diff --git a/src/lib/measurements/__tests__/daily-series-read-tiered.test.ts b/src/lib/measurements/__tests__/daily-series-read-tiered.test.ts
new file mode 100644
index 000000000..dca7b0525
--- /dev/null
+++ b/src/lib/measurements/__tests__/daily-series-read-tiered.test.ts
@@ -0,0 +1,157 @@
+/**
+ * v1.19.2 W-CHARTS — `readDailySeries` long-range tier step-up.
+ *
+ * Pins that a window WIDER than the DAY bucket cap routes through the
+ * tiered rollup reader (whole-history coverage, downsampled by tier)
+ * instead of the DAY path that would `LIMIT`/`slice` to the cap and
+ * silently drop the older history. Short / normal windows must NOT touch
+ * the tiered reader, so the common case stays byte-identical with the
+ * pre-v1.19.2 daily path (no perf regression).
+ */
+import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
+
+const mocks = vi.hoisted(() => ({
+  findMany: vi.fn(),
+  queryRaw: vi.fn(),
+  readTieredRollupSeries: vi.fn(),
+}));
+
+vi.mock("@/lib/db", () => ({
+  prisma: {
+    measurementRollup: { findMany: mocks.findMany },
+    $queryRaw: mocks.queryRaw,
+  },
+}));
+
+vi.mock("@/lib/rollups/measurement-read-wmy", () => ({
+  readTieredRollupSeries: mocks.readTieredRollupSeries,
+}));
+
+vi.mock("@/lib/rollups/measurement-rollups", () => ({
+  recomputeUserRollups: vi.fn(),
+}));
+
+import { readDailySeries } from "../daily-series-read";
+
+const DAY_MS = 86_400_000;
+
+beforeEach(() => {
+  mocks.findMany.mockReset();
+  mocks.queryRaw.mockReset();
+  mocks.readTieredRollupSeries.mockReset();
+  // Default DAY-rollup read returns enough rows (≥ SUSPICIOUS_ROW_FLOOR)
+  // so the short-window path resolves without the coverage probe / live
+  // query firing.
+  mocks.findMany.mockResolvedValue([
+    {
+      type: "WEIGHT",
+      source: "MANUAL",
+      bucketStart: new Date("2026-06-01T00:00:00.000Z"),
+      mean: 81,
+      count: 1,
+      sumValue: null,
+      minValue: 81,
+      maxValue: 81,
+    },
+    {
+      type: "WEIGHT",
+      source: "MANUAL",
+      bucketStart: new Date("2026-06-02T00:00:00.000Z"),
+      mean: 82,
+      count: 1,
+      sumValue: null,
+      minValue: 82,
+      maxValue: 82,
+    },
+    {
+      type: "WEIGHT",
+      source: "MANUAL",
+      bucketStart: new Date("2026-06-03T00:00:00.000Z"),
+      mean: 80,
+      count: 1,
+      sumValue: null,
+      minValue: 80,
+      maxValue: 80,
+    },
+  ]);
+});
+
+afterEach(() => {
+  vi.restoreAllMocks();
+});
+
+describe("readDailySeries — long-range tier step-up", () => {
+  it("routes a multi-year window through the tiered reader and returns its whole-history rows", async () => {
+    const to = new Date("2026-06-21T00:00:00.000Z");
+    const from = new Date(to.getTime() - 3650 * DAY_MS);
+    const tieredRows = [
+      {
+        type: "WEIGHT",
+        value: 80,
+        measuredAt: "2017-01-01T00:00:00.000Z",
+        count: 12,
+      },
+      {
+        type: "WEIGHT",
+        value: 79,
+        measuredAt: "2026-01-01T00:00:00.000Z",
+        count: 12,
+      },
+    ];
+    mocks.readTieredRollupSeries.mockResolvedValueOnce({
+      granularity: "MONTH",
+      rows: tieredRows,
+    });
+
+    const result = await readDailySeries({
+      userId: "u",
+      type: "WEIGHT",
+      from,
+      to,
+      priorityJson: null,
+    });
+
+    expect(mocks.readTieredRollupSeries).toHaveBeenCalledTimes(1);
+    expect(mocks.readTieredRollupSeries.mock.calls[0][0].windowDays).toBe(3650);
+    // Whole-history coverage: the earliest 2017 bucket survives.
