diff --git a/app/api/milvus.py b/app/api/milvus.py
new file mode 100644
index 0000000..4021cc0
--- /dev/null
+++ b/app/api/milvus.py
@@ -0,0 +1,119 @@
+"""Milvus 向量库只读查看 API（展示窗口 · 不加增删改）。
+
+只读导出当前 Milvus 库中的 collection 清单：中文名 / 描述 / 向量数 /
+维度 / 标量字段 / 少量样本。面向「向量知识库」展示页，供四角色查看
+公开知识库与话术模板库（无客户敏感数据），鉴权走平台级通道。
+
+连接与 pymilvus 环境防御复用 app/service/milvus_service（milvus_client）；
+Milvus Lite 跨进程重开后 collection 处于 released 状态，query 前必须
+load_collection（与 milvus_service.ensure_collection 同口径）。
+"""
+
+from __future__ import annotations
+
+from fastapi import APIRouter, Depends, Request
+
+from app.api.deps import AuthContext, get_platform_auth_context
+from app.service import milvus_service
+from app.utils.response import ok
+
+router = APIRouter(prefix="/api/milvus", tags=["platform-milvus"])
+
+# 已知 collection 的中文名 + 描述（未知库回退用原始名）
+COLLECTION_META: dict[str, dict[str, str]] = {
+    "fin_faq": {
+        "title": "常见问答库",
+        "description": "客服线 FAQ 问答对（问题 / 答案 / 分类），客户与顾问语义检索共用。",
+    },
+    "fin_policy": {
+        "title": "政策制度库",
+        "description": "客服线政策条款（政策名 / 章节），客户与顾问语义检索共用。",
+    },
+    "fin_product": {
+        "title": "产品知识库",
+        "description": "客服线产品信息（产品名 / 风险等级 / 文档类型），客户与顾问语义检索共用。",
+    },
+    "kb_script_templates": {
+        "title": "话术模板库",
+        "description": "顾问展业话术模板（标题 / 场景 / 标签 / 审核态），按语义相似度检索。",
+    },
+    "kb_product_rules": {
+        "title": "产品规则库",
+        "description": "产品手册 / 交易规则（费率、申赎、风险说明），客户与顾问共用，回答必带溯源。",
+    },
+}
+
+_SAMPLE_LIMIT = 3
+
+
+def _scalar_fields(desc: dict) -> tuple[list[str], int]:
+    """describe_collection → (标量字段名列表, embedding 维度)。"""
+    fields: list[str] = []
+    dim = 0
+    for f in desc.get("fields", []):
+        name = f.get("name")
+        if not name:
+            continue
+        if f.get("type") == milvus_service.DataType.FLOAT_VECTOR:
+            dim = int((f.get("params") or {}).get("dim", 0) or 0)
+            continue
+        fields.append(name)
+    return fields, dim
+
+
+@router.get("/collections")
+def list_collections(
+    request: Request,
+    auth: AuthContext = Depends(get_platform_auth_context),
+) -> dict:
+    """Milvus collection 清单（只读）。"""
+    del auth  # 平台级鉴权已在上方依赖完成；本端点无额外角色限制
+    client = milvus_service.milvus_client()
+    try:
+        names = sorted(client.list_collections())
+        items: list[dict] = []
+        total_vectors = 0
+        for name in names:
+            meta = COLLECTION_META.get(name, {"title": name, "description": ""})
+            row_count = 0
+            fields: list[str] = []
+            dim = 0
+            sample: list[dict] = []
+            try:
+                stats = client.get_collection_stats(name)
+                row_count = int(stats.get("row_count", 0))
+                total_vectors += row_count
+                fields, dim = _scalar_fields(client.describe_collection(name))
+                if row_count > 0:
+                    client.load_collection(name)
+                    sample = client.query(
+                        name,
+                        filter="",
+                        output_fields=fields,
+                        limit=_SAMPLE_LIMIT,
+                    )
+            except Exception:
+                # 单个 collection 读取失败不阻断整体展示（降级为空样本）
+                sample = []
+            items.append(
+                {
+                    "name": name,
+                    "title": meta.get("title", name),
+                    "description": meta.get("description", ""),
+                    "row_count": row_count,
+                    "dimension": dim,
+                    "fields": fields,
+                    "sample": sample,
+                }
+            )
+    finally:
+        client.close()
+    trace_id = getattr(request.state, "trace_id", "unknown")
+    return ok(
+        {
+            "items": items,
+            "total_collections": len(items),
+            "total_vectors": total_vectors,
+        },
+        trace_id,
+    ).model_dump()
diff --git a/app/main.py b/app/main.py
index a2cfb69..5b23680 100644
--- a/app/main.py
+++ b/app/main.py
@@ -33,6 +33,7 @@ from app.api.guard import router as advisor_guard_router
 from app.api.kyc import router as advisor_kyc_router
 from app.api.market import fund_router as advisor_market_fund_router
 from app.api.market import router as advisor_market_alerts_router
+from app.api.milvus import router as milvus_router
 from app.api.ready import build_ready_payload, router as ready_router
 from app.api.visitor import router as visitor_router
 from app.advisor_exceptions import AdvisorAppError
@@ -122,6 +123,7 @@ app.include_router(advisor_copy_router)
 app.include_router(advisor_guard_router)
 app.include_router(advisor_dashboard_router)
 app.include_router(advisor_allocation_router)
+app.include_router(milvus_router)
 app.include_router(ready_router)
 
 
diff --git a/app/service/platform/common.py b/app/service/platform/common.py
index 8b78db4..7a1c389 100644
--- a/app/service/platform/common.py
+++ b/app/service/platform/common.py
@@ -9,14 +9,22 @@ from typing import Any
 from app.config.settings import settings
 from app.utils import desensitize as d
 
+# core_product_nav 等为 DECIMAL(10,4)；若统一 round 2 位会把货基 1.001x 压成 1.0，走势图变平
+_DECIMAL_PLACES_BY_KEY: dict[str, int] = {
+    "nav": 4,
+    "daily_chg_pct": 4,
+    "daily_return": 4,
+}
 
-def to_jsonable(value: Any) -> Any:
+
+def to_jsonable(value: Any, *, _key: str | None = None) -> Any:
     if isinstance(value, Decimal):
-        return float(round(value, 2))
+        places = _DECIMAL_PLACES_BY_KEY.get(_key or "", 2)
+        return float(round(value, places))
     if isinstance(value, (_dt.datetime, _dt.date)):
         return value.isoformat()
     if isinstance(value, dict):
-        return {k: to_jsonable(v) for k, v in value.items()}
+        return {k: to_jsonable(v, _key=k) for k, v in value.items()}
     if isinstance(value, list):
         return [to_jsonable(v) for v in value]
     return value
diff --git a/docs/答辩/README.md b/docs/答辩/README.md
index 5d30afd..0db3c80 100644
--- a/docs/答辩/README.md
+++ b/docs/答辩/README.md
@@ -7,11 +7,12 @@
 
