@@ -120,7 +120,7 @@ describe('connector lease ACL pages in PostgreSQL', () => {
         RETURN NEW;
       END $$`)
     )
-    for (const projection of ['embedding_search', 'embedding_keyword_tin']) {
+    for (const projection of ['embedding_search']) {
       await db.execute(
         sql.raw(`DROP TRIGGER IF EXISTS log_lease_page_projection_write ON ${projection}`)
       )
@@ -151,7 +151,7 @@ describe('connector lease ACL pages in PostgreSQL', () => {
     await db.execute(sql`DROP FUNCTION IF EXISTS log_lease_page_acl_write()`)
     await db.execute(sql`DROP FUNCTION IF EXISTS fail_after_acl_writes()`)
     await db.execute(sql`DROP TABLE IF EXISTS lease_page_acl_writes`)
-    for (const projection of ['embedding_search', 'embedding_keyword_tin'])
+    for (const projection of ['embedding_search'])
       await db.execute(
         sql.raw(`DROP TRIGGER IF EXISTS log_lease_page_projection_write ON ${projection}`)
       )
@@ -300,25 +300,14 @@ describe('connector lease ACL pages in PostgreSQL', () => {
       )
       for (let offset = 0; offset < rows.length; offset += 200)
         await db.insert(embedding).values(rows.slice(offset, offset + 200))
-      /**
-       * Each chunk's projection rows, filled from its document as the backfill leaves them. The
-       * embedding insert writes the vector projection's row; the keyword projection's own sync
-       * trigger ships with the Tin migration, which a database without Tin skips. The fixture sets
-       * the filled state itself, whatever triggers an earlier suite left behind; what is under
-       * test is the document trigger that rewrites these rows.
-       */
+      /** Seeds the filled vector state whose ACL updates must stay bounded. */
       const chunkIds = sql.join(
         documents.map((entry) => sql`${entry.id}`),
         sql`, `
       )
       await db.execute(sql`
         UPDATE embedding_search p SET enabled = true, connector_id = d.connector_id, acl = d.acl
         FROM document d WHERE d.id = p.document_id AND d.id IN (${chunkIds})`)
-      await db.execute(sql`
-        INSERT INTO embedding_keyword_tin (id, knowledge_base_id, document_id, enabled, content, connector_id, acl)
-        SELECT e.id, e.knowledge_base_id, e.document_id, true, e.content, d.connector_id, d.acl
-        FROM embedding e JOIN document d ON d.id = e.document_id WHERE e.document_id IN (${chunkIds})
-        ON CONFLICT (id) DO UPDATE SET enabled = true, connector_id = EXCLUDED.connector_id, acl = EXCLUDED.acl`)
       /** Only writes made by the code under test are counted. */
       await db.execute(sql`DELETE FROM lease_page_projection_writes`)
       await db
@@ -337,10 +326,7 @@ describe('connector lease ACL pages in PostgreSQL', () => {
       db.execute<{ projection: string; acl: string | null; expected: string }>(sql`
         SELECT 'embedding_search' AS projection, array_to_string(p.acl, ',') AS acl,
           array_to_string(d.acl, ',') AS expected
-        FROM embedding_search p JOIN document d ON d.id = p.document_id WHERE d.connector_id = ${connectorId}
-        UNION ALL
-        SELECT 'embedding_keyword_tin', array_to_string(p.acl, ','), array_to_string(d.acl, ',')
-        FROM embedding_keyword_tin p JOIN document d ON d.id = p.document_id WHERE d.connector_id = ${connectorId}`)
+        FROM embedding_search p JOIN document d ON d.id = p.document_id WHERE d.connector_id = ${connectorId}`)
 
     /** Projection rows each transaction rewrote, per table. */
     const projectionRowsPerTransaction = async () =>
@@ -354,7 +340,7 @@ describe('connector lease ACL pages in PostgreSQL', () => {
       const seeded = await seedDocuments(ids.connectorId, [alice()], 30)
       await seedChunks(seeded)
       const before = [...(await projectionAcls(ids.connectorId))]
-      expect(before).toHaveLength(2 * 30 * CHUNKS)
+      expect(before).toHaveLength(30 * CHUNKS)
 
       await expect(
         persistDocumentAcls(
@@ -367,7 +353,7 @@ describe('connector lease ACL pages in PostgreSQL', () => {
       const after = [...(await projectionAcls(ids.connectorId))]
       expect(after.filter((row) => row.acl !== bob() || row.expected !== bob())).toEqual([])
       const perTransaction = await projectionRowsPerTransaction()
-      expect(perTransaction.reduce((total, rows) => total + rows, 0)).toBe(2 * 30 * CHUNKS)
+      expect(perTransaction.reduce((total, rows) => total + rows, 0)).toBe(30 * CHUNKS)
       expect(Math.max(...perTransaction)).toBeLessThanOrEqual(PROJECTION_ROW_BATCH_SIZE)
     })
 
