-  "created_at": "2026-03-27T13:11:41.433633927Z",
-  "updated_at": "2026-03-27T13:11:41.433633927Z"
-}
\ No newline at end of file
diff --git a/data/_catalog/manifests/b334b1eb-d7a2-473f-a7fa-017b17de74bd.json b/data/_catalog/manifests/b334b1eb-d7a2-473f-a7fa-017b17de74bd.json
deleted file mode 100644
index 502653a..0000000
--- a/data/_catalog/manifests/b334b1eb-d7a2-473f-a7fa-017b17de74bd.json
+++ /dev/null
@@ -1,15 +0,0 @@
-{
-  "id": "b334b1eb-d7a2-473f-a7fa-017b17de74bd",
-  "name": "clients",
-  "schema_fingerprint": "auto",
-  "objects": [
-    {
-      "bucket": "data",
-      "key": "datasets/clients.parquet",
-      "size_bytes": 34228,
-      "created_at": "2026-03-27T13:11:41.350247882Z"
-    }
-  ],
-  "created_at": "2026-03-27T13:11:41.350250705Z",
-  "updated_at": "2026-03-27T13:11:41.350250705Z"
-}
\ No newline at end of file
diff --git a/data/_catalog/manifests/c0224239-a265-4b15-a1e2-ebbc96aee60c.json b/data/_catalog/manifests/c0224239-a265-4b15-a1e2-ebbc96aee60c.json
new file mode 100644
index 0000000..1f3bb69
--- /dev/null
+++ b/data/_catalog/manifests/c0224239-a265-4b15-a1e2-ebbc96aee60c.json
@@ -0,0 +1,15 @@
+{
+  "id": "c0224239-a265-4b15-a1e2-ebbc96aee60c",
+  "name": "email_log",
+  "schema_fingerprint": "auto",
+  "objects": [
+    {
+      "bucket": "data",
+      "key": "datasets/email_log.parquet",
+      "size_bytes": 16768671,
+      "created_at": "2026-03-27T13:15:28.446541739Z"
+    }
+  ],
+  "created_at": "2026-03-27T13:15:28.446547070Z",
+  "updated_at": "2026-03-27T13:15:28.446547070Z"
+}
\ No newline at end of file
diff --git a/data/_catalog/manifests/c8c9d519-b8b5-4d04-ba2b-5acf53c41bc2.json b/data/_catalog/manifests/c8c9d519-b8b5-4d04-ba2b-5acf53c41bc2.json
new file mode 100644
index 0000000..b29bb14
--- /dev/null
+++ b/data/_catalog/manifests/c8c9d519-b8b5-4d04-ba2b-5acf53c41bc2.json
@@ -0,0 +1,15 @@
+{
+  "id": "c8c9d519-b8b5-4d04-ba2b-5acf53c41bc2",
+  "name": "timesheets",
+  "schema_fingerprint": "auto",
+  "objects": [
+    {
+      "bucket": "data",
+      "key": "datasets/timesheets.parquet",
+      "size_bytes": 17539932,
+      "created_at": "2026-03-27T13:15:23.111118100Z"
+    }
+  ],
+  "created_at": "2026-03-27T13:15:23.111124272Z",
+  "updated_at": "2026-03-27T13:15:23.111124272Z"
+}
\ No newline at end of file
diff --git a/data/_catalog/manifests/dcca449b-a2f6-4c1f-99b6-c69dcdbdd204.json b/data/_catalog/manifests/dcca449b-a2f6-4c1f-99b6-c69dcdbdd204.json
new file mode 100644
index 0000000..6c99fb2
--- /dev/null
+++ b/data/_catalog/manifests/dcca449b-a2f6-4c1f-99b6-c69dcdbdd204.json
@@ -0,0 +1,15 @@
+{
+  "id": "dcca449b-a2f6-4c1f-99b6-c69dcdbdd204",
+  "name": "placements",
+  "schema_fingerprint": "auto",
+  "objects": [
+    {
+      "bucket": "data",
+      "key": "datasets/placements.parquet",
+      "size_bytes": 1213820,
+      "created_at": "2026-03-27T13:15:18.264258909Z"
+    }
+  ],
+  "created_at": "2026-03-27T13:15:18.264266375Z",
+  "updated_at": "2026-03-27T13:15:18.264266375Z"
+}
\ No newline at end of file
diff --git a/data/_catalog/manifests/e015f0e2-51e4-4301-855d-76c54992c5b9.json b/data/_catalog/manifests/e015f0e2-51e4-4301-855d-76c54992c5b9.json
deleted file mode 100644
index 792949e..0000000
--- a/data/_catalog/manifests/e015f0e2-51e4-4301-855d-76c54992c5b9.json