 | 中文职责 | 文件 | 何时用 |
 | --- | --- | --- |
-| README 口播 | [`答辩稿.md`](答辩稿.md) | **17 页贴幻灯片** + Demo 脚本 + 【ADR】简句 |
+| README 口播 | [`答辩稿.md`](答辩稿.md) | 源稿 · **Word 打印：** [`答辩稿.docx`](答辩稿.docx) |
+| **Word 口播稿** | [`答辩稿.docx`](答辩稿.docx) | 由 `答辩稿.md` 导出，改 md 后需重新 pandoc |
 | Live Demo 逐步操作 | [`DEMO-SOP-答辩全流程.md`](DEMO-SOP-答辩全流程.md) | 现场演示主脚本 |
 | 问数分册 | [`DEMO-SOP-问数.md`](DEMO-SOP-问数.md) | 问数/interpret/analyze 细节 |
 | HTML 幻灯片 | [`presentation/index.html`](presentation/index.html) | 投屏 / Ctrl+P 导出 PDF |
-| **口播 A4 打印** | [`print/答辩口播-打印版.html`](print/答辩口播-打印版.html) | 浏览器 Ctrl+P · [`print/README.md`](print/README.md) |
+| **口播 A4 打印（HTML，可选）** | [`print/答辩口播-打印版.html`](print/答辩口播-打印版.html) | 浏览器 Ctrl+P |
 | 知识点提纲 + 深 Q&A | [`答辩知识点清单.md`](答辩知识点清单.md) | 备查；§八为内部工程项**不上台** |
 | **Demo 功能测试（内部）** | [`DEMO-功能测试流程.md`](DEMO-功能测试流程.md) | 答辩前自测，**不对评委念** |
 | **客户文本交付 6 项** | [`提交物料/README.md`](提交物料/README.md) | 对照 `答辩所需文本交付物清单.txt` 打包提交 |
diff --git a/docs/答辩/print/README.md b/docs/答辩/print/README.md
index 887d996..66738a1 100644
--- a/docs/答辩/print/README.md
+++ b/docs/答辩/print/README.md
@@ -2,10 +2,6 @@
 
 | 中文职责 | 文件 | 操作 |
 | --- | --- | --- |
-| **口播稿（A4 打印/PDF）** | [`答辩口播-打印版.html`](答辩口播-打印版.html) | 浏览器打开 → **Ctrl+P** → 另存为 PDF 或直接打印 |
-| 投屏幻灯片 PDF | [`../presentation/index.html`](../presentation/index.html) | 同上 Ctrl+P（需联网 CDN） |
-| Markdown 源稿 | [`../答辩稿.md`](../答辩稿.md) | 与打印版同步维护 |
-
-**打印建议：** A4 · 边距「默认」或「最小」· 勾选「背景图形」（ADR 灰底）· 双面可选。
-
-**提交物料 6 项** 仍以 `docs/答辩/提交物料/` 为准；本目录只管 **现场口播打印**。
+| **口播稿 Word（推荐）** | [`../答辩稿.docx`](../答辩稿.docx) | Word / WPS 打开后直接打印 |
+| Markdown 源稿 | [`../答辩稿.md`](../答辩稿.md) | 改内容后执行：`pandoc 答辩稿.md -o 答辩稿.docx` |
+| HTML 打印（可选） | [`答辩口播-打印版.html`](答辩口播-打印版.html) | Ctrl+P |
diff --git a/docs/答辩/答辩稿.docx b/docs/答辩/答辩稿.docx
new file mode 100644
index 0000000..882c173
Binary files /dev/null and b/docs/答辩/答辩稿.docx differ
diff --git a/scripts/core/06-seed-nav.sql b/scripts/core/06-seed-nav.sql
index 6e994d7..a0cf4b8 100644
--- a/scripts/core/06-seed-nav.sql
+++ b/scripts/core/06-seed-nav.sql
@@ -20,72 +20,12 @@ USE jinrong_core;
 --   PROD-PRIV01   <- 519062 海富通阿尔法对冲混合A（private_fund/R4：量化对冲，日波动 0.33%）
 --   PROD-WMG001   <- 004155 中信保诚至泰中短债A（wealth_mgmt/R2：中短债，日波动 0.02%）
 --   PROD-XYZ999   <- 320007 诺安成长混合A（stock/R5：高波动成长，日波动 1.76%）
---   PROD-000001   <- 恒定 1.0000（现金宝货币（money/R1：货基单位净值恒为 1 元，收益以份额结转））
+--   PROD-000001   <- 见 07-seed-nav-history.sql（现金宝：演示低波曲线，不在此重复灌平线）
 --
 -- ⚠️ 真实净值只到抓取当日。之后运行需重跑 fetch_nav.py 增量补拉，
 --    否则 T+1 确认会取不到 T 日净值（真实业务同样是「净值 T+1 才公告」）。
 
 INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
-('PROD-000001', 1.0000, 0.0000, '2026-06-22'),
-('PROD-000001', 1.0000, 0.0000, '2026-06-23'),
-('PROD-000001', 1.0000, 0.0000, '2026-06-24'),
-('PROD-000001', 1.0000, 0.0000, '2026-06-25'),
-('PROD-000001', 1.0000, 0.0000, '2026-06-26'),
-('PROD-000001', 1.0000, 0.0000, '2026-06-29'),
-('PROD-000001', 1.0000, 0.0000, '2026-06-30'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-01'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-02'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-03'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-06'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-07'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-08'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-09'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-10'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-13'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-14'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-15'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-16'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-17'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-20'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-21'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-22'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-23'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-24'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-27'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-28'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-29'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-30'),
-('PROD-000001', 1.0000, 0.0000, '2026-07-31'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-03'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-04'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-05'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-06'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-07'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-10'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-11'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-12'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-13'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-14'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-17'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-18'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-19'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-20'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-21'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-24'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-25'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-26'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-27'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-28'),
-('PROD-000001', 1.0000, 0.0000, '2026-08-31'),
-('PROD-000001', 1.0000, 0.0000, '2026-09-01'),
-('PROD-000001', 1.0000, 0.0000, '2026-09-02'),
-('PROD-000001', 1.0000, 0.0000, '2026-09-03'),
-('PROD-000001', 1.0000, 0.0000, '2026-09-04'),
-('PROD-000001', 1.0000, 0.0000, '2026-09-07'),
-('PROD-000001', 1.0000, 0.0000, '2026-09-08'),
-('PROD-000001', 1.0000, 0.0000, '2026-09-09'),
-('PROD-000001', 1.0000, 0.0000, '2026-09-10'),
-('PROD-000001', 1.0000, 0.0000, '2026-09-11');
 INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-000002', 1.1004, 0.0100, '2026-06-22'),
 ('PROD-000002', 1.1004, 0.0000, '2026-06-23'),
diff --git a/scripts/core/07-seed-nav-history.sql b/scripts/core/07-seed-nav-history.sql
index 0f42133..9a70fdb 100644
--- a/scripts/core/07-seed-nav-history.sql
+++ b/scripts/core/07-seed-nav-history.sql
@@ -2,7 +2,7 @@ USE jinrong_core;
 
 -- 近 365 个自然日（含锚定日 2026-09-04；与 06-seed-nav 锚点净值一致）
 -- 日涨跌：模拟 CSI300 + 产品 beta（seed_nav_history.py）
--- 生成：python scripts/core/seed_nav_history.py --export-sql · 5110 行 · 14 产品
+-- 生成：python scripts/core/seed_nav_history.py --export-sql · 5208 行 · 14 产品
 
 INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-110022', 1.0360, 0.0300, '2025-09-05'),
@@ -369,7 +369,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-110022', 1.0297, 0.0104, '2026-09-01'),
 ('PROD-110022', 1.0300, 0.0311, '2026-09-02'),
 ('PROD-110022', 1.0297, -0.0305, '2026-09-03'),
-('PROD-110022', 1.0300, 0.0291, '2026-09-04'),
+('PROD-110022', 1.0294, -0.0289, '2026-09-04'),
+('PROD-110022', 1.0294, -0.0021, '2026-09-05'),
+('PROD-110022', 1.0293, -0.0058, '2026-09-06'),
+('PROD-110022', 1.0295, 0.0205, '2026-09-07'),
+('PROD-110022', 1.0293, -0.0176, '2026-09-08'),
+('PROD-110022', 1.0295, 0.0219, '2026-09-09'),
+('PROD-110022', 1.0292, -0.0316, '2026-09-10'),
+('PROD-110022', 1.0292, -0.0028, '2026-09-11'),
 ('PROD-110023', 1.0199, 0.0245, '2025-09-05'),
 ('PROD-110023', 1.0200, 0.0072, '2025-09-06'),
 ('PROD-110023', 1.0198, -0.0214, '2025-09-07'),
@@ -497,16 +504,16 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-110023', 1.0189, 0.0224, '2026-01-07'),
 ('PROD-110023', 1.0193, 0.0350, '2026-01-08'),
 ('PROD-110023', 1.0198, 0.0466, '2026-01-09'),
-('PROD-110023', 1.0193, -0.0447, '2026-01-10'),
+('PROD-110023', 1.0193, -0.0447, '2026-01-10') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
+
+INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-110023', 1.0190, -0.0282, '2026-01-11'),
 ('PROD-110023', 1.0195, 0.0470, '2026-01-12'),
 ('PROD-110023', 1.0197, 0.0197, '2026-01-13'),
 ('PROD-110023', 1.0201, 0.0348, '2026-01-14'),
 ('PROD-110023', 1.0202, 0.0130, '2026-01-15'),
 ('PROD-110023', 1.0202, 0.0041, '2026-01-16'),
-('PROD-110023', 1.0205, 0.0284, '2026-01-17');
-
-INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
+('PROD-110023', 1.0205, 0.0284, '2026-01-17'),
 ('PROD-110023', 1.0206, 0.0052, '2026-01-18'),
 ('PROD-110023', 1.0207, 0.0095, '2026-01-19'),
 ('PROD-110023', 1.0202, -0.0498, '2026-01-20'),
@@ -736,7 +743,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-110023', 1.0208, 0.0273, '2026-09-01'),
 ('PROD-110023', 1.0205, -0.0282, '2026-09-02'),
 ('PROD-110023', 1.0200, -0.0500, '2026-09-03'),
-('PROD-110023', 1.0200, 0.0000, '2026-09-04'),
+('PROD-110023', 1.0197, -0.0259, '2026-09-04'),
+('PROD-110023', 1.0192, -0.0442, '2026-09-05'),
+('PROD-110023', 1.0192, -0.0029, '2026-09-06'),
+('PROD-110023', 1.0196, 0.0437, '2026-09-07'),
+('PROD-110023', 1.0201, 0.0444, '2026-09-08'),
+('PROD-110023', 1.0197, -0.0440, '2026-09-09'),
+('PROD-110023', 1.0192, -0.0447, '2026-09-10'),
+('PROD-110023', 1.0194, 0.0241, '2026-09-11'),
 ('PROD-005827', 0.9359, 0.0478, '2025-09-05'),
 ('PROD-005827', 0.9363, 0.0414, '2025-09-06'),
 ('PROD-005827', 0.9358, -0.0487, '2025-09-07'),
@@ -992,7 +1006,9 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-005827', 0.9479, -0.0500, '2026-05-15'),
 ('PROD-005827', 0.9485, 0.0628, '2026-05-16'),
 ('PROD-005827', 0.9480, -0.0527, '2026-05-17'),
-('PROD-005827', 0.9486, 0.0604, '2026-05-18'),
+('PROD-005827', 0.9486, 0.0604, '2026-05-18') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
+
+INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-005827', 0.9482, -0.0382, '2026-05-19'),
 ('PROD-005827', 0.9484, 0.0198, '2026-05-20'),
 ('PROD-005827', 0.9491, 0.0691, '2026-05-21'),
@@ -1006,9 +1022,7 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-005827', 0.9510, 0.0376, '2026-05-29'),
 ('PROD-005827', 0.9506, -0.0473, '2026-05-30'),
 ('PROD-005827', 0.9504, -0.0251, '2026-05-31'),
-('PROD-005827', 0.9508, 0.0412, '2026-06-01');
-
-INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
+('PROD-005827', 0.9508, 0.0412, '2026-06-01'),
 ('PROD-005827', 0.9502, -0.0666, '2026-06-02'),
 ('PROD-005827', 0.9503, 0.0109, '2026-06-03'),
 ('PROD-005827', 0.9500, -0.0288, '2026-06-04'),
@@ -1103,7 +1117,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-005827', 0.9484, 0.0314, '2026-09-01'),
 ('PROD-005827', 0.9489, 0.0479, '2026-09-02'),
 ('PROD-005827', 0.9494, 0.0498, '2026-09-03'),
-('PROD-005827', 0.9500, 0.0632, '2026-09-04'),
+('PROD-005827', 0.9495, 0.0090, '2026-09-04'),
+('PROD-005827', 0.9489, -0.0635, '2026-09-05'),
+('PROD-005827', 0.9491, 0.0205, '2026-09-06'),
+('PROD-005827', 0.9488, -0.0320, '2026-09-07'),
+('PROD-005827', 0.9484, -0.0467, '2026-09-08'),
+('PROD-005827', 0.9490, 0.0649, '2026-09-09'),
+('PROD-005827', 0.9486, -0.0472, '2026-09-10'),
+('PROD-005827', 0.9487, 0.0130, '2026-09-11'),
 ('PROD-005828', 1.0162, 0.0296, '2025-09-05'),
 ('PROD-005828', 1.0166, 0.0376, '2025-09-06'),
 ('PROD-005828', 1.0171, 0.0459, '2025-09-07'),
@@ -1468,7 +1489,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-005828', 1.0201, -0.0525, '2026-09-01'),
 ('PROD-005828', 1.0205, 0.0407, '2026-09-02'),
 ('PROD-005828', 1.0206, 0.0126, '2026-09-03'),
-('PROD-005828', 1.0200, -0.0588, '2026-09-04'),
+('PROD-005828', 1.0208, 0.0177, '2026-09-04'),
+('PROD-005828', 1.0209, 0.0138, '2026-09-05'),
+('PROD-005828', 1.0206, -0.0285, '2026-09-06'),
+('PROD-005828', 1.0210, 0.0432, '2026-09-07'),
+('PROD-005828', 1.0212, 0.0244, '2026-09-08'),
+('PROD-005828', 1.0206, -0.0548, '2026-09-09'),
+('PROD-005828', 1.0201, -0.0456, '2026-09-10'),
+('PROD-005828', 1.0200, -0.0072, '2026-09-11'),
 ('PROD-161725', 1.0574, -0.0469, '2025-09-05'),
 ('PROD-161725', 1.0571, -0.0282, '2025-09-06'),
 ('PROD-161725', 1.0563, -0.0775, '2025-09-07'),
@@ -1480,7 +1508,9 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-161725', 1.0557, 0.0195, '2025-09-13'),
 ('PROD-161725', 1.0561, 0.0353, '2025-09-14'),
 ('PROD-161725', 1.0561, 0.0045, '2025-09-15'),
-('PROD-161725', 1.0555, -0.0606, '2025-09-16'),
+('PROD-161725', 1.0555, -0.0606, '2025-09-16') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
+
+INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-161725', 1.0558, 0.0321, '2025-09-17'),
 ('PROD-161725', 1.0557, -0.0056, '2025-09-18'),
 ('PROD-161725', 1.0566, 0.0863, '2025-09-19'),
@@ -1508,9 +1538,7 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-161725', 1.0528, -0.0388, '2025-10-11'),
 ('PROD-161725', 1.0518, -0.0909, '2025-10-12'),
 ('PROD-161725', 1.0529, 0.1017, '2025-10-13'),
-('PROD-161725', 1.0521, -0.0779, '2025-10-14');
-
-INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
+('PROD-161725', 1.0521, -0.0779, '2025-10-14'),
 ('PROD-161725', 1.0512, -0.0865, '2025-10-15'),
 ('PROD-161725', 1.0516, 0.0383, '2025-10-16'),
 ('PROD-161725', 1.0510, -0.0553, '2025-10-17'),
@@ -1835,7 +1863,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-161725', 1.0494, -0.0607, '2026-09-01'),
 ('PROD-161725', 1.0493, -0.0056, '2026-09-02'),
 ('PROD-161725', 1.0492, -0.0075, '2026-09-03'),
-('PROD-161725', 1.0500, 0.0762, '2026-09-04'),
+('PROD-161725', 1.0497, 0.0491, '2026-09-04'),
+('PROD-161725', 1.0494, -0.0242, '2026-09-05'),
+('PROD-161725', 1.0503, 0.0874, '2026-09-06'),
+('PROD-161725', 1.0512, 0.0825, '2026-09-07'),
+('PROD-161725', 1.0518, 0.0607, '2026-09-08'),
+('PROD-161725', 1.0519, 0.0126, '2026-09-09'),
+('PROD-161725', 1.0521, 0.0194, '2026-09-10'),
+('PROD-161725', 1.0524, 0.0309, '2026-09-11'),
 ('PROD-161726', 1.0439, -0.0260, '2025-09-05'),
 ('PROD-161726', 1.0429, -0.0980, '2025-09-06'),
 ('PROD-161726', 1.0429, -0.0039, '2025-09-07'),
@@ -1975,7 +2010,9 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-161726', 1.0529, -0.0999, '2026-01-19'),