@@ -384,7 +370,7 @@ describe('connector lease ACL pages in PostgreSQL', () => {
       ).resolves.toBe(true)
 
       const after = [...(await projectionAcls(members.connectorId))]
-      expect(after).toHaveLength(2 * 30 * CHUNKS)
+      expect(after).toHaveLength(30 * CHUNKS)
       expect(after.filter((row) => row.acl !== '' || row.expected !== '')).toEqual([])
       expect(Math.max(...(await projectionRowsPerTransaction()))).toBeLessThanOrEqual(
         PROJECTION_ROW_BATCH_SIZE
 
@@ -8,7 +8,6 @@ import {
 import {
   document,
   embedding,
-  embeddingKeywordSearch,
   embeddingKeywordTin,
   embeddingSearch,
   knowledgeBase,
@@ -123,6 +122,25 @@ afterAll(async () => {
 })
 
 describe('ordinary KB vector repair after indexed Search retirement', () => {
+  it('keeps canonical chunk writes after the retired keyword projection is removed', async () => {
+    const [relations] =
+      await projector`SELECT to_regclass('public.embedding_keyword_search') AS keyword`
+    expect(relations.keyword).toBeNull()
+    const chunk = chunkRow(generateId(), 0)
+    await db.insert(embedding).values(chunk)
+    await db
+      .update(embedding)
+      .set({ content: 'updated searchable text' })
+      .where(eq(embedding.id, chunk.id))
+    const [canonical] =
+      await projector`SELECT content_tsv @@ plainto_tsquery('english', 'searchable') AS matches
+      FROM embedding WHERE id = ${chunk.id}`
+    expect(canonical.matches).toBe(true)
+    expect((await vectorsOf()).map((row) => row.id)).toEqual([chunk.id])
+    await db.delete(embedding).where(eq(embedding.id, chunk.id))
+    expect(await vectorsOf()).toEqual([])
+  })
+
   it('repairs deferred vectors in bounded pages without creating copied ACL or keyword rows', async () => {
     const chunks = Array.from({ length: 5 }, (_, index) => chunkRow(generateId(), index))
     await defer((tx) => tx.insert(embedding).values(chunks))
@@ -143,12 +161,6 @@ describe('ordinary KB vector repair after indexed Search retirement', () => {
         (row) => row.vector512?.[511] === 1 && row.acl === null && row.connectorId === null
       )
     ).toBe(true)
-    expect(
-      await db
-        .select()
-        .from(embeddingKeywordSearch)
-        .where(eq(embeddingKeywordSearch.documentId, documentId))
-    ).toEqual([])
     expect(
       await db
         .select()
@@ -167,12 +179,6 @@ describe('ordinary KB vector repair after indexed Search retirement', () => {
     expect(await markOf(searchDocumentId)).toMatchObject({ content: true })
     await runKnowledgeProjection(projector, {})
     expect(await vectorsOf(searchDocumentId)).toEqual([])
-    expect(
-      await db
-        .select()
-        .from(embeddingKeywordSearch)
-        .where(eq(embeddingKeywordSearch.documentId, searchDocumentId))
-    ).toEqual([])
     expect(
       await db
         .select()
 
@@ -685,7 +685,6 @@ describe.skipIf(!enabled)('Knowledge search latency on a realistic indexed corpu
     await db.execute(sql`ANALYZE document`)
     await db.execute(sql`ANALYZE embedding`)
     await db.execute(sql`ANALYZE embedding_search`)
-    await db.execute(sql`ANALYZE embedding_keyword_search`)
     if (evictSharedBuffers) await db.execute(sql`CREATE EXTENSION IF NOT EXISTS pg_buffercache`)
     report.server = (
       await db.execute(sql`SELECT version(), current_setting('work_mem') AS work_mem,
 
@@ -17,7 +17,6 @@ import {
   credentialGroupEnrollment,
   document,
   embedding,
-  embeddingKeywordSearch,
   embeddingSearch,
   knowledgeBase,
   knowledgeConnector,
@@ -135,9 +134,6 @@ describe.each([
       .update(embeddingSearch)
       .set({ acl: ['s:nobody:-:stale'], connectorId: null })
       .where(eq(embeddingSearch.knowledgeBaseId, baseId))
-    await db
-      .delete(embeddingKeywordSearch)
-      .where(eq(embeddingKeywordSearch.knowledgeBaseId, baseId))
   })
 
   afterAll(async () => {
 
@@ -1,10 +1,4 @@
-import {
-  document,
-  embeddingKeywordTin,
-  embeddingSearch,
-  knowledgeBase,
-  knowledgeConnector,
-} from '@sim/db/schema'
+import { document, embeddingSearch, knowledgeBase, knowledgeConnector } from '@sim/db/schema'
 import { dbChainMockFns, queueTableRows, resetDbChainMock } from '@sim/testing'
 import { billingStorageMock, billingStorageMockFns } from '@sim/testing/mocks/billing-storage.mock'
 import {
@@ -68,12 +62,10 @@ function queueBatch(documentIds: string[], reservedBytes = 0) {
 }
 