+++ /dev/null
@@ -1,15 +0,0 @@
-{
-  "id": "e015f0e2-51e4-4301-855d-76c54992c5b9",
-  "name": "call_log",
-  "schema_fingerprint": "auto",
-  "objects": [
-    {
-      "bucket": "data",
-      "key": "datasets/call_log.parquet",
-      "size_bytes": 3276693,
-      "created_at": "2026-03-27T13:11:42.483220340Z"
-    }
-  ],
-  "created_at": "2026-03-27T13:11:42.483225870Z",
-  "updated_at": "2026-03-27T13:11:42.483225870Z"
-}
\ No newline at end of file
diff --git a/data/_catalog/manifests/e8cc1ad2-114e-4441-a526-b8e6de10cb59.json b/data/_catalog/manifests/e8cc1ad2-114e-4441-a526-b8e6de10cb59.json
new file mode 100644
index 0000000..c4cd6dd
--- /dev/null
+++ b/data/_catalog/manifests/e8cc1ad2-114e-4441-a526-b8e6de10cb59.json
@@ -0,0 +1,15 @@
+{
+  "id": "e8cc1ad2-114e-4441-a526-b8e6de10cb59",
+  "name": "job_orders",
+  "schema_fingerprint": "auto",
+  "objects": [
+    {
+      "bucket": "data",
+      "key": "datasets/job_orders.parquet",
+      "size_bytes": 905534,
+      "created_at": "2026-03-27T13:15:18.114659931Z"
+    }
+  ],
+  "created_at": "2026-03-27T13:15:18.114667579Z",
+  "updated_at": "2026-03-27T13:15:18.114667579Z"
+}
\ No newline at end of file
diff --git a/data/datasets/call_log.parquet b/data/datasets/call_log.parquet
index 62e8b43..0f62d0e 100644
Binary files a/data/datasets/call_log.parquet and b/data/datasets/call_log.parquet differ
diff --git a/data/datasets/candidates.parquet b/data/datasets/candidates.parquet
index b454918..a7f05d5 100644
Binary files a/data/datasets/candidates.parquet and b/data/datasets/candidates.parquet differ
diff --git a/data/datasets/clients.parquet b/data/datasets/clients.parquet
index a8eff98..c61e229 100644
Binary files a/data/datasets/clients.parquet and b/data/datasets/clients.parquet differ
diff --git a/data/datasets/email_log.parquet b/data/datasets/email_log.parquet
index 18cee5e..34ee53c 100644
Binary files a/data/datasets/email_log.parquet and b/data/datasets/email_log.parquet differ
diff --git a/data/datasets/job_orders.parquet b/data/datasets/job_orders.parquet
index ddec4c5..3ad5c39 100644
Binary files a/data/datasets/job_orders.parquet and b/data/datasets/job_orders.parquet differ
diff --git a/data/datasets/placements.parquet b/data/datasets/placements.parquet
index 947c63a..49d3d55 100644
Binary files a/data/datasets/placements.parquet and b/data/datasets/placements.parquet differ
diff --git a/data/datasets/timesheets.parquet b/data/datasets/timesheets.parquet
index 3dd7c62..c1e6fb1 100644
Binary files a/data/datasets/timesheets.parquet and b/data/datasets/timesheets.parquet differ
diff --git a/data/vectors/candidate_resumes.parquet b/data/vectors/candidate_resumes.parquet
deleted file mode 100644
index 3acbdb3..0000000
Binary files a/data/vectors/candidate_resumes.parquet and /dev/null differ
diff --git a/data/vectors/resumes_10k.parquet b/data/vectors/resumes_10k.parquet
new file mode 100644
index 0000000..54e4d7d
Binary files /dev/null and b/data/vectors/resumes_10k.parquet differ
diff --git a/scripts/scale_test.py b/scripts/scale_test.py
new file mode 100644
index 0000000..dedecb0
--- /dev/null
+++ b/scripts/scale_test.py
@@ -0,0 +1,264 @@
+#!/usr/bin/env python3
+"""
+Scale test: 2.5M rows across staffing tables + 100K vector embeddings.
+Designed for 128GB RAM machine.
