diff --git a/src/simplnx/Filter/IFilter.cpp b/src/simplnx/Filter/IFilter.cpp
index 1c8e99ae42..c6daf561e2 100644
--- a/src/simplnx/Filter/IFilter.cpp
+++ b/src/simplnx/Filter/IFilter.cpp
@@ -2,15 +2,12 @@
 
 #include "simplnx/Filter/DataParameter.hpp"
 #include "simplnx/Filter/ValueParameter.hpp"
+#include "simplnx/Utilities/StringUtilities.hpp"
 
 #include <fmt/format.h>
 #include <nlohmann/json.hpp>
 
-#include <iostream>
-#include <limits> // For std::numeric_limits
 #include <sstream>
-#include <string>
-#include <utility> // For std::pair
 #include <vector>
 
 using namespace nx::core;
@@ -260,47 +257,6 @@ nlohmann::json IFilter::toJson(const Arguments& args) const
   return json;
 }
 
-// Assuming levenshteinDistance function is defined as before
-int levenshteinDistance(const std::string& s1, const std::string& s2)
-{
-  const size_t len1 = s1.size(), len2 = s2.size();
-  std::vector<std::vector<unsigned int>> d(len1 + 1, std::vector<unsigned int>(len2 + 1));
-
-  d[0][0] = 0;
-  for(unsigned int i = 1; i <= len1; ++i)
-    d[i][0] = i;
-  for(unsigned int i = 1; i <= len2; ++i)
-    d[0][i] = i;
-
-  for(unsigned int i = 1; i <= len1; ++i)
-    for(unsigned int j = 1; j <= len2; ++j)
-      d[i][j] = std::min({d[i - 1][j] + 1, d[i][j - 1] + 1, d[i - 1][j - 1] + (s1[i - 1] == s2[j - 1] ? 0 : 1)});
-
-  return d[len1][len2];
-}
-
-// Function to find best matching word pairs based on Levenshtein distance
-std::vector<std::pair<std::string, std::string>> findBestMatches(const std::vector<std::string>& vec1, const std::vector<std::string>& vec2)
-{
-  std::vector<std::pair<std::string, std::string>> bestPairs;
-  for(const auto& word1 : vec1)
-  {
-    int bestDistance = std::numeric_limits<int>::max();
-    std::string bestMatch;
-    for(const auto& word2 : vec2)
-    {
-      int currentDistance = levenshteinDistance(word1, word2);
-      if(currentDistance < bestDistance)
-      {
-        bestDistance = currentDistance;
-        bestMatch = word2;
-      }
-    }
-    bestPairs.emplace_back(word1, bestMatch);
-  }
-  return bestPairs;
-}
-
 Result<Arguments> IFilter::fromJson(const nlohmann::json& json) const
 {
   Parameters params = parameters();
@@ -340,7 +296,7 @@ Result<Arguments> IFilter::fromJson(const nlohmann::json& json) const
     }
   }
 
-  auto bestMatches = findBestMatches(jsonKeyNotFound, paramKeyNotFound);
+  auto bestMatches = StringUtilities::FindBestMatches(jsonKeyNotFound, paramKeyNotFound);
   for(const auto& match : bestMatches)
   {
     if(!match.first.empty() && !match.second.empty())
diff --git a/src/simplnx/Utilities/StringUtilities.hpp b/src/simplnx/Utilities/StringUtilities.hpp
index d8978ff84b..5a5cc5e8fd 100644
--- a/src/simplnx/Utilities/StringUtilities.hpp
+++ b/src/simplnx/Utilities/StringUtilities.hpp
@@ -32,12 +32,17 @@
 #pragma once
 
 #include "simplnx/Common/StringLiteral.hpp"
+#include "simplnx/Common/Types.hpp"
 
 #include <fmt/ranges.h>
 #include <nonstd/span.hpp>
 
+#include <algorithm>
 #include <cctype>
+#include <limits>
 #include <sstream>
+#include <string>
+#include <utility>
 #include <vector>
 
 /*' '(0x20)space(SPC)
@@ -439,4 +444,62 @@ inline std::string toLower(std::string input)
   return input;
 }
 
+/**
+ * @brief Calculates the Levenshtein distance between two strings.
+ * @param s1
+ * @param s2
+ * @return uint32
+ */
+inline uint32 CalculateLevenshteinDistance(const std::string& s1, const std::string& s2)
+{
+  usize len1 = s1.size();
+  usize len2 = s2.size();
+  std::vector<std::vector<uint32>> d(len1 + 1, std::vector<uint32>(len2 + 1));
+
+  d[0][0] = 0;
+  for(uint32 i = 1; i <= len1; ++i)
+  {
+    d[i][0] = i;
+  }
+  for(uint32 i = 1; i <= len2; ++i)
+  {
+    d[0][i] = i;
+  }
+
+  for(uint32 i = 1; i <= len1; ++i)
+  {
+    for(uint32 j = 1; j <= len2; ++j)
+    {
+      d[i][j] = std::min({d[i - 1][j] + 1, d[i][j - 1] + 1, d[i - 1][j - 1] + (s1[i - 1] == s2[j - 1] ? 0 : 1)});
+    }
+  }
+  return d[len1][len2];
+}
+
+/**
+ * @brief Finds the best matches between two lists of strings using the Levenshtein distance.
+ * @param vec1
+ * @param vec2
+ * @return std::vector<std::pair<std::string, std::string>>
+ */
+inline std::vector<std::pair<std::string, std::string>> FindBestMatches(const std::vector<std::string>& vec1, const std::vector<std::string>& vec2)
+{
+  std::vector<std::pair<std::string, std::string>> bestPairs;
+  for(const auto& word1 : vec1)
+  {
+    uint32 bestDistance = std::numeric_limits<uint32>::max();
+    std::string bestMatch;
+    for(const auto& word2 : vec2)
+    {
+      uint32 currentDistance = CalculateLevenshteinDistance(word1, word2);
+      if(currentDistance < bestDistance)
+      {
+        bestDistance = currentDistance;
+        bestMatch = word2;
+      }
+    }
+    bestPairs.emplace_back(word1, bestMatch);
+  }
+  return bestPairs;
+}
 } // namespace nx::core::StringUtilities