diff --git a/Cargo.lock b/Cargo.lock
index 20d6ad95d..a921caa50 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -731,6 +731,7 @@ dependencies = [
  "byteorder",
  "clap",
  "diskann",
+ "diskann-benchmark-core",
  "diskann-label-filter",
  "diskann-providers",
  "diskann-quantization",
diff --git a/diskann-benchmark-core/src/streaming/executors/bigann/runbook.rs b/diskann-benchmark-core/src/streaming/executors/bigann/runbook.rs
index fbaee73df..072b3b1f6 100644
--- a/diskann-benchmark-core/src/streaming/executors/bigann/runbook.rs
+++ b/diskann-benchmark-core/src/streaming/executors/bigann/runbook.rs
@@ -176,8 +176,7 @@ impl RunBook {
     }
 
     /// Returns a reference to the stages in this runbook.
-    #[cfg(test)]
-    pub(super) fn stages(&self) -> &[Stage] {
+    pub fn stages(&self) -> &[Stage] {
         &self.stages
     }
 
diff --git a/diskann-tools/Cargo.toml b/diskann-tools/Cargo.toml
index 644ee1173..92bcbc949 100644
--- a/diskann-tools/Cargo.toml
+++ b/diskann-tools/Cargo.toml
@@ -15,6 +15,7 @@ clap = { workspace = true, features = ["derive"] }
 diskann-providers = { workspace = true, default-features = false } # see `linalg/Cargo.toml`
 diskann-vector = { workspace = true }
 diskann-utils = { workspace = true }
+diskann-benchmark-core = { workspace = true, features = ["bigann"] }
 bytemuck.workspace = true
 num_cpus.workspace = true
 rayon.workspace = true
diff --git a/diskann-tools/src/bin/compute_streaming_groundtruth.rs b/diskann-tools/src/bin/compute_streaming_groundtruth.rs
new file mode 100644
index 000000000..3cf8661ba
--- /dev/null
+++ b/diskann-tools/src/bin/compute_streaming_groundtruth.rs
@@ -0,0 +1,342 @@
+/*
+ * Copyright (c) Microsoft Corporation.
+ * Licensed under the MIT license.
+ */
+
+//! Computes KNN ground truth for every search stage in a BigANN-style runbook.
+//!
+//! The tool simulates the insert / replace / delete operations in the runbook,
+//! tracking the set of active base-vector IDs at each search stage.  For each
+//! search stage it computes the exact top-k nearest neighbours for each query
+//! against the currently active set, and writes the result to
+//! `<output-dir>/step<stage>.gt<recall_at>` -- the naming convention expected by
+//! [`diskann_benchmark_core::streaming::executors::bigann::ScanDirectory`].
+
+use std::{
+    collections::HashMap,
+    path::{Path, PathBuf},
+    time::Instant,
+};
+
+use anyhow::Context;
+use clap::Parser;
+use diskann::neighbor::{Neighbor, NeighborPriorityQueue};
+use diskann::utils::VectorRepr;
+use diskann_benchmark_core::streaming::executors::bigann::{FindGroundtruth, RunBook};
+use diskann_benchmark_core::streaming::{self, Executor};
+use diskann_providers::storage::{FileStorageProvider, StorageReadProvider};
+use diskann_tools::utils::{
+    init_subscriber, write_ground_truth, CMDResult, CMDToolError, DataType,
+};
+use diskann_utils::io::read_bin;
+use diskann_utils::views::Matrix;
+use diskann_vector::{distance::Metric, DistanceFunction};
+use rayon::prelude::*;
+
+fn main() -> CMDResult<()> {
+    init_subscriber();
+    let args = Args::parse();
+    match args.data_type {
+        DataType::Float => run::<f32>(&args),
+        DataType::Fp16 => run::<diskann_vector::Half>(&args),
+        DataType::Uint8 => run::<u8>(&args),
+        DataType::Int8 => run::<i8>(&args),
+    }
+}
+
+fn run<V: VectorRepr + Send + Sync>(args: &Args) -> CMDResult<()> {
+    let storage = FileStorageProvider;
+
+    tracing::info!("Loading dataset from {}", args.base_file);
+    let dataset =
+        read_bin::<V>(&mut storage.open_reader(&args.base_file)?).map_err(|e| CMDToolError {
+            details: e.to_string(),
+        })?;
+
+    tracing::info!("Loading queries from {}", args.query_file);
+    let queries =
+        read_bin::<V>(&mut storage.open_reader(&args.query_file)?).map_err(|e| CMDToolError {
+            details: e.to_string(),
+        })?;
+
+    let n_base = dataset.nrows();
+    let n_queries = queries.nrows();
+    let recall_at = args.recall_at as usize;
+
+    tracing::info!(
+        "Dataset: {} vectors, Queries: {} vectors, dim: {}, recall@{}",
+        n_base,
+        n_queries,
+        dataset.ncols(),
+        recall_at,
+    );
+
+    let output_dir = Path::new(&args.output_dir);
+    std::fs::create_dir_all(output_dir)
+        .with_context(|| format!("creating output directory {}", output_dir.display()))
+        .map_err(|e| CMDToolError {
+            details: e.to_string(),
+        })?;
+
+    let gt_suffix = format!("gt{}", recall_at);
+
+    // FindGroundtruth impl that always returns the expected output path whether
+    // or not it exists yet -- we are about to generate the files.