+    expect(result[0].measuredAt).toBe("2017-01-01T00:00:00.000Z");
+    expect(result).toHaveLength(2);
+    // The DAY-rollup path was NOT consulted for the long window.
+    expect(mocks.findMany).not.toHaveBeenCalled();
+  });
+
+  it("falls through to the daily path on a tiered coverage miss (no silent empty)", async () => {
+    const to = new Date("2026-06-21T00:00:00.000Z");
+    const from = new Date(to.getTime() - 3650 * DAY_MS);
+    mocks.readTieredRollupSeries.mockResolvedValueOnce(null);
+
+    const result = await readDailySeries({
+      userId: "u",
+      type: "WEIGHT",
+      from,
+      to,
+      priorityJson: null,
+    });
+
+    expect(mocks.readTieredRollupSeries).toHaveBeenCalledTimes(1);
+    // Daily DAY-rollup read still ran as the fallback.
+    expect(mocks.findMany).toHaveBeenCalled();
+    expect(result).toHaveLength(3);
+  });
+
+  it("does NOT touch the tiered reader for a normal 90-day window", async () => {
+    const to = new Date("2026-06-21T00:00:00.000Z");
+    const from = new Date(to.getTime() - 90 * DAY_MS);
+
+    await readDailySeries({
+      userId: "u",
+      type: "WEIGHT",
+      from,
+      to,
+      priorityJson: null,
+    });
+
+    expect(mocks.readTieredRollupSeries).not.toHaveBeenCalled();
+    expect(mocks.findMany).toHaveBeenCalled();
+  });
+});
diff --git a/src/lib/measurements/daily-series-read.ts b/src/lib/measurements/daily-series-read.ts
index 969c8f140..8759c4e72 100644
--- a/src/lib/measurements/daily-series-read.ts
+++ b/src/lib/measurements/daily-series-read.ts
@@ -20,6 +20,7 @@ import { prisma } from "@/lib/db";
 import { BUCKET_CAP } from "@/lib/measurements/range-aggregation";
 import { CUMULATIVE_HK_TYPES } from "@/lib/measurements/apple-health-mapping";
 import { collapseRollupRowsBySource } from "@/lib/rollups/measurement-read";
+import { readTieredRollupSeries } from "@/lib/rollups/measurement-read-wmy";
 import { recomputeUserRollups } from "@/lib/rollups/measurement-rollups";
 import { buildSourceRankCase } from "@/lib/analytics/source-rank-sql";
 import { annotate } from "@/lib/logging/context";
@@ -59,6 +60,45 @@ export async function readDailySeries(opts: {
   const { userId, type, from, to, priorityJson } = opts;
   const cap = Math.min(opts.limit ?? BUCKET_CAP.daily, BUCKET_CAP.daily);
 
+  // v1.19.2 — whole-history step-up for very long ranges. When the
+  // requested window holds more days than the DAY bucket cap can carry,
+  // the daily path below would `LIMIT`/`slice` to `cap` (365) buckets and
+  // silently drop the older history — a multi-year "Alle" range collapsed
+  // to roughly the most recent year. Step UP the bucket tier
+  // (DAY → WEEK → MONTH → YEAR) so the series spans the whole window
+  // inside a sane point budget instead. The chart's own `bucketTimeSeries`
+  // downsampler already renders week / month points for long ranges, so a
+  // coarser server tier is the resolution it would have collapsed to
+  // anyway — minus the truncation. Short / normal ranges (≤ cap days)
+  // never enter this branch and stay byte-identical with the prior daily
+  // path, so there is no perf regression for the common case.
+  const windowDaysFull = Math.ceil(
+    (to.getTime() - from.getTime()) / 86_400_000,
+  );
+  if (windowDaysFull > cap) {
+    const tiered = await readTieredRollupSeries({
+      userId,
+      type,
+      windowDays: windowDaysFull,
+      priorityJson,
+    });
+    if (tiered && tiered.rows.length > 0) {
+      return tiered.rows;
+    }
+    // Coverage miss at every tier — fall through to the daily path, which
+    // probes the live table and folds an under-converged window. The
+    // daily fallback still caps at `cap`; the annotate below records that
+    // the long-range read could not step up so a truncated daily slice is
+    // an explicit, logged outcome rather than a silent one.
