diff --git a/online/src/main/scala/ai/chronon/online/TileCodec.scala b/online/src/main/scala/ai/chronon/online/TileCodec.scala
new file mode 100644
index 000000000..aa70bc687
--- /dev/null
+++ b/online/src/main/scala/ai/chronon/online/TileCodec.scala
@@ -0,0 +1,57 @@
+package ai.chronon.online
+
+import ai.chronon.aggregator.row.RowAggregator
+import ai.chronon.api.{BooleanType, DataType, GroupBy, StructType}
+import org.apache.avro.generic.GenericData
+import ai.chronon.api.Extensions.{AggregationOps, MetadataOps}
+
+import scala.collection.JavaConverters._
+
+object TileCodec {
+  def buildRowAggregator(groupBy: GroupBy, inputSchema: Seq[(String, DataType)]): RowAggregator = {
+    // a set of Chronon groupBy aggregations needs to be flatted out to get the
+    // full cross-product of all the feature column aggregations to be computed
+    val unpackedAggs = groupBy.aggregations.asScala.flatMap(_.unpack)
+    new RowAggregator(inputSchema, unpackedAggs)
+  }
+}
+
+/**
+  * TileCodec is a helper class that allows for the creation of pre-aggregated tiles of feature values.
+  * These pre-aggregated tiles can be used in the serving layer to compute the final feature values along
+  * with batch pre-aggregates produced by GroupByUploads.
+  * The pre-aggregated tiles are serialized as Avro and indicate whether the tile is complete or not (partial aggregates)
+  */
+class TileCodec(rowAggregator: RowAggregator, groupBy: GroupBy) {
+  val windowedIrSchema: StructType = StructType.from("WindowedIr", rowAggregator.irSchema)
+  val fields: Array[(String, DataType)] = Array(
+    "collapsedIr" -> windowedIrSchema,
+    "isComplete" -> BooleanType
+  )
+
+  val tileChrononSchema: StructType =
+    StructType.from(s"${groupBy.metaData.cleanName}_TILE_IR", fields)
+  val tileAvroSchema: String = AvroConversions.fromChrononSchema(tileChrononSchema).toString()
+  val tileAvroCodec: AvroCodec = AvroCodec.of(tileAvroSchema)
+  private val irToBytesFn = AvroConversions.encodeBytes(tileChrononSchema, null)
+
+  def makeTileIr(ir: Array[Any], isComplete: Boolean): Array[Byte] = {
+    val normalizedIR = rowAggregator.normalize(ir)
+    val tileIr: Array[Any] = Array(normalizedIR, Boolean.box(isComplete))
+    irToBytesFn(tileIr)
+  }
+
+  def decodeTileIr(tileIr: Array[Byte]): (Array[Any], Boolean) = {
+    val decodedTileIr = tileAvroCodec.decode(tileIr)
+    val collapsedIr = decodedTileIr
+      .get("collapsedIr")
+      .asInstanceOf[GenericData.Record]
+
+    val ir = AvroConversions
+      .toChrononRow(collapsedIr, windowedIrSchema)
+      .asInstanceOf[Array[Any]]
+    val denormalizedIr = rowAggregator.denormalize(ir)
+    val isComplete = decodedTileIr.get("isComplete").asInstanceOf[Boolean]
+    (denormalizedIr, isComplete)
+  }
+}
diff --git a/online/src/test/scala/ai/chronon/online/TileCodecTest.scala b/online/src/test/scala/ai/chronon/online/TileCodecTest.scala
new file mode 100644
index 000000000..c666211fd
--- /dev/null
+++ b/online/src/test/scala/ai/chronon/online/TileCodecTest.scala
@@ -0,0 +1,89 @@
+package ai.chronon.online
+
+import ai.chronon.api.{Aggregation, Builders, FloatType, IntType, ListType, LongType, Operation, Row, StringType, TimeUnit, Window}
+import org.junit.Assert.assertEquals
+import org.junit.Test
+import scala.collection.JavaConverters._
+
+class TileCodecTest {
+  private val histogram = Map[String, Int]("A" -> 3, "B" -> 2).asJava
+
+  private val aggregationsAndExpected: Array[(Aggregation, Any)] = Array(
+    Builders.Aggregation(Operation.AVERAGE, "views", Seq(new Window(1, TimeUnit.DAYS))) -> 16.0,
+    Builders.Aggregation(Operation.AVERAGE, "rating", Seq(new Window(1, TimeUnit.DAYS))) -> 4.0,
