diff --git a/example/multipanel/example_multipanel_plot.ipynb b/example/multipanel/example_multipanel_plot.ipynb
new file mode 100644
index 00000000..fc0802be
--- /dev/null
+++ b/example/multipanel/example_multipanel_plot.ipynb
@@ -0,0 +1,320 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: <object object at 0x105a7f5a0>\n"
+     ]
+    }
+   ],
+   "source": [
+    "%matplotlib auto"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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",
+      "text/plain": [
+       "<Figure size 1000x1200 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\"\"\"\n",
+    "Example of creating a multipanel plot with matplotlib.\n",
+    "\n",
+    "This script demonstrates how to create a figure with multiple panels\n",
+    "containing different types of plots: line plot, bar plot, and scatter plot.\n",
+    "\"\"\"\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "import maidr\n",
+    "\n",
+    "maidr.set_engine(\"ts\")\n",
+    "\n",
+    "x_line = np.array([1, 2, 3, 4, 5, 6, 7, 8])\n",
+    "y_line = np.array([2, 4, 1, 5, 3, 7, 6, 8])\n",
+    "\n",
+    "# Data for bar plot\n",
+    "categories = [\"A\", \"B\", \"C\", \"D\", \"E\"]\n",
+    "values = np.random.rand(5) * 10\n",
+    "\n",
+    "# Data for bar plot\n",
+    "categories_2 = [\"A\", \"B\", \"C\", \"D\", \"E\"]\n",
+    "values_2 = np.random.randn(5) * 100\n",
+    "\n",
+    "# Data for scatter plot\n",
+    "x_scatter = np.random.randn(50)\n",
+    "y_scatter = np.random.randn(50)\n",
+    "\n",
+    "# Create a figure with 3 subplots arranged vertically\n",
+    "fig, axs = plt.subplots(3, 1, figsize=(10, 12))\n",
+    "\n",
+    "# First panel: Line plot\n",
+    "axs[0].plot(x_line, y_line, color=\"blue\", linewidth=2)\n",
+    "axs[0].set_title(\"Line Plot: Random Data\")\n",
+    "axs[0].set_xlabel(\"X-axis\")\n",
+    "axs[0].set_ylabel(\"Values\")\n",
+    "axs[0].grid(True, linestyle=\"--\", alpha=0.7)\n",
+    "\n",
+    "# Second panel: Bar plot\n",
+    "axs[1].bar(categories, values, color=\"green\", alpha=0.7)\n",
+    "axs[1].set_title(\"Bar Plot: Random Values\")\n",
+    "axs[1].set_xlabel(\"Categories\")\n",
+    "axs[1].set_ylabel(\"Values\")\n",
+    "\n",
+    "# Third panel: Bar plot\n",
+    "axs[2].bar(categories_2, values_2, color=\"blue\", alpha=0.7)\n",
+    "axs[2].set_title(\"Bar Plo 2t: Random Values\")\n",
+    "axs[2].set_xlabel(\"Categories\")\n",
+    "axs[2].set_ylabel(\"Values\")\n",
+    "\n",
+    "# Adjust layout to prevent overlap\n",
+    "plt.tight_layout()\n",
+    "\n",
+    "# Display the figure\n",
+    "maidr.show(fig)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "\n",
+    "import maidr\n",
+    "\n",
+    "\"\"\"\n",
+    "Creates a multiline plot using seaborn showing basic data trends.\n",
+    "\n",
+    "The plot displays three different data series with discrete points\n",
+    "connected by lines of different styles and colors using seaborn's\n",
+    "lineplot function.\n",
+    "\n",
+    "\"\"\"\n",
+    "# Set maidr engine\n",
+    "maidr.set_engine(\"ts\")\n",
+    "\n",
+    "# Create sample data points\n",
+    "x = np.array([1, 2, 3, 4, 5, 6, 7, 8])\n",
+    "y1 = np.array([2, 4, 1, 5, 3, 7, 6, 8])\n",
+    "y2 = np.array([1, 3, 5, 2, 4, 6, 8, 7])\n",
+    "y3 = np.array([3, 1, 4, 6, 5, 2, 4, 5])\n",
+    "\n",
+    "# Convert to pandas DataFrame for seaborn\n",
+    "data = pd.DataFrame(\n",
+    "    {\n",
+    "        \"x\": np.tile(x, 3),\n",
+    "        \"y\": np.concatenate([y1, y2, y3]),\n",
+    "        \"series\": np.repeat([\"Series 1\", \"Series 2\", \"Series 3\"], len(x)),\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "# Create the plot\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "\n",