+    annotate({
+      meta: {
+        tiered_series_coverage_miss: true,
+        window_days: windowDaysFull,
+        type,
+      },
+    });
+  }
+
   const readRollup = async () =>
     collapseRollupRowsBySource(
       await prisma.measurementRollup.findMany({
diff --git a/src/lib/rollups/__tests__/measurement-read-wmy.test.ts b/src/lib/rollups/__tests__/measurement-read-wmy.test.ts
index f47c6dffa..733937bb6 100644
--- a/src/lib/rollups/__tests__/measurement-read-wmy.test.ts
+++ b/src/lib/rollups/__tests__/measurement-read-wmy.test.ts
@@ -44,6 +44,7 @@ vi.mock("@/lib/db", () => ({
 import {
   aggregateWmyBuckets,
   readBestGranularityRollups,
+  readTieredRollupSeries,
   type RollupBucketRow,
 } from "../measurement-read-wmy";
 
@@ -286,3 +287,126 @@ describe("readBestGranularityRollups — cross-consumer routing parity", () => {
     expect(monthAgg.mean).toBeCloseTo(dayAgg.mean ?? Number.NaN, 5);
   });
 });
+
+/**
+ * v1.19.2 W-CHARTS — whole-history series reader. Pins that a very long
+ * "Alle" window reads the display-matching coarse tier (WEEK for 1–2 y,
+ * MONTH beyond) and returns coverage spanning the FULL span rather than a
+ * truncated recent slice; that the finer fallback rescues a coverage
+ * miss; and that the wire shape mirrors the daily reader.
+ */
+describe("readTieredRollupSeries", () => {
+  it("returns null on a non-positive window without touching the db", async () => {
+    expect(
+      await readTieredRollupSeries({
+        userId: "u",
+        type: "WEIGHT",
+        windowDays: 0,
+      }),
+    ).toBeNull();
+    expect(findMany).not.toHaveBeenCalled();
+  });
+
+  it("reads the MONTH tier for a multi-year window and spans the whole history", async () => {
+    // 10-year window → MONTH tier. The fixture carries buckets from the
+    // OLDEST month through the most recent — the result must keep the
+    // oldest bucket, proving no recent-slice truncation.
+    const months: RollupBucketRow[] = [];
+    for (let y = 2017; y <= 2026; y++) {
+      months.push(bucket(`${y}-01-01T00:00:00.000Z`, { count: 12, mean: 80 }));
+    }
+    findMany.mockResolvedValueOnce(months);
+
+    const result = await readTieredRollupSeries({
+      userId: "u",
+      type: "WEIGHT",
+      windowDays: 3650,
+    });
+
+    expect(result).not.toBeNull();
+    expect(result?.granularity).toBe("MONTH");
+    expect(findMany.mock.calls[0][0].where.granularity).toBe("MONTH");
+    // Whole-history coverage: the earliest 2017 bucket survives.
+    expect(result?.rows[0].measuredAt).toBe("2017-01-01T00:00:00.000Z");
+    expect(result?.rows.at(-1)?.measuredAt).toBe("2026-01-01T00:00:00.000Z");
+    expect(result?.rows.length).toBe(10);
+  });
+
+  it("reads the WEEK tier for a 1–2 year window", async () => {
+    findMany.mockResolvedValueOnce([bucket("2025-08-04T00:00:00.000Z")]);
+    const result = await readTieredRollupSeries({
+      userId: "u",
+      type: "WEIGHT",
+      windowDays: 540,
+    });
+    expect(result?.granularity).toBe("WEEK");
+    expect(findMany.mock.calls[0][0].where.granularity).toBe("WEEK");
+  });
+
+  it("falls FINER (MONTH → WEEK → DAY) when the target tier has no coverage", async () => {
+    findMany
+      .mockResolvedValueOnce([]) // MONTH miss
+      .mockResolvedValueOnce([]) // WEEK miss
+      .mockResolvedValueOnce([bucket("2024-03-01T00:00:00.000Z")]); // DAY hit
+    const result = await readTieredRollupSeries({
+      userId: "u",
+      type: "WEIGHT",
+      windowDays: 3650,
+    });
+    expect(result?.granularity).toBe("DAY");
+    expect(findMany.mock.calls[0][0].where.granularity).toBe("MONTH");
+    expect(findMany.mock.calls[1][0].where.granularity).toBe("WEEK");
+    expect(findMany.mock.calls[2][0].where.granularity).toBe("DAY");
+  });
+
+  it("returns null when no tier at or below the target carries coverage", async () => {
+    findMany.mockResolvedValue([]);
+    const result = await readTieredRollupSeries({
+      userId: "u",
+      type: "WEIGHT",
+      windowDays: 3650,
+    });
+    expect(result).toBeNull();
+    // MONTH, WEEK, DAY all probed (never coarser than the target).