 ('PROD-161726', 1.0525, -0.0418, '2026-01-20'),
 ('PROD-161726', 1.0534, 0.0897, '2026-01-21'),
-('PROD-161726', 1.0524, -0.0924, '2026-01-22'),
+('PROD-161726', 1.0524, -0.0924, '2026-01-22') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
+
+INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-161726', 1.0526, 0.0236, '2026-01-23'),
 ('PROD-161726', 1.0519, -0.0696, '2026-01-24'),
 ('PROD-161726', 1.0525, 0.0543, '2026-01-25'),
@@ -2010,9 +2047,7 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-161726', 1.0542, -0.0285, '2026-02-23'),
 ('PROD-161726', 1.0551, 0.0900, '2026-02-24'),
 ('PROD-161726', 1.0542, -0.0898, '2026-02-25'),
-('PROD-161726', 1.0546, 0.0425, '2026-02-26');
-
-INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
+('PROD-161726', 1.0546, 0.0425, '2026-02-26'),
 ('PROD-161726', 1.0556, 0.0915, '2026-02-27'),
 ('PROD-161726', 1.0556, 0.0008, '2026-02-28'),
 ('PROD-161726', 1.0553, -0.0307, '2026-03-01'),
@@ -2202,7 +2237,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-161726', 1.0490, 0.0790, '2026-09-01'),
 ('PROD-161726', 1.0497, 0.0695, '2026-09-02'),
 ('PROD-161726', 1.0491, -0.0558, '2026-09-03'),
-('PROD-161726', 1.0500, 0.0858, '2026-09-04'),
+('PROD-161726', 1.0497, 0.0598, '2026-09-04'),
+('PROD-161726', 1.0495, -0.0215, '2026-09-05'),
+('PROD-161726', 1.0502, 0.0698, '2026-09-06'),
+('PROD-161726', 1.0498, -0.0338, '2026-09-07'),
+('PROD-161726', 1.0505, 0.0628, '2026-09-08'),
+('PROD-161726', 1.0508, 0.0312, '2026-09-09'),
+('PROD-161726', 1.0512, 0.0338, '2026-09-10'),
+('PROD-161726', 1.0514, 0.0173, '2026-09-11'),
 ('PROD-003095', 0.9521, -0.0888, '2025-09-05'),
 ('PROD-003095', 0.9520, -0.0105, '2025-09-06'),
 ('PROD-003095', 0.9519, -0.0068, '2025-09-07'),
@@ -2470,7 +2512,9 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-003095', 0.9456, -0.0847, '2026-05-27'),
 ('PROD-003095', 0.9465, 0.0934, '2026-05-28'),
 ('PROD-003095', 0.9463, -0.0186, '2026-05-29'),
-('PROD-003095', 0.9468, 0.0554, '2026-05-30'),
+('PROD-003095', 0.9468, 0.0554, '2026-05-30') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
+
+INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-003095', 0.9470, 0.0222, '2026-05-31'),
 ('PROD-003095', 0.9467, -0.0319, '2026-06-01'),
 ('PROD-003095', 0.9463, -0.0412, '2026-06-02'),
@@ -2512,9 +2556,7 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-003095', 0.9516, -0.0445, '2026-07-08'),
 ('PROD-003095', 0.9510, -0.0670, '2026-07-09'),
 ('PROD-003095', 0.9511, 0.0145, '2026-07-10'),
-('PROD-003095', 0.9516, 0.0516, '2026-07-11');
-
-INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
+('PROD-003095', 0.9516, 0.0516, '2026-07-11'),
 ('PROD-003095', 0.9521, 0.0517, '2026-07-12'),
 ('PROD-003095', 0.9512, -0.0910, '2026-07-13'),
 ('PROD-003095', 0.9520, 0.0795, '2026-07-14'),
@@ -2569,7 +2611,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-003095', 0.9511, 0.0636, '2026-09-01'),
 ('PROD-003095', 0.9504, -0.0713, '2026-09-02'),
 ('PROD-003095', 0.9507, 0.0276, '2026-09-03'),
-('PROD-003095', 0.9500, -0.0736, '2026-09-04'),
+('PROD-003095', 0.9499, -0.0872, '2026-09-04'),
+('PROD-003095', 0.9498, -0.0094, '2026-09-05'),
+('PROD-003095', 0.9503, 0.0548, '2026-09-06'),
+('PROD-003095', 0.9502, -0.0061, '2026-09-07'),
+('PROD-003095', 0.9507, 0.0524, '2026-09-08'),
+('PROD-003095', 0.9505, -0.0219, '2026-09-09'),
+('PROD-003095', 0.9503, -0.0241, '2026-09-10'),
+('PROD-003095', 0.9501, -0.0238, '2026-09-11'),
 ('PROD-510300', 1.0282, -0.0655, '2025-09-05'),
 ('PROD-510300', 1.0281, -0.0116, '2025-09-06'),
 ('PROD-510300', 1.0284, 0.0324, '2025-09-07'),
@@ -2934,7 +2983,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-510300', 1.0284, -0.0471, '2026-09-01'),
 ('PROD-510300', 1.0284, 0.0026, '2026-09-02'),
 ('PROD-510300', 1.0289, 0.0463, '2026-09-03'),
-('PROD-510300', 1.0300, 0.1069, '2026-09-04'),
+('PROD-510300', 1.0293, 0.0380, '2026-09-04'),
+('PROD-510300', 1.0290, -0.0299, '2026-09-05'),
+('PROD-510300', 1.0295, 0.0528, '2026-09-06'),
+('PROD-510300', 1.0294, -0.0073, '2026-09-07'),
+('PROD-510300', 1.0290, -0.0436, '2026-09-08'),
+('PROD-510300', 1.0285, -0.0503, '2026-09-09'),
+('PROD-510300', 1.0283, -0.0176, '2026-09-10'),
+('PROD-510300', 1.0280, -0.0303, '2026-09-11'),
 ('PROD-510500', 0.9841, -0.0745, '2025-09-05'),
 ('PROD-510500', 0.9837, -0.0367, '2025-09-06'),
 ('PROD-510500', 0.9844, 0.0667, '2025-09-07'),
@@ -2958,7 +3014,9 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-510500', 0.9855, 0.0179, '2025-09-25'),
 ('PROD-510500', 0.9854, -0.0071, '2025-09-26'),
 ('PROD-510500', 0.9855, 0.0136, '2025-09-27'),
-('PROD-510500', 0.9863, 0.0766, '2025-09-28'),
+('PROD-510500', 0.9863, 0.0766, '2025-09-28') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
+
+INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-510500', 0.9872, 0.0876, '2025-09-29'),
 ('PROD-510500', 0.9871, -0.0094, '2025-09-30'),
 ('PROD-510500', 0.9867, -0.0355, '2025-10-01'),
@@ -3014,9 +3072,7 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-510500', 0.9857, -0.0755, '2025-11-20'),
 ('PROD-510500', 0.9855, -0.0157, '2025-11-21'),
 ('PROD-510500', 0.9847, -0.0779, '2025-11-22'),
-('PROD-510500', 0.9851, 0.0379, '2025-11-23');
-
-INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
+('PROD-510500', 0.9851, 0.0379, '2025-11-23'),
 ('PROD-510500', 0.9844, -0.0673, '2025-11-24'),
 ('PROD-510500', 0.9845, 0.0143, '2025-11-25'),
 ('PROD-510500', 0.9842, -0.0353, '2025-11-26'),
@@ -3301,7 +3357,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-510500', 0.9803, 0.0860, '2026-09-01'),
 ('PROD-510500', 0.9804, 0.0075, '2026-09-02'),
 ('PROD-510500', 0.9798, -0.0565, '2026-09-03'),
-('PROD-510500', 0.9800, 0.0204, '2026-09-04'),
+('PROD-510500', 0.9805, 0.0716, '2026-09-04'),
+('PROD-510500', 0.9806, 0.0112, '2026-09-05'),
+('PROD-510500', 0.9803, -0.0330, '2026-09-06'),
+('PROD-510500', 0.9805, 0.0237, '2026-09-07'),
+('PROD-510500', 0.9811, 0.0613, '2026-09-08'),
+('PROD-510500', 0.9809, -0.0181, '2026-09-09'),
+('PROD-510500', 0.9804, -0.0487, '2026-09-10'),
+('PROD-510500', 0.9802, -0.0174, '2026-09-11'),
 ('PROD-XYZ999', 0.9064, -0.1494, '2025-09-05'),
 ('PROD-XYZ999', 0.9058, -0.0665, '2025-09-06'),
 ('PROD-XYZ999', 0.9046, -0.1313, '2025-09-07'),
@@ -3453,7 +3516,9 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-XYZ999', 0.9040, 0.0529, '2026-01-31'),
 ('PROD-XYZ999', 0.9036, -0.0489, '2026-02-01'),
 ('PROD-XYZ999', 0.9038, 0.0223, '2026-02-02'),
-('PROD-XYZ999', 0.9047, 0.1032, '2026-02-03'),
+('PROD-XYZ999', 0.9047, 0.1032, '2026-02-03') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
+
+INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-XYZ999', 0.9055, 0.0915, '2026-02-04'),
 ('PROD-XYZ999', 0.9052, -0.0370, '2026-02-05'),
 ('PROD-XYZ999', 0.9055, 0.0305, '2026-02-06'),
@@ -3516,9 +3581,7 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-XYZ999', 0.9075, 0.0194, '2026-04-04'),
 ('PROD-XYZ999', 0.9084, 0.1034, '2026-04-05'),
 ('PROD-XYZ999', 0.9079, -0.0529, '2026-04-06'),
-('PROD-XYZ999', 0.9074, -0.0502, '2026-04-07');
-
-INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
+('PROD-XYZ999', 0.9074, -0.0502, '2026-04-07'),
 ('PROD-XYZ999', 0.9061, -0.1416, '2026-04-08'),
 ('PROD-XYZ999', 0.9059, -0.0212, '2026-04-09'),
 ('PROD-XYZ999', 0.9061, 0.0248, '2026-04-10'),