+    "# Use seaborn lineplot for multiple lines\n",
+    "lineplot = sns.lineplot(\n",
+    "    x=\"x\", y=\"y\", hue=\"series\", style=\"series\", markers=True, dashes=True, data=data\n",
+    ")\n",
+    "\n",
+    "# Customize the plot\n",
+    "plt.title(\"Seaborn Multiline Plot\")\n",
+    "plt.xlabel(\"X values\")\n",
+    "plt.ylabel(\"Y values\")\n",
+    "\n",
+    "# Display the plot using maidr\n",
+    "maidr.show(lineplot)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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",
+      "text/plain": [
+       "<Figure size 1000x1200 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#!/usr/bin/env python3\n",
+    "\"\"\"\n",
+    "Example of creating a multipanel plot with seaborn.\n",
+    "\n",
+    "This script demonstrates how to create a figure with multiple panels\n",
+    "containing different types of plots using seaborn: line plot, bar plot, and bar plot.\n",
+    "\"\"\"\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "\n",
+    "import maidr\n",
+    "\n",
+    "# Set the plotting style\n",
+    "sns.set_theme(style=\"whitegrid\")\n",
+    "\n",
+    "# Set the maidr engine\n",
+    "maidr.set_engine(\"ts\")\n",
+    "\n",
+    "# Data for line plot\n",
+    "x_line = np.array([1, 2, 3, 4, 5, 6, 7, 8])\n",
+    "y_line = np.array([2, 4, 1, 5, 3, 7, 6, 8])\n",
+    "line_data = {\"x\": x_line, \"y\": y_line}\n",
+    "\n",
+    "# Data for first bar plot\n",
+    "categories = [\"A\", \"B\", \"C\", \"D\", \"E\"]\n",
+    "values = np.random.rand(5) * 10\n",
+    "bar_data = {\"categories\": categories, \"values\": values}\n",
+    "\n",
+    "# Data for second bar plot\n",
+    "categories_2 = [\"A\", \"B\", \"C\", \"D\", \"E\"]\n",
+    "values_2 = np.random.randn(5) * 100\n",
+    "bar_data_2 = {\"categories\": categories_2, \"values\": values_2}\n",
+    "\n",
+    "# Create a figure with 3 subplots arranged vertically\n",
+    "fig, axs = plt.subplots(3, 1, figsize=(10, 12))\n",
+    "\n",
+    "# First panel: Line plot using seaborn\n",
+    "sns.lineplot(x=\"x\", y=\"y\", data=line_data, color=\"blue\", linewidth=2, ax=axs[0])\n",
+    "axs[0].set_title(\"Line Plot: Random Data\")\n",
+    "axs[0].set_xlabel(\"X-axis\")\n",
+    "axs[0].set_ylabel(\"Values\")\n",
+    "\n",
+    "# Second panel: Bar plot using seaborn\n",
+    "sns.barplot(\n",
+    "    x=\"categories\", y=\"values\", data=bar_data, color=\"green\", alpha=0.7, ax=axs[1]\n",
+    ")\n",
+    "axs[1].set_title(\"Bar Plot: Random Values\")\n",
+    "axs[1].set_xlabel(\"Categories\")\n",
+    "axs[1].set_ylabel(\"Values\")\n",
+    "\n",
+    "# Third panel: Bar plot using seaborn\n",
+    "sns.barplot(\n",
+    "    x=\"categories\", y=\"values\", data=bar_data_2, color=\"blue\", alpha=0.7, ax=axs[2]\n",
+    ")\n",
+    "axs[2].set_title(\"Bar Plot 2: Random Values\")  # Fixed the typo in the title\n",
+    "axs[2].set_xlabel(\"Categories\")\n",
+    "axs[2].set_ylabel(\"Values\")\n",
+    "\n",
+    "# Adjust layout to prevent overlap\n",
+    "plt.tight_layout()\n",
+    "\n",
+    "# Display the figure\n",
+    "maidr.show(fig)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/example/multipanel/matplotlib/example_mpl_multipanel.py b/example/multipanel/matplotlib/example_mpl_multipanel.py
new file mode 100644
index 00000000..537c0c03
--- /dev/null
+++ b/example/multipanel/matplotlib/example_mpl_multipanel.py
@@ -0,0 +1,57 @@
+#!/usr/bin/env python3
+"""
+Example of creating a multipanel plot with matplotlib.
+
+This script demonstrates how to create a figure with multiple panels
+containing different types of plots: line plot, bar plot, and scatter plot.