+    expect(findMany).toHaveBeenCalledTimes(3);
+  });
+
+  it("surfaces the cumulative summed total for SUM metrics and drops the spread", async () => {
+    findMany.mockResolvedValueOnce([
+      bucket("2025-01-01T00:00:00.000Z", {
+        count: 30,
+        mean: 8000,
+        sumValue: 240_000,
+        minValue: 0,
+        maxValue: 20_000,
+      }),
+    ]);
+    const result = await readTieredRollupSeries({
+      userId: "u",
+      type: "ACTIVITY_STEPS",
+      windowDays: 3650,
+    });
+    expect(result?.rows[0].value).toBe(240_000);
+    expect(result?.rows[0].minValue).toBeUndefined();
+    expect(result?.rows[0].maxValue).toBeUndefined();
+  });
+
+  it("carries the count-weighted mean + spread for spot metrics", async () => {
+    findMany.mockResolvedValueOnce([
+      bucket("2025-01-01T00:00:00.000Z", {
+        count: 12,
+        mean: 81.5,
+        minValue: 78,
+        maxValue: 85,
+      }),
+    ]);
+    const result = await readTieredRollupSeries({
+      userId: "u",
+      type: "WEIGHT",
+      windowDays: 3650,
+    });
+    expect(result?.rows[0].value).toBe(81.5);
+    expect(result?.rows[0].minValue).toBe(78);
+    expect(result?.rows[0].maxValue).toBe(85);
+  });
+});
diff --git a/src/lib/rollups/measurement-read-wmy.ts b/src/lib/rollups/measurement-read-wmy.ts
index 7d9222ec7..46eb1235d 100644
--- a/src/lib/rollups/measurement-read-wmy.ts
+++ b/src/lib/rollups/measurement-read-wmy.ts
@@ -61,6 +61,8 @@ import type {
 } from "@/generated/prisma/client";
 
 import { prisma } from "@/lib/db";
+import { CUMULATIVE_HK_TYPES } from "@/lib/measurements/apple-health-mapping";
+import { annotate } from "@/lib/logging/context";
 import {
   collapseRollupRowsBySource,
   loadUserSourcePriority,
@@ -272,3 +274,135 @@ async function readGranularity(
     maxValue: r.maxValue,
   }));
 }
+
+/**
+ * Wire-row shape the chart-data client consumes — mirrors
+ * `DailySeriesRow` in `daily-series-read.ts` so a tier-stepped series
+ * interleaves with the daily path without the caller branching on the
+ * source granularity. `measuredAt` is the bucket-start ISO string at the
+ * resolved tier (one row per DAY / WEEK / MONTH / YEAR bucket).
+ */
+export interface TieredSeriesRow {
+  type: string;
+  value: number;
+  measuredAt: string;
+  count: number;
+  minValue?: number | null;
+  maxValue?: number | null;
+}
+
+/**
+ * Pick the rollup granularity that matches the chart's own client-side
+ * `bucketTimeSeries` downsampler (`src/lib/charts/bucket-time-series.ts`):
+ *
+ *   - > 730 days  → MONTH (the chart renders month points)
+ *   - 366–730     → WEEK  (the chart renders week points)
+ *   - ≤ 365       → DAY   (daily resolution; the DAY cap covers it)
+ *
+ * Mirroring the display tier means the server returns exactly the
+ * resolution the chart will paint — no finer (which would truncate at the
+ * DAY cap) and no coarser (which would drop visible detail). The finer
+ * fallback in `readTieredRollupSeries` still rescues a tenant whose
+ * coarse buckets the worker has not minted yet.