@@ -3668,7 +3731,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-XYZ999', 0.9003, -0.0622, '2026-09-01'),
 ('PROD-XYZ999', 0.8992, -0.1269, '2026-09-02'),
 ('PROD-XYZ999', 0.8992, -0.0029, '2026-09-03'),
-('PROD-XYZ999', 0.9000, 0.0890, '2026-09-04'),
+('PROD-XYZ999', 0.8999, 0.0771, '2026-09-04'),
+('PROD-XYZ999', 0.9000, 0.0066, '2026-09-05'),
+('PROD-XYZ999', 0.8988, -0.1304, '2026-09-06'),
+('PROD-XYZ999', 0.8992, 0.0477, '2026-09-07'),
+('PROD-XYZ999', 0.9000, 0.0846, '2026-09-08'),
+('PROD-XYZ999', 0.8989, -0.1263, '2026-09-09'),
+('PROD-XYZ999', 0.8986, -0.0373, '2026-09-10'),
+('PROD-XYZ999', 0.8978, -0.0905, '2026-09-11'),
 ('PROD-000001', 1.0012, 0.0076, '2025-09-05'),
 ('PROD-000001', 1.0012, -0.0009, '2025-09-06'),
 ('PROD-000001', 1.0012, 0.0028, '2025-09-07'),
@@ -3948,7 +4018,9 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-000001', 1.0020, 0.0057, '2026-06-08'),
 ('PROD-000001', 1.0020, -0.0017, '2026-06-09'),
 ('PROD-000001', 1.0020, 0.0036, '2026-06-10'),
-('PROD-000001', 1.0021, 0.0075, '2026-06-11'),
+('PROD-000001', 1.0021, 0.0075, '2026-06-11') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
+
+INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-000001', 1.0021, 0.0029, '2026-06-12'),
 ('PROD-000001', 1.0021, 0.0011, '2026-06-13'),
 ('PROD-000001', 1.0020, -0.0051, '2026-06-14'),
@@ -4018,9 +4090,7 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-000001', 1.0033, -0.0001, '2026-08-17'),
 ('PROD-000001', 1.0033, -0.0028, '2026-08-18'),
 ('PROD-000001', 1.0033, -0.0043, '2026-08-19'),
-('PROD-000001', 1.0033, 0.0001, '2026-08-20');
-
-INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
+('PROD-000001', 1.0033, 0.0001, '2026-08-20'),
 ('PROD-000001', 1.0034, 0.0062, '2026-08-21'),
 ('PROD-000001', 1.0034, 0.0019, '2026-08-22'),
 ('PROD-000001', 1.0034, 0.0042, '2026-08-23'),
@@ -4035,7 +4105,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-000001', 1.0034, -0.0076, '2026-09-01'),
 ('PROD-000001', 1.0033, -0.0073, '2026-09-02'),
 ('PROD-000001', 1.0033, 0.0007, '2026-09-03'),
-('PROD-000001', 1.0020, -0.1296, '2026-09-04'),
+('PROD-000001', 1.0033, -0.0032, '2026-09-04'),
+('PROD-000001', 1.0032, -0.0079, '2026-09-05'),
+('PROD-000001', 1.0032, 0.0006, '2026-09-06'),
+('PROD-000001', 1.0032, -0.0011, '2026-09-07'),
+('PROD-000001', 1.0032, -0.0042, '2026-09-08'),
+('PROD-000001', 1.0031, -0.0058, '2026-09-09'),
+('PROD-000001', 1.0030, -0.0060, '2026-09-10'),
+('PROD-000001', 1.0030, -0.0027, '2026-09-11'),
 ('PROD-000002', 1.0074, 0.0236, '2025-09-05'),
 ('PROD-000002', 1.0072, -0.0178, '2025-09-06'),
 ('PROD-000002', 1.0073, 0.0066, '2025-09-07'),
@@ -4400,7 +4477,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-000002', 1.0045, 0.0184, '2026-09-01'),
 ('PROD-000002', 1.0042, -0.0264, '2026-09-02'),
 ('PROD-000002', 1.0041, -0.0070, '2026-09-03'),
-('PROD-000002', 1.0050, 0.0896, '2026-09-04'),
+('PROD-000002', 1.0044, 0.0296, '2026-09-04'),
+('PROD-000002', 1.0043, -0.0069, '2026-09-05'),
+('PROD-000002', 1.0040, -0.0282, '2026-09-06'),
+('PROD-000002', 1.0039, -0.0117, '2026-09-07'),
+('PROD-000002', 1.0038, -0.0121, '2026-09-08'),
+('PROD-000002', 1.0037, -0.0111, '2026-09-09'),
+('PROD-000002', 1.0036, -0.0073, '2026-09-10'),
+('PROD-000002', 1.0035, -0.0126, '2026-09-11'),
 ('PROD-WMG001', 1.0113, 0.0098, '2025-09-05'),
 ('PROD-WMG001', 1.0114, 0.0077, '2025-09-06'),
 ('PROD-WMG001', 1.0114, -0.0015, '2025-09-07'),
@@ -4436,7 +4520,9 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-WMG001', 1.0127, 0.0046, '2025-10-07'),
 ('PROD-WMG001', 1.0127, 0.0033, '2025-10-08'),
 ('PROD-WMG001', 1.0130, 0.0293, '2025-10-09'),
-('PROD-WMG001', 1.0129, -0.0069, '2025-10-10'),
+('PROD-WMG001', 1.0129, -0.0069, '2025-10-10') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
+
+INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-WMG001', 1.0129, -0.0045, '2025-10-11'),
 ('PROD-WMG001', 1.0132, 0.0301, '2025-10-12'),
 ('PROD-WMG001', 1.0131, -0.0148, '2025-10-13'),
@@ -4520,9 +4606,7 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-WMG001', 1.0119, -0.0257, '2025-12-30'),
 ('PROD-WMG001', 1.0119, -0.0013, '2025-12-31'),
 ('PROD-WMG001', 1.0118, -0.0119, '2026-01-01'),
-('PROD-WMG001', 1.0115, -0.0289, '2026-01-02');
-
-INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
+('PROD-WMG001', 1.0115, -0.0289, '2026-01-02'),
 ('PROD-WMG001', 1.0115, 0.0019, '2026-01-03'),
 ('PROD-WMG001', 1.0117, 0.0201, '2026-01-04'),
 ('PROD-WMG001', 1.0116, -0.0082, '2026-01-05'),
@@ -4767,7 +4851,14 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-WMG001', 1.0138, 0.0182, '2026-09-01'),
 ('PROD-WMG001', 1.0140, 0.0196, '2026-09-02'),
 ('PROD-WMG001', 1.0142, 0.0225, '2026-09-03'),
-('PROD-WMG001', 1.0150, 0.0789, '2026-09-04'),
+('PROD-WMG001', 1.0141, -0.0100, '2026-09-04'),
+('PROD-WMG001', 1.0138, -0.0253, '2026-09-05'),
+('PROD-WMG001', 1.0136, -0.0197, '2026-09-06'),
+('PROD-WMG001', 1.0140, 0.0366, '2026-09-07'),
+('PROD-WMG001', 1.0144, 0.0385, '2026-09-08'),
+('PROD-WMG001', 1.0142, -0.0217, '2026-09-09'),
+('PROD-WMG001', 1.0145, 0.0321, '2026-09-10'),
+('PROD-WMG001', 1.0143, -0.0187, '2026-09-11'),
 ('PROD-PRIV01', 1.0984, 0.0591, '2025-09-05'),
 ('PROD-PRIV01', 1.0987, 0.0261, '2025-09-06'),
 ('PROD-PRIV01', 1.0979, -0.0708, '2025-09-07'),
@@ -4931,7 +5022,9 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-PRIV01', 1.0835, 0.0063, '2026-02-12'),
 ('PROD-PRIV01', 1.0828, -0.0622, '2026-02-13'),
 ('PROD-PRIV01', 1.0836, 0.0776, '2026-02-14'),
-('PROD-PRIV01', 1.0837, 0.0086, '2026-02-15'),
+('PROD-PRIV01', 1.0837, 0.0086, '2026-02-15') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
+
+INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-PRIV01', 1.0839, 0.0227, '2026-02-16'),
 ('PROD-PRIV01', 1.0834, -0.0452, '2026-02-17'),
 ('PROD-PRIV01', 1.0833, -0.0061, '2026-02-18'),
@@ -5022,9 +5115,7 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-PRIV01', 1.0858, -0.0001, '2026-05-14'),
 ('PROD-PRIV01', 1.0862, 0.0384, '2026-05-15'),
 ('PROD-PRIV01', 1.0867, 0.0443, '2026-05-16'),
-('PROD-PRIV01', 1.0874, 0.0624, '2026-05-17');
-
-INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
+('PROD-PRIV01', 1.0874, 0.0624, '2026-05-17'),
 ('PROD-PRIV01', 1.0868, -0.0559, '2026-05-18'),
 ('PROD-PRIV01', 1.0876, 0.0772, '2026-05-19'),
 ('PROD-PRIV01', 1.0884, 0.0692, '2026-05-20'),
@@ -5134,4 +5225,11 @@ INSERT INTO core_product_nav (product_id, nav, daily_chg_pct, nav_date) VALUES
 ('PROD-PRIV01', 1.0807, 0.0652, '2026-09-01'),
 ('PROD-PRIV01', 1.0802, -0.0427, '2026-09-02'),
 ('PROD-PRIV01', 1.0792, -0.0919, '2026-09-03'),
-('PROD-PRIV01', 1.0800, 0.0741, '2026-09-04');
+('PROD-PRIV01', 1.0792, 0.0046, '2026-09-04'),
+('PROD-PRIV01', 1.0796, 0.0408, '2026-09-05'),
+('PROD-PRIV01', 1.0790, -0.0558, '2026-09-06'),
+('PROD-PRIV01', 1.0788, -0.0195, '2026-09-07'),
+('PROD-PRIV01', 1.0781, -0.0631, '2026-09-08'),
+('PROD-PRIV01', 1.0773, -0.0726, '2026-09-09'),
+('PROD-PRIV01', 1.0780, 0.0609, '2026-09-10'),
+('PROD-PRIV01', 1.0780, -0.0042, '2026-09-11') ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);
diff --git a/scripts/core/fetch_nav.py b/scripts/core/fetch_nav.py
index c1cb9e7..f8a12cc 100644
--- a/scripts/core/fetch_nav.py
+++ b/scripts/core/fetch_nav.py
@@ -28,9 +28,9 @@
 