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+import maidr
+
+maidr.set_engine("ts")
+
+x_line = np.array([1, 2, 3, 4, 5, 6, 7, 8])
+y_line = np.array([2, 4, 1, 5, 3, 7, 6, 8])
+
+# Data for bar plot
+categories = ["A", "B", "C", "D", "E"]
+values = np.random.rand(5) * 10
+
+# Data for bar plot
+categories_2 = ["A", "B", "C", "D", "E"]
+values_2 = np.random.randn(5) * 100
+
+# Data for scatter plot
+x_scatter = np.random.randn(50)
+y_scatter = np.random.randn(50)
+
+# Create a figure with 3 subplots arranged vertically
+fig, axs = plt.subplots(3, 1, figsize=(10, 12))
+
+# First panel: Line plot
+axs[0].plot(x_line, y_line, color="blue", linewidth=2)
+axs[0].set_title("Line Plot: Random Data")
+axs[0].set_xlabel("X-axis")
+axs[0].set_ylabel("Values")
+axs[0].grid(True, linestyle="--", alpha=0.7)
+
+# Second panel: Bar plot
+axs[1].bar(categories, values, color="green", alpha=0.7)
+axs[1].set_title("Bar Plot: Random Values")
+axs[1].set_xlabel("Categories")
+axs[1].set_ylabel("Values")
+
+# Third panel: Bar plot
+axs[2].bar(categories_2, values_2, color="blue", alpha=0.7)
+axs[2].set_title("Bar Plot 2: Random Values")
+axs[2].set_xlabel("Categories")
+axs[2].set_ylabel("Values")
+
+# Adjust layout to prevent overlap
+plt.tight_layout()
+
+# Display the figure
+maidr.show(fig)
diff --git a/example/multipanel/seaborn/example_sns_multipanel.py b/example/multipanel/seaborn/example_sns_multipanel.py
new file mode 100644
index 00000000..f799fade
--- /dev/null
+++ b/example/multipanel/seaborn/example_sns_multipanel.py
@@ -0,0 +1,65 @@
+#!/usr/bin/env python3
+"""
+Example of creating a multipanel plot with seaborn.
+
+This script demonstrates how to create a figure with multiple panels
+containing different types of plots using seaborn: line plot, bar plot, and bar plot.
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+import seaborn as sns
+
+import maidr
+
+# Set the plotting style
+sns.set_theme(style="whitegrid")
+
+# Set the maidr engine
+maidr.set_engine("ts")
+
+# Data for line plot
+x_line = np.array([1, 2, 3, 4, 5, 6, 7, 8])
+y_line = np.array([2, 4, 1, 5, 3, 7, 6, 8])
+line_data = {"x": x_line, "y": y_line}
+
+# Data for first bar plot
+categories = ["A", "B", "C", "D", "E"]
+values = np.random.rand(5) * 10
+bar_data = {"categories": categories, "values": values}
+
+# Data for second bar plot
+categories_2 = ["A", "B", "C", "D", "E"]
+values_2 = np.random.randn(5) * 100
+bar_data_2 = {"categories": categories_2, "values": values_2}
+
+# Create a figure with 3 subplots arranged vertically
+fig, axs = plt.subplots(3, 1, figsize=(10, 12))
+
+# First panel: Line plot using seaborn
+sns.lineplot(x="x", y="y", data=line_data, color="blue", linewidth=2, ax=axs[0])
+axs[0].set_title("Line Plot: Random Data")
+axs[0].set_xlabel("X-axis")
+axs[0].set_ylabel("Values")
+
+# Second panel: Bar plot using seaborn
+sns.barplot(
+    x="categories", y="values", data=bar_data, color="green", alpha=0.7, ax=axs[1]
+)
+axs[1].set_title("Bar Plot: Random Values")
+axs[1].set_xlabel("Categories")
+axs[1].set_ylabel("Values")
+
+# Third panel: Bar plot using seaborn
+sns.barplot(
+    x="categories", y="values", data=bar_data_2, color="blue", alpha=0.7, ax=axs[2]
+)
+axs[2].set_title("Bar Plot 2: Random Values")  # Fixed the typo in the title
+axs[2].set_xlabel("Categories")
+axs[2].set_ylabel("Values")
+
+# Adjust layout to prevent overlap
+plt.tight_layout()
+
+# Display the figure
+maidr.show(fig)
diff --git a/maidr/api.py b/maidr/api.py
index c3755016..4b747069 100644
--- a/maidr/api.py
+++ b/maidr/api.py
@@ -21,7 +21,7 @@ def render(plot: Any) -> Tag:
 def show(plot: Any, renderer: Literal["auto", "ipython", "browser"] = "auto") -> object:
     ax = FigureManager.get_axes(plot)
     htmls = []
-    if type(ax) is list:
+    if isinstance(ax, list):
         for axes in ax:
             maidr = FigureManager.get_maidr(axes.get_figure())
             htmls.append(maidr.render())
@@ -36,7 +36,7 @@ def save_html(
 ) -> str:
     ax = FigureManager.get_axes(plot)
     htmls = []
-    if type(ax) is list:
+    if isinstance(ax, list):
         for axes in ax:
             maidr = FigureManager.get_maidr(axes.get_figure())
             htmls.append(maidr.render())
diff --git a/maidr/core/maidr.py b/maidr/core/maidr.py
index aee44224..a7f9fb02 100644
--- a/maidr/core/maidr.py
+++ b/maidr/core/maidr.py
@@ -6,7 +6,7 @@
 import tempfile
 import uuid
 import webbrowser
-from typing import Literal
+from typing import Any, Literal
 
 from htmltools import HTML, HTMLDocument, Tag, tags
 from lxml import etree
@@ -139,23 +139,66 @@ def _create_html_doc(self) -> HTMLDocument:
 
     def _flatten_maidr(self) -> dict | list[dict]:
         """Return a single plot schema or a list of schemas from the Maidr instance."""