+ */
+function pickRollupGranularityForWindow(windowDays: number): RollupGranularity {
+  if (windowDays > 730) return "MONTH";
+  if (windowDays > 365) return "WEEK";
+  return "DAY";
+}
+
+/** DAY → WEEK → MONTH → YEAR ordering for the finer-fallback walk. */
+const TIER_ORDER: RollupGranularity[] = ["DAY", "WEEK", "MONTH", "YEAR"];
+
+/**
+ * v1.19.2 — whole-history series reader for very long chart ranges.
+ *
+ * The DAY-only `readDailySeries` reader caps its result at
+ * `BUCKET_CAP.daily` (365) buckets. A multi-year "Alle" range therefore
+ * silently truncated to roughly the most recent year — the older history
+ * never reached the client even though the chart's own
+ * `bucketTimeSeries` downsampler would have rendered it as week / month
+ * points. This reader closes that gap by reading the bucket tier that
+ * matches the chart's display granularity (WEEK for 1–2 years, MONTH
+ * beyond), so the returned series spans the WHOLE requested window inside
+ * a sane point budget instead of being chopped to a recent slice.
+ *
+ * The tier is purely a downsampling choice: `count` and the
+ * count-weighted `mean` compose identically across any granularity (see
+ * the compositional contract above), so a 5-year window rendered as ~60
+ * MONTH points carries the same trend as the ~1 800 DAY points would have
+ * — minus the truncation. `minValue` / `maxValue` ride through for the
+ * range band on spot metrics; cumulative metrics (steps, energy,
+ * distance) surface the bucket's summed total and drop the spread.
+ *
+ * Coverage handling: the target tier is read first; on a coverage miss
+ * (the boot backfill / worker has not minted the coarse buckets yet) the
+ * reader walks FINER (MONTH → WEEK → DAY) so a tenant still gets a usable
+ * series rather than an empty chart. Returns `null` only when no tier at
+ * or below the target carries any buckets for the window — the caller
+ * then falls through to its live-SQL path.
+ *
+ * The result is NOT capped — the tier selection bounds the row count
+ * (≤ ~104 weeks for the WEEK tier, ≤ ~12 months/year for MONTH). If a
+ * future tier ever risks an unbounded count it must step coarser rather
+ * than truncate; no silent cap lives on this path.
+ */
+export async function readTieredRollupSeries(opts: {
+  userId: string;
+  type: MeasurementType;
+  windowDays: number;
+  priorityJson?: unknown;
+}): Promise<{
+  granularity: RollupGranularity;
+  rows: TieredSeriesRow[];
+} | null> {
+  const { userId, type, windowDays, priorityJson } = opts;
+  if (!Number.isFinite(windowDays) || windowDays <= 0) return null;
+
+  const since = new Date(Date.now() - windowDays * 24 * 60 * 60 * 1000);
+  const priority =
+    priorityJson !== undefined
+      ? priorityJson
+      : await loadUserSourcePriority(userId);
+
+  const target = pickRollupGranularityForWindow(windowDays);
+  // Walk the target tier first, then finer (never coarser — coarser would
+  // drop detail the chart can render). Stop at the first tier with coverage.
+  const targetIdx = TIER_ORDER.indexOf(target);
+  for (let i = targetIdx; i >= 0; i--) {
+    const granularity = TIER_ORDER[i];
+    const rows = await readGranularity(
+      userId,
+      type,
+      granularity,
+      since,
+      priority,
+    );
+    if (rows && rows.length > 0) {
+      const useSum = CUMULATIVE_HK_TYPES.has(type);
+      annotate({
+        action: { name: "measurement.list" },
+        meta: {
+          total: rows.length,
+          type,
+          aggregate: "tiered",
+          granularity,
+          target_granularity: target,
+          source: "rollup",
+        },
+      });
+      return {
+        granularity,
+        rows: rows.map((r) => ({
+          type,
+          value: useSum ? (r.sumValue ?? r.mean * r.count) : r.mean,
+          measuredAt: r.bucketStart.toISOString(),
+          count: r.count,
+          minValue: useSum ? undefined : r.minValue,
+          maxValue: useSum ? undefined : r.maxValue,
+        })),
+      };
+    }
+  }
+  return null;
+}