+
+    Builders.Aggregation(Operation.SUM, "rating", Seq(new Window(1, TimeUnit.DAYS))) -> 12.0f,
+    Builders.Aggregation(Operation.SUM, "rating", Seq(new Window(7, TimeUnit.DAYS))) -> 12.0f,
+
+    Builders.Aggregation(Operation.UNIQUE_COUNT, "title", Seq(new Window(1, TimeUnit.DAYS))) -> 3L,
+    Builders.Aggregation(Operation.UNIQUE_COUNT, "title", Seq(new Window(7, TimeUnit.DAYS))) -> 3L,
+
+    Builders.Aggregation(Operation.LAST, "title", Seq(new Window(1, TimeUnit.DAYS))) -> "C",
+    Builders.Aggregation(Operation.LAST, "title", Seq(new Window(7, TimeUnit.DAYS))) -> "C",
+
+    Builders.Aggregation(Operation.LAST_K, "title", Seq(new Window(1, TimeUnit.DAYS)), argMap = Map("k" -> "2")) -> List("C", "B").asJava,
+    Builders.Aggregation(Operation.LAST_K, "title", Seq(new Window(7, TimeUnit.DAYS)), argMap = Map("k" -> "2")) -> List("C", "B").asJava,
+
+    Builders.Aggregation(Operation.TOP_K, "title", Seq(new Window(1, TimeUnit.DAYS)), argMap = Map("k" -> "1")) -> List("C").asJava,
+    Builders.Aggregation(Operation.TOP_K, "title", Seq(new Window(7, TimeUnit.DAYS)), argMap = Map("k" -> "1")) -> List("C").asJava,
+
+    Builders.Aggregation(Operation.MIN, "title", Seq(new Window(1, TimeUnit.DAYS))) -> "A",
+    Builders.Aggregation(Operation.MIN, "title", Seq(new Window(7, TimeUnit.DAYS))) -> "A",
+
+    Builders.Aggregation(Operation.APPROX_UNIQUE_COUNT, "title", Seq(new Window(1, TimeUnit.DAYS))) -> 3L,
+    Builders.Aggregation(Operation.APPROX_UNIQUE_COUNT, "title", Seq(new Window(7, TimeUnit.DAYS))) -> 3L,
+
+    Builders.Aggregation(Operation.HISTOGRAM, "hist_input", Seq(new Window(1, TimeUnit.DAYS)), argMap = Map("k" -> "2")) -> histogram,
+    Builders.Aggregation(Operation.HISTOGRAM, "hist_input", Seq(new Window(7, TimeUnit.DAYS)), argMap = Map("k" -> "2")) -> histogram
+  )
+
+  private val schema = List(
+    "created" -> LongType,
+    "views" -> IntType,
+    "rating" -> FloatType,
+    "title" -> StringType,
+    "hist_input" -> ListType(StringType)
+  )
+
+  @Test
+  def testTileCodecIrSerRoundTrip(): Unit = {
+    val groupByMetadata = Builders.MetaData(name = "my_group_by")
+    val (aggregations, expectedVals) = aggregationsAndExpected.unzip
+    val groupBy = Builders.GroupBy(metaData = groupByMetadata, aggregations = aggregations)
+    val rowAggregator = TileCodec.buildRowAggregator(groupBy, schema)
+    val rowIR = rowAggregator.init
+    val tileCodec = new TileCodec(rowAggregator, groupBy)
+
+    val originalIsComplete = true
+    val rows = Seq(
+      createRow(1519862399984L, 4, 4.0f, "A", Seq("D", "A", "B", "A")),
+      createRow(1519862399984L, 40, 5.0f, "B", Seq()),
+      createRow(1519862399988L, 4, 3.0f, "C", Seq("A", "B", "C"))
+    )
+    rows.foreach(row => rowAggregator.update(rowIR, row))
+    val bytes = tileCodec.makeTileIr(rowIR, originalIsComplete)
+    assert(bytes.length > 0)
+
+    val (deserPayload, isComplete) = tileCodec.decodeTileIr(bytes)
+    assert(isComplete == originalIsComplete)
+
+    // lets finalize the payload intermediate results and verify things
+    val finalResults = rowAggregator.finalize(deserPayload)
+    expectedVals.zip(finalResults).zip(rowAggregator.outputSchema.map(_._1)).foreach {
+      case ((expected, actual), name) =>
+        println(s"Checking: $name")
+        assertEquals(expected, actual)
+    }
+  }
+
+  def createRow(ts: Long, views: Int, rating: Float, title: String, histInput: Seq[String]): Row = {
+    val values: Array[(String, Any)] = Array(
+      "created" -> ts,
+      "views" -> views,
+      "rating" -> rating,
+      "title" -> title,
+      "hist_input" -> histInput
+    )
+    new ArrayRow(values.map(_._2), ts)
+  }
+}