 /** Row ids the projection release returns, in the order the handler updates the tables. */
-function releaseProjectionRows(searchRows: number, keywordRows: number) {
+function releaseProjectionRows(searchRows: number) {
   const rows = (count: number) =>
     Array.from({ length: count }, (_, index) => ({ id: `c-${index}` }))
-  dbChainMockFns.returning
-    .mockResolvedValueOnce(rows(searchRows))
-    .mockResolvedValueOnce(rows(keywordRows))
+  dbChainMockFns.returning.mockResolvedValueOnce(rows(searchRows))
 }
 
 function updatedTables() {
@@ -92,7 +84,7 @@ describe('connector detachment', () => {
 
   it('releases documents against the reservation, then settles what remains with the connector', async () => {
     queueBatch(['doc-1', 'doc-2'], 25)
-    releaseProjectionRows(3, 3)
+    releaseProjectionRows(3)
     dbChainMockFns.returning.mockResolvedValueOnce([
       { fileSize: 10, deletedAt: null },
       { fileSize: 5, deletedAt: new Date('2026-09-01T00:00:00.000Z') },
@@ -108,12 +100,7 @@ describe('connector detachment', () => {
       context()
     )
 
-    expect(updatedTables()).toEqual([
-      embeddingSearch,
-      embeddingKeywordTin,
-      document,
-      knowledgeConnector,
-    ])
+    expect(updatedTables()).toEqual([embeddingSearch, document, knowledgeConnector])
     expect(dbChainMockFns.set).toHaveBeenCalledWith({ connectorId: null })
     expect(dbChainMockFns.set).toHaveBeenCalledWith(
       expect.objectContaining({ connectorId: null, deletedAt: expect.anything() })
@@ -131,7 +118,7 @@ describe('connector detachment', () => {
   it('keeps documents attached until their search rows fit one page, without spending retries', async () => {
     for (let batch = 0; batch < 4; batch++) {
       queueBatch(['doc-1'])
-      releaseProjectionRows(250, 0)
+      releaseProjectionRows(250)
     }
 
     expect(await detachKnowledgeConnector(payload, context())).toMatchObject({
 
@@ -1,12 +1,6 @@
 import { db } from '@sim/db'
 import { PROJECTION_ROW_BATCH_SIZE } from '@sim/db/knowledge-projection'
-import {
-  document,
-  embeddingKeywordTin,
-  embeddingSearch,
-  knowledgeBase,
-  knowledgeConnector,
-} from '@sim/db/schema'
+import { document, embeddingSearch, knowledgeBase, knowledgeConnector } from '@sim/db/schema'
 import { and, asc, eq, inArray, isNotNull, lt, ne, sql } from 'drizzle-orm'
 import { z } from 'zod'
 import {
@@ -78,8 +72,6 @@ export function keptDocumentBytes() {
   END`
 }
 
-const SEARCH_PROJECTIONS = [embeddingSearch, embeddingKeywordTin] as const
-
 /**
  * Settles what is left of a detached connector's reservation: an unreleased remainder is refunded,
  * and an overdraft, released bytes beyond what removal charged, is charged as already admitted.
@@ -196,8 +188,8 @@ export async function settleDetachedConnectorReservations(
  * Releases a detached connector's documents as standalone entries, then deletes the connector.
  *
  * Nulling a document's `connector_id` fires the projection trigger, which rewrites every enabled
- * chunk of it in both search projections, each a fresh index entry. So each transaction first
- * releases at most 250 projection rows per table of the next 100 documents, and flips those
+ * chunk of it in the vector projection, each a fresh index entry. So each transaction first
+ * releases at most 250 vector projection rows of the next 100 documents, and flips those
  * documents only once none of their rows still name the connector; the trigger then finds nothing
  * to rewrite. A document larger than one page spans several transactions, and its released rows
  * read as an upload in the meantime, which grants the same access: only workspace-access
@@ -299,27 +291,23 @@ export const detachKnowledgeConnector: OutboxHandler = async (rawPayload, contex
         return drained
       }
 
