diff --git a/sql-plugin-api/src/main/java/com/nvidia/spark/RapidsSimpleGroupByAggregation.java b/sql-plugin-api/src/main/java/com/nvidia/spark/RapidsSimpleGroupByAggregation.java
new file mode 100644
index 00000000000..3b5aa06742a
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+++ b/sql-plugin-api/src/main/java/com/nvidia/spark/RapidsSimpleGroupByAggregation.java
@@ -0,0 +1,35 @@
+/*
+ * Copyright (c) 2025, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package com.nvidia.spark;
+
+import ai.rapids.cudf.GroupByAggregationOnColumn;
+
+/**
+ * Standard CUDF-based aggregation step that uses built-in CUDF aggregation
+ * operations. This handles the most common aggregation patterns and provides
+ * the best performance.
+ */
+public interface RapidsSimpleGroupByAggregation extends RapidsUDAFGroupByAggregation {
+ /**
+ * The main aggregation step that uses built-in CUDF GroupBy operations.
+ *
+ * @param inputIndices An array of ints, which are the indices of the input
+ * columns.
+ * @return An array of CUDF `GroupByAggregationOnColumn` instances.
+ */
+ GroupByAggregationOnColumn[] aggregate(int[] inputIndices);
+}
diff --git a/sql-plugin-api/src/main/java/com/nvidia/spark/RapidsUDAF.java b/sql-plugin-api/src/main/java/com/nvidia/spark/RapidsUDAF.java
new file mode 100644
index 00000000000..b8fa8e79a3a
--- /dev/null
+++ b/sql-plugin-api/src/main/java/com/nvidia/spark/RapidsUDAF.java
@@ -0,0 +1,84 @@
+/*
+ * Copyright (c) 2025, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package com.nvidia.spark;
+
+import ai.rapids.cudf.ColumnVector;
+import ai.rapids.cudf.Scalar;
+import org.apache.spark.sql.types.DataType;
+
+/**
+ * An interface for a GPU-accelerated User Defined Aggregate Function (UDAF).
+ * This provides the necessary methods to perform distributed group-by and
+ * reduction aggregations using CUDF.
+ */
+public interface RapidsUDAF {
+ /**
+ * Provides an array of default values for the aggregation result. This is
+ * used when a reduction aggregation does not have any rows to aggregate.
+ *
+ * The returned Scalars will be closed automatically.
+ *
+ * @return An array of cudf Scalar representing the output of the
+ * updateAggregation stage of processing. The output of this
+ * may still be merged with other tasks.
+ */
+ Scalar[] getDefaultValue();
+
+ /**
+ * This method returns a RapidsUDAFGroupByAggregation that defines the
+ * logic for the initial aggregation.
+ *
+ * @return A RapidsUDAFGroupByAggregation that defines the aggregation logic.
+ */
+ RapidsUDAFGroupByAggregation updateAggregation();
+
+ /**
+ * This method returns a RapidsUDAFGroupByAggregation that defines how to
+ * merge two sets of aggregation results. This is used in distributed
+ * aggregation scenarios where intermediate results from different
+ * partitions are combined.
+ *
+ * @return A RapidsUDAFGroupByAggregation that defines the merge logic.
+ */
+ RapidsUDAFGroupByAggregation mergeAggregation();
+
+ /**
+ * A last step that takes the result of the merged aggregation
+ * and performs any necessary transformations before returning the final
+ * result. This method returns a single ColumnVector, which is the final
+ * result of the aggregation.
+ *
+ * Users should close the input columns to avoid GPU memory leak. But the
+ * returned column will be closed automatically.
+ *
+ * @param numRows The number of rows in the aggregated data.
+ * @param args An array of ColumnVector arguments from the final aggregation step.
+ * @param outType The final data type of this UDAF
+ * @return A single ColumnVector representing the final UDAF result.
+ */
+ ColumnVector getResult(int numRows, ColumnVector[] args, DataType outType);
+
+ /**
+ * Data types of the aggregate buffer.
+ *
+ * It is better to align with the "bufferSchema" of "UserDefinedAggregateFunction", or
+ * data corruption is likely to happen when some operations of this aggregation fall
+ * back to CPU. E.g. Partial aggregates runs on CPU but final aggregates runs on GPU,
+ * or vice-versa. This is rare but just in case.
+ */
+ DataType[] bufferTypes();
+}
diff --git a/sql-plugin-api/src/main/java/com/nvidia/spark/RapidsUDAFGroupByAggregation.java b/sql-plugin-api/src/main/java/com/nvidia/spark/RapidsUDAFGroupByAggregation.java
new file mode 100644
index 00000000000..6c162085988
--- /dev/null
+++ b/sql-plugin-api/src/main/java/com/nvidia/spark/RapidsUDAFGroupByAggregation.java
@@ -0,0 +1,74 @@
+/*
+ * Copyright (c) 2025, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package com.nvidia.spark;
+
+import ai.rapids.cudf.ColumnVector;
+import ai.rapids.cudf.Scalar;
+
+/**
+ * Base interface for GPU-accelerated UDAF aggregation implementations. This provides
+ * the contract for different aggregation strategies.
+ *
+ * Please do not try and extend from this interface directly.
+ * `RapidsSimpleGroupByAggregation` is currently supported as interfaces to directly
+ * implement. More may be added in the future.
+ */
+public interface RapidsUDAFGroupByAggregation {
+ /**
+ * An optional pre-step for the aggregation. By default, this is a no-op
+ * and will just return the arguments passed in.
+ *
+ * Users should close the input columns to avoid GPU memory leak, but the
+ * returned columns will be closed automatically.
+ *
+ * @param numRows The number of rows.
+ * @param args An array of input ColumnVectors.
+ * @return An array of ColumnVectors.
+ */
+ default ColumnVector[] preStep(int numRows, ColumnVector[] args) {
+ return args;
+ }
+
+ /**
+ * Performs a reduction on the pre-step output (no keys). The
+ * output of this will be turned into a ColumnVector and possibly
+ * combined with other rows before being processed more.
+ *
+ * Both the input columns and returned Scalars will be closed automatically.
+ *
+ * @param numRows The number of rows to process.
+ * @param preStepData The output from the preStep method.
+ * @return An array of cudf Scalars representing the reduced data.
+ */
+ Scalar[] reduce(int numRows, ColumnVector[] preStepData);
+
+ /**
+ * A post-process step for the aggregation. It takes the output of the
+ * aggregations and performs any processing needed to make it match the
+ * input to the merge aggregation.
+ *
+ * Users should close the input columns to avoid GPU memory leak, but the
+ * returned columns will be closed automatically.
+ *
+ * @param numRows The number of rows in the aggregated data.
+ * @param aggregatedData The output from the aggregation step.
+ * @return An array of ColumnVectors compatible with the merge step.
+ */
+ default ColumnVector[] postStep(int numRows, ColumnVector[] aggregatedData) {
+ return aggregatedData;
+ }
+}