+    struct AllowMissing {
+        dir: PathBuf,
+        suffix: String,
+    }
+    impl FindGroundtruth for AllowMissing {
+        fn find_groundtruth(&mut self, stage: usize) -> anyhow::Result<PathBuf> {
+            Ok(self.dir.join(format!("step{}.{}", stage, self.suffix)))
+        }
+    }
+
+    let mut finder = AllowMissing {
+        dir: output_dir.to_path_buf(),
+        suffix: gt_suffix,
+    };
+
+    tracing::info!(
+        "Parsing runbook {} for dataset \"{}\"",
+        args.runbook_file,
+        args.dataset_name
+    );
+    let mut runbook = RunBook::load(
+        Path::new(&args.runbook_file),
+        &args.dataset_name,
+        &mut finder,
+    )
+    .map_err(|e| CMDToolError {
+        details: e.to_string(),
+    })?;
+
+    tracing::info!("Runbook has {} stages", runbook.len());
+    let distance_fn = V::distance(args.distance_function, Some(dataset.ncols()));
+
+    let mut stream = GroundtruthStream {
+        storage: &storage,
+        dataset: &dataset,
+        queries: &queries,
+        distance_fn,
+        n_base,
+        n_queries,
+        recall_at,
+        active: vec![false; n_base],
+        ext_id: vec![0u32; n_base],
+        ext_to_offset: HashMap::new(),
+    };
+
+    runbook
+        .run_with(&mut stream, |_| Ok(()))
+        .map_err(|e| CMDToolError {
+            details: e.to_string(),
+        })?;
+
+    tracing::info!("Done.");
+    Ok(())
+}
+
+struct GroundtruthStream<'a, V: VectorRepr + Send + Sync> {
+    storage: &'a FileStorageProvider,
+    dataset: &'a Matrix<V>,
+    queries: &'a Matrix<V>,
+    distance_fn: V::Distance,
+    n_base: usize,
+    n_queries: usize,
+    recall_at: usize,
+    active: Vec<bool>,
+    ext_id: Vec<u32>,
+    ext_to_offset: HashMap<u32, usize>,
+}
+
+impl<'a, V> streaming::Stream<diskann_benchmark_core::streaming::executors::bigann::Args>
+    for GroundtruthStream<'a, V>
+where
+    V: VectorRepr + Send + Sync,
+{
+    type Output = ();
+
+    fn search(
+        &mut self,
+        args: diskann_benchmark_core::streaming::executors::bigann::Search<'_>,
+    ) -> anyhow::Result<Self::Output> {
+        let timer = Instant::now();
+        let n_active = self.active.iter().filter(|&&b| b).count();
+
+        tracing::info!(
+            "Computing top-{} groundtruth for {} active vectors against {} queries",
+            self.recall_at,
+            n_active,
+            self.n_queries,
+        );
+
+        let active_ids: Vec<usize> = self
+            .active
+            .iter()
+            .enumerate()
+            .filter_map(|(i, &on)| if on { Some(i) } else { None })
+            .collect();
+
+        // it's generally find to use the global threadpool in diskann-tools
+        #[allow(clippy::disallowed_methods)]
+        let results: Vec<NeighborPriorityQueue<u32>> = (0..self.n_queries)
+            .into_par_iter()
+            .map(|qi| {
+                let query = self.queries.row(qi);
+                let mut pq = NeighborPriorityQueue::new(self.recall_at);
+                for &offset in &active_ids {
+                    let dist = self
+                        .distance_fn
+                        .evaluate_similarity(self.dataset.row(offset), query);
+                    pq.insert(Neighbor {
+                        id: self.ext_id[offset],
+                        distance: dist,
+                    });
+                }
+                pq
+            })
+            .collect();
+
+        let under_k: Vec<usize> = results
+            .iter()
+            .enumerate()
+            .filter_map(|(qi, pq)| (pq.size() < self.recall_at).then_some(qi))
+            .collect();
+        if !under_k.is_empty() {
+            let preview: Vec<usize> = under_k.iter().copied().take(20).collect();
+            let suffix = if under_k.len() > preview.len() {
+                format!(" (showing first {} query indices)", preview.len())
+            } else {
+                String::new()
+            };
+            return Err(anyhow::anyhow!(
+                "{}: {} / {} queries have fewer than {} results (active set = {}). Query indices: {:?}{}",
+                args.groundtruth.display(),
+                under_k.len(),
+                self.n_queries,
+                self.recall_at,
+                n_active,
+                preview,
+                suffix,
+            ));
+        }
+
+        write_ground_truth::<()>(