+"""
+
+import random, json, urllib.request, time
+from datetime import datetime, timedelta
+import pyarrow as pa, pyarrow.parquet as pq
+
+API = "http://localhost:3100"
+random.seed(2026)
+
+def upload(name, table):
+    path = f"/tmp/{name}.parquet"
+    pq.write_table(table, path, compression="snappy")
+    with open(path, "rb") as f:
+        data = f.read()
+    key = f"datasets/{name}.parquet"
+    req = urllib.request.Request(f"{API}/storage/objects/{key}", data=data, method="PUT")
+    urllib.request.urlopen(req)
+    body = json.dumps({"name": name, "schema_fingerprint": "auto",
+        "objects": [{"bucket": "data", "key": key, "size_bytes": len(data)}]}).encode()
+    req = urllib.request.Request(f"{API}/catalog/datasets", data=body, method="POST",
+        headers={"Content-Type": "application/json"})
+    urllib.request.urlopen(req)
+    print(f"  {name}: {table.num_rows:,} rows ({len(data)/1024/1024:.1f} MB)")
+
+# Shared data
+first_names = ["James","Mary","Robert","Patricia","John","Jennifer","Michael","Linda","David","Elizabeth",
+    "William","Barbara","Richard","Susan","Joseph","Jessica","Thomas","Sarah","Christopher","Karen",
+    "Charles","Lisa","Daniel","Nancy","Matthew","Betty","Anthony","Margaret","Mark","Sandra",
+    "Donald","Ashley","Steven","Dorothy","Paul","Kimberly","Andrew","Emily","Joshua","Donna",
+    "Kenneth","Michelle","Kevin","Carol","Brian","Amanda","George","Melissa","Timothy","Deborah"]
+last_names = ["Smith","Johnson","Williams","Brown","Jones","Garcia","Miller","Davis","Rodriguez","Martinez",
+    "Hernandez","Lopez","Gonzalez","Wilson","Anderson","Thomas","Taylor","Moore","Jackson","Martin",
+    "Lee","Perez","Thompson","White","Harris","Sanchez","Clark","Ramirez","Lewis","Robinson",
+    "Walker","Young","Allen","King","Wright","Scott","Torres","Nguyen","Hill","Flores"]
+cities_zips = [
+    ("Chicago","IL","60601"),("Chicago","IL","60610"),("Chicago","IL","60614"),("Chicago","IL","60622"),
+    ("New York","NY","10001"),("New York","NY","10016"),("New York","NY","10022"),("New York","NY","10036"),
+    ("Los Angeles","CA","90001"),("Los Angeles","CA","90024"),("Houston","TX","77001"),("Houston","TX","77019"),
+    ("Dallas","TX","75201"),("Dallas","TX","75219"),("Atlanta","GA","30301"),("Atlanta","GA","30309"),
+    ("Denver","CO","80201"),("Denver","CO","80206"),("Phoenix","AZ","85001"),("Phoenix","AZ","85006"),
+    ("Seattle","WA","98101"),("Seattle","WA","98104"),("Miami","FL","33101"),("Miami","FL","33132"),
+]
+verticals = ["IT","Healthcare","Industrial","Accounting","Admin"]
+skills_by_vert = {
+    "IT": ["Java","Python","C#",".NET","JavaScript","React","Angular","Node.js","SQL","AWS","Azure","Docker","Kubernetes","Linux","Git","REST APIs","MongoDB","PostgreSQL","Redis","Terraform","Jenkins","Agile","Spring Boot","Django","Go","Rust","TypeScript","GraphQL","Microservices","CI/CD"],
+    "Healthcare": ["RN","LPN","CNA","BLS","ACLS","EMR","Epic","Cerner","ICD-10","CPT","HIPAA","Phlebotomy","ICU","OR","ER","Med-Surg","Pediatrics","Oncology","Telemetry","IV Therapy"],
+    "Industrial": ["Forklift","OSHA 10","OSHA 30","Welding","CNC","PLC","Blueprint Reading","Quality Control","Six Sigma","AutoCAD","SolidWorks","Mechanical Assembly","Electrical","Hydraulics","Warehouse","Lean Manufacturing"],
+    "Accounting": ["QuickBooks","SAP","Oracle","Accounts Payable","Accounts Receivable","General Ledger","Financial Reporting","CPA","Payroll","Budgeting","Excel Advanced","Power BI","Tableau","GAAP","SOX","Audit"],
+    "Admin": ["Microsoft Office","Data Entry","Customer Service","Scheduling","Receptionist","Executive Assistant","Calendar Management","Salesforce","CRM","Multi-line Phone","Typing 60+ WPM","Bilingual Spanish","Notary"],
+}
+email_domains = ["gmail.com","yahoo.com","hotmail.com","outlook.com","icloud.com","protonmail.com"]
+base_date = datetime(2026, 1, 1)
+
+def make_phone():
+    return f"({random.randint(200,999)}) {random.randint(200,999)}-{random.randint(1000,9999)}"
+
+print("=" * 60)
+print("SCALE TEST: 2.5M rows + 100K vectors")
+print("=" * 60)
+t_start = time.time()
+
+# ============================================================
+# 100K CANDIDATES
+# ============================================================
+print("\nGenerating candidates (100K)...")