 货币基金（`PROD-000001` 现金宝货币）
 ------------------------------------------------------------------
-真实业务中货币基金**单位净值恒为 1.0000 元**，收益以份额结转，不存在净值序列
-（实测：天弘余额宝 000198、广发钱袋子 000509 在该接口均无 `Data_netWorthTrend`）。
-故货基不联网，直接按真实业务生成恒定 1.0000、日涨幅 0。
+真实业务中货基**展示**单位净值常为 1.0000，但该接口也无可用 `Data_netWorthTrend`。
+演示库不与 06 写死平线：货基净值与 `seed_nav_history.py` / `07-seed-nav-history.sql`
+同源（锚定 1.0020 附近、低 beta 微波动），便于行情页看到走势与日涨跌。
 
 用法
 ------------------------------------------------------------------
@@ -74,15 +74,20 @@ NAV_SOURCE: dict[str, tuple[str, str, str]] = {
     "PROD-PRIV01": ("519062", "海富通阿尔法对冲混合A", "private_fund/R4：量化对冲，日波动 0.33%"),
 }
 
-# 货币基金：净值恒为 1.0000（真实业务，不联网）
+# 货币基金：不联网，曲线与 seed_nav_history / 07-seed 同源
 MONEY_FUNDS: dict[str, str] = {
-    "PROD-000001": "现金宝货币（money/R1：货基单位净值恒为 1 元，收益以份额结转）",
+    "PROD-000001": "现金宝货币（money/R1：演示用低波净值，见 seed_nav_history.py）",
 }
 