-      let projectionPageFull = false
-      for (const projection of SEARCH_PROJECTIONS) {
-        const page = tx
-          .select({ id: projection.id })
-          .from(projection)
-          .where(
-            and(
-              inArray(projection.documentId, documentIds),
-              eq(projection.enabled, true),
-              isNotNull(projection.connectorId)
-            )
+      const page = tx
+        .select({ id: embeddingSearch.id })
+        .from(embeddingSearch)
+        .where(
+          and(
+            inArray(embeddingSearch.documentId, documentIds),
+            eq(embeddingSearch.enabled, true),
+            isNotNull(embeddingSearch.connectorId)
           )
-          .limit(PROJECTION_ROW_BATCH_SIZE)
-        const released = await tx
-          .update(projection)
-          .set({ connectorId: null })
-          .where(inArray(projection.id, page))
-          .returning({ id: projection.id })
-        if (released.length === PROJECTION_ROW_BATCH_SIZE) projectionPageFull = true
-      }
-      if (projectionPageFull) return 'progress'
+        )
+        .limit(PROJECTION_ROW_BATCH_SIZE)
+      const released = await tx
+        .update(embeddingSearch)
+        .set({ connectorId: null })
+        .where(inArray(embeddingSearch.id, page))
+        .returning({ id: embeddingSearch.id })
+      if (released.length === PROJECTION_ROW_BATCH_SIZE) return 'progress'
 
       const releasedDocuments = await tx
         .update(document)
 
@@ -153,7 +153,7 @@ describe('completed listing reconciliation in PostgreSQL', () => {
       acl text[] NOT NULL DEFAULT '{ws}', acl_requirements jsonb NOT NULL DEFAULT '[]',
       acl_verified_at timestamp
     )`
-    for (const projection of ['embedding_search', 'embedding_keyword_tin']) {
+    for (const projection of ['embedding_search']) {
       await sql`CREATE TABLE ${sql(projection)} (
         id text PRIMARY KEY, document_id text NOT NULL, enabled boolean NOT NULL DEFAULT true,
         connector_id text, acl text[]
@@ -170,7 +170,6 @@ describe('completed listing reconciliation in PostgreSQL', () => {
     await sql`CREATE TRIGGER count_fan_out AFTER UPDATE OF connector_id, acl ON document
       FOR EACH ROW EXECUTE FUNCTION count_fan_out()`
     await sql`ALTER TABLE embedding_search DISABLE TRIGGER embedding_search_source_acl_set`
-    await sql`ALTER TABLE embedding_keyword_tin DISABLE TRIGGER embedding_keyword_tin_source_acl_set`
   }, 60_000)
 
   afterAll(async () => {
@@ -181,7 +180,7 @@ describe('completed listing reconciliation in PostgreSQL', () => {
 
   beforeEach(async () => {
     hardDelete.mockClear()
-    await sql`TRUNCATE embedding_search, embedding_keyword_tin, document, fan_out, knowledge_connector`
+    await sql`TRUNCATE embedding_search, document, fan_out, knowledge_connector`
     await sql`INSERT INTO knowledge_connector (id) VALUES (${CONNECTOR})`
   })
 
@@ -191,7 +190,7 @@ describe('completed listing reconciliation in PostgreSQL', () => {
       { id: 'absent-empty', acl: [], seenAt: ABSENT_SINCE },
       { id: 'absent-granted', acl: [ALICE], seenAt: ABSENT_SINCE, verified: true },
     ])
-    for (const projection of ['embedding_search', 'embedding_keyword_tin']) {
+    for (const projection of ['embedding_search']) {
       const prefix = projection === 'embedding_search' ? 'vec' : 'kw'
       await sql`INSERT INTO ${sql(projection)} (id, document_id, connector_id, acl) VALUES
         (${`${prefix}-empty-filled`}, 'absent-empty', ${CONNECTOR}, '{}'),
@@ -210,13 +209,7 @@ describe('completed listing reconciliation in PostgreSQL', () => {
       { id: 'absent-empty', acl: [], verified: false, deleted: true },
       { id: 'absent-granted', acl: [], verified: false, deleted: true },
     ])
-    expect(
-      await sql`SELECT id, acl FROM embedding_search
-        UNION ALL SELECT id, acl FROM embedding_keyword_tin ORDER BY id`
-    ).toEqual([
-      { id: 'kw-empty-filled', acl: [] },
-      { id: 'kw-granted-filled', acl: [] },
-      { id: 'kw-granted-unfilled', acl: null },
+    expect(await sql`SELECT id, acl FROM embedding_search ORDER BY id`).toEqual([
       { id: 'vec-empty-filled', acl: [] },
       { id: 'vec-granted-filled', acl: [] },
       { id: 'vec-granted-unfilled', acl: null },