+t0 = time.time()
+N = 100_000
+
+c_ids, c_first, c_last, c_emails, c_phones = [], [], [], [], []
+c_city, c_state, c_zip = [], [], []
+c_vertical, c_skills, c_resume = [], [], []
+c_status, c_source, c_pay, c_years = [], [], [], []
+
+for i in range(N):
+    fn = random.choice(first_names)
+    ln = random.choice(last_names)
+    city, state, zc = random.choice(cities_zips)
+    vert = random.choice(verticals)
+    sk = random.sample(skills_by_vert[vert], min(random.randint(3, 10), len(skills_by_vert[vert])))
+    yrs = random.randint(0, 30)
+
+    resume = f"{fn} {ln} — {vert} professional with {yrs} years experience in {city}, {state} {zc}. Skills: {', '.join(sk)}. "
+    resume += random.choice([
+        f"Previously at {random.choice(['Acme','TechFlow','GlobalStaff','MedPro','BuildRight','CoreSys','Apex','Summit'])} Corp.",
+        f"Seeking {random.choice(['contract','full-time','temp-to-hire'])} in {city} metro.",
+        f"Available {random.choice(['immediately','in 2 weeks','after current assignment'])}.",
+        f"Open to {random.choice(['remote','hybrid','on-site'])} work arrangements.",
+        f"Certified in {random.choice(sk)} with hands-on project experience.",
+    ])
+
+    c_ids.append(f"CAND-{i+1:06d}")
+    c_first.append(fn)
+    c_last.append(ln)
+    c_emails.append(f"{fn.lower()}.{ln.lower()}{random.randint(1,99)}@{random.choice(email_domains)}")
+    c_phones.append(make_phone())
+    c_city.append(city)
+    c_state.append(state)
+    c_zip.append(zc)
+    c_vertical.append(vert)
+    c_skills.append("|".join(sk))
+    c_resume.append(resume)
+    c_status.append(random.choice(["active","active","active","inactive","placed"]))
+    c_source.append(random.choice(["Indeed","LinkedIn","Referral","Walk-in","Monster","Website"]))
+    c_pay.append(round(random.uniform(12, 95), 2))
+    c_years.append(yrs)
+
+candidates = pa.table({
+    "candidate_id": c_ids, "first_name": c_first, "last_name": c_last,
+    "email": c_emails, "phone": c_phones,
+    "city": c_city, "state": c_state, "zip": c_zip,
+    "vertical": c_vertical, "skills": c_skills, "resume_summary": c_resume,
+    "status": c_status, "source": c_source, "min_pay_rate": c_pay, "years_experience": c_years,
+})
+upload("candidates", candidates)
+print(f"  Generated in {time.time()-t0:.1f}s")
+
+# ============================================================
+# 2K CLIENTS
+# ============================================================
+print("\nGenerating clients (2K)...")
+prefixes = ["Apex","Summit","Core","National","Metro","Pacific","Global","United","Pinnacle","Horizon","Pioneer","Titan","Quantum","Vertex","Elite"]
+suffixes = ["Industries","Solutions","Systems","Group","Corp","Technologies","Services","Partners","Manufacturing","Healthcare"]
+cl_ids, cl_names, cl_verts, cl_city, cl_state, cl_zip = [], [], [], [], [], []
+for i in range(2000):
+    city, state, zc = random.choice(cities_zips)
+    cl_ids.append(f"CLI-{i+1:05d}")
+    cl_names.append(f"{random.choice(prefixes)} {random.choice(suffixes)}")
+    cl_verts.append(random.choice(verticals))
+    cl_city.append(city)
+    cl_state.append(state)
+    cl_zip.append(zc)
+clients = pa.table({"client_id": cl_ids, "company_name": cl_names, "vertical": cl_verts, "city": cl_city, "state": cl_state, "zip": cl_zip})
+upload("clients", clients)
+
+# ============================================================
+# 15K JOB ORDERS
+# ============================================================
+print("\nGenerating job_orders (15K)...")