 DEFAULT_OUT = Path(__file__).with_name("06-seed-nav.sql")
 DEFAULT_DAYS = 60
 TIMEOUT = 30
 
+_SCRIPT_DIR = Path(__file__).resolve().parent
+if str(_SCRIPT_DIR) not in sys.path:
+    sys.path.insert(0, str(_SCRIPT_DIR))
+from seed_nav_history import nav_rows_for_product_dates  # noqa: E402
+
 
 # ── 抓取与解析 ───────────────────────────────────────────────────────────
 def fetch_js(code: str, cache_dir: Path | None) -> str:
@@ -119,7 +124,10 @@ def build_sql(rows: list[tuple[str, dt.date, float, float]], fetched_at: str) ->
         f"--   {pid:<13} <- {code} {name}（{why}）"
         for pid, (code, name, why) in sorted(NAV_SOURCE.items())
     )
-    money = "\n".join(f"--   {pid:<13} <- 恒定 1.0000（{why}）" for pid, why in sorted(MONEY_FUNDS.items()))
+    money = "\n".join(
+        f"--   {pid:<13} <- 演示曲线（{why}；与 07-seed-nav-history 同源）"
+        for pid, why in sorted(MONEY_FUNDS.items())
+    )
     dates = [r[1] for r in rows]
     head = (
         "USE jinrong_core;\n\n"
@@ -185,13 +193,13 @@ def main(argv: list[str] | None = None) -> int:
             rows.append((pid, day, nav, chg))
         print(f"[OK] {pid} <- {code} {name}：{len(series[-args.days:])} 条，最新 {series[-1][0]} {series[-1][1]}")
 
-    # 货币基金：净值恒定 1.0000
+    # 货币基金：与 07 种子同源的低波演示曲线（勿再写死 1.0000/0）
     if rows:
         money_days = sorted({r[1] for r in rows})
         for pid in sorted(MONEY_FUNDS):
-            for day in money_days:
-                rows.append((pid, day, 1.0000, 0.0))
-            print(f"[OK] {pid} <- 货基恒定净值 1.0000：{len(money_days)} 条")
+            sim = nav_rows_for_product_dates(pid, money_days)
+            rows.extend(sim)
+            print(f"[OK] {pid} <- 货基演示曲线（seed_nav_history）：{len(sim)} 条")
 
     if failed:
         print("\n[FAIL] 以下产品拉取失败：", file=sys.stderr)
diff --git a/scripts/core/seed_nav_history.py b/scripts/core/seed_nav_history.py
index 6d9126c..43d27ae 100644
--- a/scripts/core/seed_nav_history.py
+++ b/scripts/core/seed_nav_history.py
@@ -25,6 +25,8 @@ from sqlalchemy import text
 from app.config.database import get_core_engine
 
 ANCHOR_DATE = date(2026, 9, 4)
+# 与 06-seed-nav（fetch_nav --days 60）末日对齐，锚定日后继续微波动以免被 06 平线覆盖
+LATEST_NAV_DATE = date(2026, 9, 11)
 DAYS_BACK = 364  # 与锚定日合计约 365 个自然日
 SQL_OUT = Path(__file__).resolve().parent / "07-seed-nav-history.sql"
 
@@ -96,12 +98,8 @@ def build_history_rows() -> list[dict]:
         running = round(nav, 4)
         for i, d in enumerate(days_list):
             if i > 0:
-                if d == ANCHOR_DATE:
-                    chg = round(((anchor_nav - running) / running) * 100, 4)
-                    running = anchor_nav
-                else:
-                    chg = _product_daily_chg_pct(product_id, d)
-                    running = round(running * (1 + chg / 100.0), 4)
+                chg = _product_daily_chg_pct(product_id, d)
+                running = round(running * (1 + chg / 100.0), 4)
             else:
                 chg = _product_daily_chg_pct(product_id, d)
             rows.append(
@@ -112,9 +110,37 @@ def build_history_rows() -> list[dict]:
                     "daily_chg_pct": chg,
                 }
             )
+        d = ANCHOR_DATE
+        while d < LATEST_NAV_DATE:
+            d = d + timedelta(days=1)
+            chg = _product_daily_chg_pct(product_id, d)
+            running = round(running * (1 + chg / 100.0), 4)
+            rows.append(
+                {
+                    "product_id": product_id,
+                    "nav_date": d.isoformat(),
+                    "nav": running,
+                    "daily_chg_pct": chg,
+                }
+            )
     return rows
 
 
+def nav_rows_for_product_dates(
+    product_id: str, days: list[date], *, rows: list[dict] | None = None
+) -> list[tuple[str, date, float, float]]:
+    """按自然日取单产品净值（供 fetch_nav 货基演示曲线，与 07 同源）。"""
+    rows = rows or build_history_rows()
+    index = {(r["product_id"], r["nav_date"]): r for r in rows}
+    out: list[tuple[str, date, float, float]] = []
+    for day in days:
+        r = index.get((product_id, day.isoformat()))
+        if not r:
+            continue
+        out.append((product_id, day, float(r["nav"]), float(r["daily_chg_pct"])))
+    return out
+
+
 def anchor_rows_for_seed06(rows: list[dict] | None = None) -> list[dict]:
     rows = rows or build_history_rows()
     anchor = ANCHOR_DATE.isoformat()
@@ -150,7 +176,10 @@ def export_sql(path: Path = SQL_OUT, *, batch_size: int = 500) -> int:
             f"('{r['product_id']}', {r['nav']:.4f}, {r['daily_chg_pct']:.4f}, '{r['nav_date']}')"
             for r in chunk
         ]
-        lines.append(",\n".join(value_lines) + ";")
+        lines.append(
+            ",\n".join(value_lines)
+            + " ON DUPLICATE KEY UPDATE nav = VALUES(nav), daily_chg_pct = VALUES(daily_chg_pct);"
+        )
         lines.append("")
     path.write_text("\n".join(lines), encoding="utf-8")
     return len(rows)
diff --git a/tests/test_platform_common.py b/tests/test_platform_common.py
new file mode 100644
index 0000000..058e711
--- /dev/null
+++ b/tests/test_platform_common.py
@@ -0,0 +1,11 @@
+from decimal import Decimal
+
+from app.service.platform.common import to_jsonable
+
+
+def test_to_jsonable_nav_keeps_four_decimals():
+    row = {"nav": Decimal("1.0017"), "daily_chg_pct": Decimal("-0.0027"), "amount": Decimal("1234.567")}
+    out = to_jsonable(row)
+    assert out["nav"] == 1.0017
+    assert out["daily_chg_pct"] == -0.0027
+    assert out["amount"] == 1234.57
diff --git a/web/src/App.tsx b/web/src/App.tsx
index 4cd34c9..6d91a11 100644
--- a/web/src/App.tsx
+++ b/web/src/App.tsx
@@ -24,6 +24,7 @@ import { AdvisorKycPage } from './pages/advisor/AdvisorKycPage'
 import { AdvisorMarketAlertsPage } from './pages/advisor/AdvisorMarketAlertsPage'
 import { MarketQuotesPage } from './pages/market/MarketQuotesPage'
 import { ProductNavDetailPage } from './pages/market/ProductNavDetailPage'
+import { KnowledgeBasePage } from './pages/knowledge/KnowledgeBasePage'
 import { RiskAlertsPage } from './pages/risk/RiskAlertsPage'
 import { RiskChatPage } from './pages/risk/RiskChatPage'
 import { RiskSimulatePage } from './pages/risk/RiskSimulatePage'
@@ -144,6 +145,8 @@ export default function AppRoutes() {
         <Route path="risk/convert" element={<RiskConvertPage />} />
         <Route path="risk/chat" element={<RiskChatPage />} />
 