+            self.storage,
+            args.groundtruth.to_str().ok_or_else(|| {
+                anyhow::anyhow!("Non-UTF8 groundtruth path: {}", args.groundtruth.display())
+            })?,
+            self.n_queries,
+            self.recall_at,
+            results,
+            None,
+        )
+        .map_err(|e| anyhow::anyhow!(e.to_string()))?;
+
+        tracing::info!(
+            "Groundtruth written to {} in {:?}",
+            args.groundtruth.display(),
+            timer.elapsed(),
+        );
+
+        Ok(())
+    }
+
+    fn insert(
+        &mut self,
+        args: diskann_benchmark_core::streaming::executors::bigann::Insert,
+    ) -> anyhow::Result<Self::Output> {
+        for id in args.offsets.clone() {
+            if id < self.n_base {
+                self.active[id] = true;
+                self.ext_id[id] = id as u32;
+                self.ext_to_offset.insert(id as u32, id);
+            }
+        }
+        Ok(())
+    }
+
+    fn replace(
+        &mut self,
+        args: diskann_benchmark_core::streaming::executors::bigann::Replace,
+    ) -> anyhow::Result<Self::Output> {
+        for eid in args.ids.clone() {
+            if let Some(&offset) = self.ext_to_offset.get(&(eid as u32)) {
+                self.active[offset] = false;
+                self.ext_to_offset.remove(&(eid as u32));
+            }
+        }
+
+        for (offset, eid) in args.offsets.clone().zip(args.ids.clone()) {
+            if offset < self.n_base {
+                self.active[offset] = true;
+                self.ext_id[offset] = eid as u32;
+                self.ext_to_offset.insert(eid as u32, offset);
+            }
+        }
+
+        Ok(())
+    }
+
+    fn delete(
+        &mut self,
+        args: diskann_benchmark_core::streaming::executors::bigann::Delete,
+    ) -> anyhow::Result<Self::Output> {
+        for eid in args.ids.clone() {
+            if let Some(&offset) = self.ext_to_offset.get(&(eid as u32)) {
+                self.active[offset] = false;
+                self.ext_to_offset.remove(&(eid as u32));
+            }
+        }
+        Ok(())
+    }
+
+    fn maintain(&mut self, _args: ()) -> anyhow::Result<Self::Output> {
+        Ok(())
+    }
+
+    fn needs_maintenance(&mut self) -> bool {
+        false
+    }
+}
+
+#[derive(Debug, Parser)]
+struct Args {
+    /// Data type of the base and query vectors.
+    #[arg(long = "data-type", default_value = "float")]
+    pub data_type: DataType,
+
+    /// Distance function to use.
+    #[arg(long = "dist-fn", default_value = "l2")]
+    pub distance_function: Metric,
+
+    /// File containing the full base dataset in binary format.
+    #[arg(long = "base-file", short, required = true)]
+    pub base_file: String,
+
+    /// File containing the query vectors in binary format.
+    #[arg(long = "query-file", short, required = true)]
+    pub query_file: String,
+
+    /// Path to the BigANN runbook YAML file.
+    #[arg(long = "runbook-file", required = true)]
+    pub runbook_file: String,
+
+    /// Dataset name within the runbook YAML file.
+    #[arg(long = "dataset-name", required = true)]
+    pub dataset_name: String,
+
+    /// Number of nearest neighbours to compute per query (k).
+    ///
+    /// Output files are named step<stage>.gt<recall_at>.
+    #[arg(long = "recall-at", short = 'K', required = true)]
+    pub recall_at: u32,
+
+    /// Directory to write the groundtruth files into.
+    ///
+    /// Files are written as `step<stage>.gt<recall_at>`, matching the
+    /// naming convention expected by `ScanDirectory`.
+    #[arg(long = "gt-dir", short, required = true)]
+    pub output_dir: String,
+}
diff --git a/diskann-tools/src/utils/ground_truth.rs b/diskann-tools/src/utils/ground_truth.rs
index 77c2f663c..f42535ca8 100644
--- a/diskann-tools/src/utils/ground_truth.rs
+++ b/diskann-tools/src/utils/ground_truth.rs
@@ -520,7 +520,7 @@ fn write_range_search_ground_truth<StorageProvider: StorageReadProvider + Storag
 /// Writes out a ground truth file.  ground_truth is a vector of NeighborPriorityQueue objects
 /// where the order of queue objects corresponds to the order of queries used to compute this
 /// ground truth.
-fn write_ground_truth<A: Serialize + Copy>(
+pub fn write_ground_truth<A: Serialize + Copy>(
     storage_provider: &impl StorageWriteProvider,
     ground_truth_file: &str,
     number_of_queries: usize,