+titles_map = {
+    "IT": ["Software Developer","Java Developer",".NET Developer","DevOps Engineer","Data Analyst","QA Engineer","Cloud Architect","React Developer","DBA","Security Analyst","Python Developer","Full Stack Developer"],
+    "Healthcare": ["Registered Nurse","LPN","CNA","Medical Assistant","Phlebotomist","Radiology Tech","Pharmacy Tech","Medical Coder"],
+    "Industrial": ["Forklift Operator","Welder","CNC Machinist","Quality Inspector","Maintenance Tech","Electrician","Warehouse Associate","Assembly Tech"],
+    "Accounting": ["Staff Accountant","AP Specialist","AR Specialist","Payroll Clerk","Financial Analyst","Bookkeeper","Controller","Tax Preparer"],
+    "Admin": ["Administrative Assistant","Executive Assistant","Receptionist","Data Entry Clerk","Office Manager","Customer Service Rep","HR Coordinator"],
+}
+jo_ids, jo_clients, jo_titles, jo_verts, jo_bills, jo_pays, jo_status = [], [], [], [], [], [], []
+jo_city, jo_state, jo_zip, jo_desc = [], [], [], []
+for i in range(15000):
+    vert = random.choice(verticals)
+    title = random.choice(titles_map[vert])
+    ci = random.randint(0, 1999)
+    city, state, zc = random.choice(cities_zips)
+    bill = round(random.uniform(25, 150), 2)
+    pay = round(bill * random.uniform(0.55, 0.75), 2)
+    req_sk = random.sample(skills_by_vert[vert], min(random.randint(3, 6), len(skills_by_vert[vert])))
+    desc = f"{title} for {cl_names[ci]} in {city}, {state}. Requires: {', '.join(req_sk)}. {random.randint(1,10)}+ years exp. ${bill}/hr."
+    jo_ids.append(f"JO-{i+1:06d}")
+    jo_clients.append(cl_ids[ci])
+    jo_titles.append(title)
+    jo_verts.append(vert)
+    jo_bills.append(bill)
+    jo_pays.append(pay)
+    jo_status.append(random.choice(["open","open","filled","filled","closed"]))
+    jo_city.append(city)
+    jo_state.append(state)
+    jo_zip.append(zc)
+    jo_desc.append(desc)
+job_orders = pa.table({"job_order_id": jo_ids, "client_id": jo_clients, "title": jo_titles, "vertical": jo_verts, "bill_rate": jo_bills, "pay_rate": jo_pays, "status": jo_status, "city": jo_city, "state": jo_state, "zip": jo_zip, "description": jo_desc})
+upload("job_orders", job_orders)
+
+# ============================================================
+# 50K PLACEMENTS
+# ============================================================
+print("\nGenerating placements (50K)...")
+recruiters = [f"{random.choice(first_names)} {random.choice(last_names)}" for _ in range(100)]
+p_ids, p_cands, p_jobs, p_clients, p_bills, p_pays, p_recs, p_status = [], [], [], [], [], [], [], []
+for i in range(50000):
+    ci = random.randint(0, N-1)
+    ji = random.randint(0, 14999)
+    p_ids.append(f"PL-{i+1:06d}")
+    p_cands.append(c_ids[ci])
+    p_jobs.append(jo_ids[ji])
+    p_clients.append(jo_clients[ji])
+    p_bills.append(jo_bills[ji])
+    p_pays.append(jo_pays[ji])
+    p_recs.append(random.choice(recruiters))
+    p_status.append(random.choice(["active","active","completed","completed","terminated"]))
+placements = pa.table({"placement_id": p_ids, "candidate_id": p_cands, "job_order_id": p_jobs, "client_id": p_clients, "bill_rate": p_bills, "pay_rate": p_pays, "recruiter": p_recs, "status": p_status})
+upload("placements", placements)
+
+# ============================================================
+# 1M TIMESHEETS
+# ============================================================
+print("\nGenerating timesheets (1M)...")