+        <Route path="knowledge" element={<KnowledgeBasePage />} />
+
         <Route path="market" element={<MarketQuotesPage />} />
         <Route path="market/:productId" element={<ProductNavDetailPage />} />
       </Route>
diff --git a/web/src/api/kb.ts b/web/src/api/kb.ts
new file mode 100644
index 0000000..e6011c4
--- /dev/null
+++ b/web/src/api/kb.ts
@@ -0,0 +1,24 @@
+import { apiFetch } from './client'
+
+export type VectorCollection = {
+  name: string
+  title: string
+  description: string
+  row_count: number
+  dimension: number
+  fields: string[]
+  sample: Record<string, unknown>[]
+}
+
+export type VectorCollectionsResponse = {
+  items: VectorCollection[]
+  total_collections: number
+  total_vectors: number
+}
+
+export async function listVectorCollections(token: string) {
+  const { data } = await apiFetch<VectorCollectionsResponse>('/api/milvus/collections', {
+    token,
+  })
+  return data
+}
diff --git a/web/src/pages/knowledge/KnowledgeBasePage.tsx b/web/src/pages/knowledge/KnowledgeBasePage.tsx
new file mode 100644
index 0000000..b04f36a
--- /dev/null
+++ b/web/src/pages/knowledge/KnowledgeBasePage.tsx
@@ -0,0 +1,145 @@
+import { Alert, Spin, Table, Tag, Typography } from 'antd'
+import type { ColumnsType } from 'antd/es/table'
+import { useEffect, useState } from 'react'
+import { listVectorCollections, type VectorCollection } from '../../api/kb'
+import { ApiErrorResult } from '../../components/ApiErrorResult'
+import { PageShell } from '../../components/PageShell'
+import { EmptyState, MetricCard, Surface } from '../../components/ui'
+import { useAppAuth } from '../../layouts/AppLayout'
+
+function formatCell(value: unknown): string {
+  if (value === null || value === undefined || value === '') return '—'
+  if (typeof value === 'boolean') return value ? '是' : '否'
+  if (typeof value === 'object') return JSON.stringify(value)
+  return String(value)
+}
+
+function SampleTable({ collection }: { collection: VectorCollection }) {
+  if (!collection.sample.length) {
+    return <Typography.Text type="secondary">暂无样本（该库为空）</Typography.Text>
+  }
+  const columns: ColumnsType<Record<string, unknown>> = collection.fields.map((f) => ({
+    title: f,
+    dataIndex: f,
+    ellipsis: true,
+    render: (v: unknown) => (
+      <span className="tabular-nums text-jr-text">{formatCell(v)}</span>
+    ),
+  }))
+  return (
+    <Table<Record<string, unknown>>
+      rowKey="id"
+      size="small"
+      columns={columns}
+      dataSource={collection.sample}
+      pagination={false}
+      scroll={{ x: 'max-content' }}
+      title={() => (
+        <Typography.Text type="secondary" className="!text-xs">
+          样本预览（最多 {collection.sample.length} 条）
+        </Typography.Text>
+      )}
+    />
+  )
+}
+
+export function KnowledgeBasePage() {
+  const auth = useAppAuth()
+  const [items, setItems] = useState<VectorCollection[]>([])
+  const [totals, setTotals] = useState({ total_collections: 0, total_vectors: 0 })
+  const [loading, setLoading] = useState(true)
+  const [error, setError] = useState<Error | null>(null)
+  const [reload, setReload] = useState(0)
+
+  useEffect(() => {
+    let cancelled = false
+    setLoading(true)
+    setError(null)
+    listVectorCollections(auth.accessToken)
+      .then((data) => {
+        if (cancelled) return
+        setItems(data.items ?? [])
+        setTotals({
+          total_collections: data.total_collections ?? 0,
+          total_vectors: data.total_vectors ?? 0,
+        })
+      })
+      .catch((e) => {
+        if (!cancelled) setError(e instanceof Error ? e : new Error('load failed'))
+      })
+      .finally(() => {
+        if (!cancelled) setLoading(false)
+      })
+    return () => {
+      cancelled = true
+    }
+  }, [auth.accessToken, reload])
+
+  return (
+    <PageShell
+      title="向量知识库"
+      crumbs={[{ title: '平台服务' }, { title: '向量知识库' }]}
+    >
+      <Alert
+        type="info"
+        showIcon
+        className="mb-6"
+        message="只读展示"
+        description="展示 Milvus 向量库的概览与样本，仅供查看，不支持增删改。"
+      />
+
+      <div className="grid gap-4 sm:grid-cols-2">
+        <MetricCard
+          label="向量库数量"
+          value={totals.total_collections}
+          detail="Milvus collections"
+        />
+        <MetricCard
+          label="向量总数"
+          value={totals.total_vectors}
+          detail="已入库向量条数"
+        />
+      </div>
+
+      {error && (
+        <ApiErrorResult
+          error={error}
+          onRetry={() => {
+            setError(null)
+            setReload((n) => n + 1)
+          }}
+        />
+      )}
+
+      {!error && (
+        <Spin spinning={loading}>
+          {items.length === 0 && !loading ? (
+            <Surface padding="lg">
+              <EmptyState
+                title="暂无向量库"
+                description="Milvus 中还没有可展示的 collection，请先运行知识库入库脚本。"
+              />
+            </Surface>
+          ) : (
+            items.map((c) => (
+              <Surface key={c.name} padding="lg" className="space-y-3">
+                <div className="flex flex-wrap items-center gap-2">
+                  <Typography.Text strong className="text-base text-jr-ink">
+                    {c.title}
+                  </Typography.Text>
+                  <Tag color="blue">{c.name}</Tag>
+                  <Tag>{c.row_count} 条</Tag>
+                  <Tag>{c.dimension} 维</Tag>
+                </div>
+                <Typography.Paragraph type="secondary" className="!mb-0 !text-sm">
+                  {c.description}
+                </Typography.Paragraph>
+                <SampleTable collection={c} />
+              </Surface>
+            ))
+          )}
+        </Spin>
+      )}
+    </PageShell>
+  )
+}
diff --git a/web/src/routes/menus.tsx b/web/src/routes/menus.tsx
index c679b2e..9e675c0 100644
--- a/web/src/routes/menus.tsx
+++ b/web/src/routes/menus.tsx
@@ -3,6 +3,7 @@ import {
   BarChartOutlined,
   CheckCircleOutlined,
   CommentOutlined,
+  DatabaseOutlined,
   FileTextOutlined,
   FormOutlined,
   HomeOutlined,
@@ -32,6 +33,7 @@ export type RouteMenuGroup = {
 const sharedPlatform: RouteMenuLeaf[] = [
   { key: '/app/market', icon: <LineChartOutlined />, label: '产品行情', path: '/app/market' },
   { key: '/app/analytics/query', icon: <BarChartOutlined />, label: '数据分析', path: '/app/analytics/query' },
+  { key: '/app/knowledge', icon: <DatabaseOutlined />, label: '向量知识库', path: '/app/knowledge' },
 ]
 
 export function buildMenuGroups(roleLabel: string): RouteMenuGroup[] {
@@ -116,7 +118,10 @@ export function buildMenuGroups(roleLabel: string): RouteMenuGroup[] {
         {
           type: 'group',
           label: '平台服务',
-          children: [{ key: '/app/market', icon: <LineChartOutlined />, label: '产品行情', path: '/app/market' }],
+          children: [
+            { key: '/app/market', icon: <LineChartOutlined />, label: '产品行情', path: '/app/market' },
+            { key: '/app/knowledge', icon: <DatabaseOutlined />, label: '向量知识库', path: '/app/knowledge' },
+          ],
         },
       ]
     case '风控':