-        if self.plot_type in (PlotType.LINE, PlotType.DODGED, PlotType.STACKED):
-            self._plots = [self._plots[0]]
-        maidr = [plot.schema for plot in self._plots]
-
-        # Replace the selector having maidr='true' with maidr={self.maidr_id}
-        for plot in maidr:
-            if MaidrKey.SELECTOR in plot:
-                plot[MaidrKey.SELECTOR] = plot[MaidrKey.SELECTOR].replace(
-                    "maidr='true'", f"maidr='{self.selector_id}'"
-                )
+        # To support legacy JS Engine we will just return the format in this way
+        # but soon enough this should be deprecated and when we will completely
+        # transition to TypeScript :)
         engine = Environment.get_engine()
         if engine == "js":
+            if self.plot_type in (PlotType.LINE, PlotType.DODGED, PlotType.STACKED):
+                self._plots = [self._plots[0]]
+            maidr = [plot.schema for plot in self._plots]
+            for plot in maidr:
+                if MaidrKey.SELECTOR in plot:
+                    plot[MaidrKey.SELECTOR] = plot[MaidrKey.SELECTOR].replace(
+                        "maidr='true'", f"maidr='{self.selector_id}'"
+                    )
             return maidr if len(maidr) != 1 else maidr[0]
-        return {
-            "id": Maidr._unique_id(),
-            "subplots": [[{"id": Maidr._unique_id(), "layers": maidr}]],
-        }
+
+        # Now let's start building the maidr object for the newer TypeScript engine
+
+        plot_schemas = []
+
+        for plot in self._plots:
+            schema = plot.schema
+            if MaidrKey.SELECTOR in schema:
+                schema[MaidrKey.SELECTOR] = schema[MaidrKey.SELECTOR].replace(
+                    "maidr='true'", f"maidr='{self.selector_id}'"
+                )
+            plot_schemas.append(
+                {
+                    "schema": schema,
+                    "row": getattr(plot, "row_index", 0),
+                    "col": getattr(plot, "col_index", 0),
+                }
+            )
+
+        max_row = max([plot.get("row", 0) for plot in plot_schemas], default=0)
+        max_col = max([plot.get("col", 0) for plot in plot_schemas], default=0)
+
+        subplot_grid: list[list[dict[str, str | list[Any]]]] = [
+            [{} for _ in range(max_col + 1)] for _ in range(max_row + 1)
+        ]
+
+        position_groups = {}
+        for plot in plot_schemas:
+            pos = (plot.get("row", 0), plot.get("col", 0))
+            if pos not in position_groups:
+                position_groups[pos] = []
+            position_groups[pos].append(plot["schema"])
+
+        for (row, col), layers in position_groups.items():
+            if subplot_grid[row][col]:
+                subplot_grid[row][col]["layers"].append(layers)
+            else:
+                subplot_grid[row][col] = {"id": Maidr._unique_id(), "layers": layers}
+
+        for i in range(len(subplot_grid)):
+            subplot_grid[i] = [
+                cell if cell is not None else {"id": Maidr._unique_id(), "layers": []}
+                for cell in subplot_grid[i]
+            ]
+
+        return {"id": Maidr._unique_id(), "subplots": subplot_grid}
 
     def _get_svg(self) -> HTML:
         """Extract the chart SVG from ``matplotlib.figure.Figure``."""
diff --git a/maidr/core/plot/maidr_plot.py b/maidr/core/plot/maidr_plot.py
index d9c858b6..3d4f8497 100644
--- a/maidr/core/plot/maidr_plot.py
+++ b/maidr/core/plot/maidr_plot.py
@@ -41,6 +41,9 @@ def __init__(self, ax: Axes, plot_type: PlotType) -> None:
         self.ax = ax
         self._support_highlighting = True
         self._elements = []
+        ss = self.ax.get_subplotspec()
+        self.row_index = ss.rowspan.start
+        self.col_index = ss.colspan.start
 
         # MAIDR data
         self.type = plot_type
diff --git a/maidr/patch/scatterplot.py b/maidr/patch/scatterplot.py
index b30edfb6..32067351 100644
--- a/maidr/patch/scatterplot.py
+++ b/maidr/patch/scatterplot.py
@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 import wrapt
-
 from matplotlib.axes import Axes
 from matplotlib.collections import PathCollection