+ts_ids, ts_placements, ts_cands, ts_clients = [], [], [], []
+ts_hrs_reg, ts_hrs_ot, ts_bill_total, ts_pay_total, ts_weeks, ts_approved = [], [], [], [], [], []
+for i in range(1_000_000):
+    pi = random.randint(0, 49999)
+    hrs = random.choice([40.0, 40.0, 40.0, 32.0, 24.0, 20.0])
+    ot = random.choice([0.0, 0.0, 0.0, 4.0, 8.0, 12.0])
+    b = p_bills[pi]
+    p = p_pays[pi]
+    ts_ids.append(f"TS-{i+1:07d}")
+    ts_placements.append(p_ids[pi])
+    ts_cands.append(p_cands[pi])
+    ts_clients.append(p_clients[pi])
+    ts_hrs_reg.append(hrs)
+    ts_hrs_ot.append(ot)
+    ts_bill_total.append(round(hrs * b + ot * b * 1.5, 2))
+    ts_pay_total.append(round(hrs * p + ot * p * 1.5, 2))
+    ts_weeks.append((base_date - timedelta(weeks=random.randint(0, 156))).strftime("%Y-%m-%d"))
+    ts_approved.append(random.random() < 0.85)
+timesheets = pa.table({"timesheet_id": ts_ids, "placement_id": ts_placements, "candidate_id": ts_cands, "client_id": ts_clients, "hours_regular": ts_hrs_reg, "hours_overtime": ts_hrs_ot, "bill_total": ts_bill_total, "pay_total": ts_pay_total, "week_ending": ts_weeks, "approved": ts_approved})
+upload("timesheets", timesheets)
+
+# ============================================================
+# 800K CALL LOG
+# ============================================================
+print("\nGenerating call_log (800K)...")
+call_ids, call_from, call_to, call_dur, call_ts, call_rec, call_cand, call_disp = [], [], [], [], [], [], [], []
+disps = ["connected","voicemail","no_answer","busy","wrong_number","callback_scheduled"]
+for i in range(800_000):
+    ci = random.randint(0, N-1)
+    call_ids.append(f"CALL-{i+1:07d}")
+    call_from.append(make_phone())
+    call_to.append(c_phones[ci])
+    call_dur.append(random.randint(0, 1800))
+    call_ts.append((base_date - timedelta(seconds=random.randint(0, 86400*365))).isoformat())
+    call_rec.append(random.choice(recruiters))
+    call_cand.append(c_ids[ci])
+    call_disp.append(random.choice(disps))
+call_log = pa.table({"call_id": call_ids, "from_number": call_from, "to_number": call_to, "duration_seconds": call_dur, "timestamp": call_ts, "recruiter": call_rec, "candidate_id": call_cand, "disposition": call_disp})
+upload("call_log", call_log)
+
+# ============================================================
+# 500K EMAIL LOG
+# ============================================================
+print("\nGenerating email_log (500K)...")
+em_ids, em_from, em_to, em_subj, em_ts, em_rec, em_cand, em_opened = [], [], [], [], [], [], [], []
+subjects = ["New opportunity: {}", "Following up", "Interview scheduled", "Timesheet reminder", "Background check complete", "Assignment details", "Rate update", "Welcome aboard"]
+for i in range(500_000):
+    ci = random.randint(0, N-1)
+    ji = random.randint(0, 14999)
+    rec = random.choice(recruiters)
+    em_ids.append(f"EM-{i+1:07d}")
+    em_from.append(f"{rec.replace(' ','.').lower()}@acmestaffing.com")
+    em_to.append(c_emails[ci])
+    em_subj.append(random.choice(subjects).format(jo_titles[ji]))
+    em_ts.append((base_date - timedelta(seconds=random.randint(0, 86400*365))).isoformat())
+    em_rec.append(rec)
+    em_cand.append(c_ids[ci])
+    em_opened.append(random.random() < 0.55)
+email_log = pa.table({"email_id": em_ids, "from_addr": em_from, "to_addr": em_to, "subject": em_subj, "timestamp": em_ts, "recruiter": em_rec, "candidate_id": em_cand, "opened": em_opened})
+upload("email_log", email_log)
+
+total = 100_000 + 2_000 + 15_000 + 50_000 + 1_000_000 + 800_000 + 500_000
+t_total = time.time() - t_start
+print(f"\n{'='*60}")
+print(f"LOADED: {total:,} rows in {t_total:.0f}s")
+print(f"{'='*60}")