diff --git a/.env b/.env
index 5170ea1..697ecb4 100644
--- a/.env
+++ b/.env
@@ -9,7 +9,6 @@ DB_PASSWORD=password
 
 # MLFlow
 MLFLOW_BACKEND_STORE_URI=postgresql://${DB_USER}:${DB_PASSWORD}@postgres:5432/${DB_NAME}
-MLFLOW_TRACKING_URI=http://mlflow:5000
 
 # Prefect
 PREFECT_API_DATABASE_CONNECTION_URL=postgresql+asyncpg://${DB_USER}:${DB_PASSWORD}@postgres:5432/prefect
diff --git a/app/app.py b/app/app.py
index 784d137..ef0ec4e 100644
--- a/app/app.py
+++ b/app/app.py
@@ -4,6 +4,8 @@
 # Imports
 ######################################
 
+import os
+
 import dash_bootstrap_components as dbc
 import pandas as pd
 import plotly.express as px
@@ -12,6 +14,13 @@
 from hydra import compose, initialize
 from hydra.utils import instantiate
 
+######################################
+# Environment
+######################################
+
+if os.environ.get("PREFECT_API_URL") is None:
+    os.environ["PREFECT_API_URL"] = "http://127.0.0.1:4200/api"
+
 ######################################
 # Functions
 ######################################
diff --git a/app/conf/form/common.yaml b/app/conf/form/common.yaml
index e5bd316..0f20842 100644
--- a/app/conf/form/common.yaml
+++ b/app/conf/form/common.yaml
@@ -310,11 +310,6 @@ components:
           children: Run model
           color: primary
           className: me-1
-      - id: download-sim-data-input
-        label: Download
-        help: Download the simulation output data
-        class_name: dash_daq.BooleanSwitch.BooleanSwitch 
-        kwargs: {}
       - id: save-param-button
         label: Save
         help: Save current parameter configuration to file
diff --git a/app/flows/bye_flow.py b/app/flows/bye_flow.py
deleted file mode 100644
index c82f4b9..0000000
--- a/app/flows/bye_flow.py
+++ /dev/null
@@ -1,38 +0,0 @@
-#!/usr/bin/env python
-
-######################################
-# Imports
-######################################
-
-from prefect import context, flow, task
-from prefect.task_runners import SequentialTaskRunner
-
-######################################
-# Main
-######################################
-
-
-@task
-def bye() -> None:
-    print(context.get_run_context().task_run.flow_run_id)
-    print("Bye")
-
-
-task_runner = SequentialTaskRunner()
-
-
-@flow(
-    name="Bye",
-    description="Bye description.",
-    task_runner=task_runner,
-)
-def bye_flow() -> None:
-    bye.submit()
-
-
-def main() -> None:
-    bye_flow()
-
-
-if __name__ == "__main__":
-    main()
diff --git a/app/flows/hello_flow.py b/app/flows/hello_flow.py
deleted file mode 100644
index c4f2129..0000000
--- a/app/flows/hello_flow.py
+++ /dev/null
@@ -1,53 +0,0 @@
-#!/usr/bin/env python
-
-######################################
-# Imports
-######################################
-
-import asyncio
-
-from prefect import context, flow, task
-from prefect.client import get_client
-from prefect.runtime import flow_run
-from prefect.task_runners import SequentialTaskRunner
-
-######################################
-# Main
-######################################
-
-
-@task
-async def hello() -> None:
-    print(context.get_run_context().task_run.flow_run_id)
-    print("Hello")
-
-
-@task
-async def add_tags(id: str) -> None:
-    client = get_client()
-    current_flow_run_id = flow_run.id
-    tags = flow_run.tags
-    tags.append(id)
-    await client.update_flow_run(current_flow_run_id, tags=tags)
-
-
-task_runner = SequentialTaskRunner()
-
-
-@flow(
-    name="Hello",
-    description="Hello description.",
-    task_runner=task_runner,
-)
-async def hello_flow() -> None:
-    await hello.submit()
-    await add_tags("http://localhost:4200")
-
-
-async def main() -> None:
-    await hello_flow()
-
-
-if __name__ == "__main__":
-    loop = asyncio.get_event_loop()
-    loop.run_until_complete(main())
diff --git a/app/flows/prefect.yaml b/app/flows/prefect.yaml
index 1bc1afc..e64101a 100644
--- a/app/flows/prefect.yaml
+++ b/app/flows/prefect.yaml
@@ -19,15 +19,37 @@ pull:
 
 # the deployments section allows you to provide configuration for deploying flows
 deployments:
-- name: Hello Flow
-  description: Hello description.
-  entrypoint: /app/flows/hello_flow.py:hello_flow
+- name: run_simulation_flow
+  description: Run a single simulation for the root model.
+  entrypoint: /app/flows/run_simulation.py:run_simulation_flow
   parameters: {}
   work_pool:
     name: default
-- name: Bye Flow
-  description: Bye description.
-  entrypoint: /app/flows/bye_flow.py:bye_flow
+
+- name: run_optimisation_flow
+  description: Run an optimisation procedure for the root model.
+  entrypoint: /app/flows/run_optimisation.py:run_optimisation_flow
+  parameters: {}
+  work_pool:
+    name: default
+
+- name: run_sensitivity_analysis_flow
+  description: Run a sensitivity analysis for the root model.
+  entrypoint: /app/flows/run_sensitivity_analysis.py:run_sensitivity_analysis_flow
+  parameters: {}
+  work_pool:
+    name: default
+
+- name: run_abc_flow
+  description: Perform Bayesian parameter estimation for the root model using Approximate Bayesian Computation.
+  entrypoint: /app/flows/run_abc.py:run_abc_flow
+  parameters: {}
+  work_pool:
+    name: default
+
+- name: run_snpe_flow
+  description: Perform Bayesian parameter estimation for the root model using Sequential Neural Posterior Estimation.
+  entrypoint: /app/flows/run_snpe.py:run_snpe_flow
   parameters: {}
   work_pool:
     name: default
\ No newline at end of file
diff --git a/app/flows/prefect_remote_dispatch.py b/app/flows/prefect_remote_dispatch.py
deleted file mode 100644
index 84c1879..0000000
--- a/app/flows/prefect_remote_dispatch.py
+++ /dev/null
@@ -1,40 +0,0 @@
-import os
-import uuid
-
-from dash import Dash, Input, Output, State, callback, dcc, html
-from prefect.deployments import run_deployment
-
-os.environ["PREFECT_UI_URL"] = "http://127.0.0.1:4200/api"
-os.environ["PREFECT_API_URL"] = "http://127.0.0.1:4200/api"
-
-app = Dash(__name__)
-
-app.layout = html.Div(
-    [
-        html.Div(dcc.Input(id="input-on-submit", type="text")),
-        html.Button("Submit", id="submit-val", n_clicks=0),
-        html.Div(
-            id="container-button-basic", children="Enter a value and press submit"
-        ),
-    ]
-)
-
-
-@callback(
-    Output("container-button-basic", "children"),
-    Input("submit-val", "n_clicks"),
-    prevent_initial_call=True,
-)
-def update_output(n_clicks: int) -> str:
-    run_id = str(uuid.uuid4())
-    run_deployment("Hello/Hello Flow", flow_run_name=f"run-{run_id}", timeout=0)
-
-    run_deployment("Bye/Bye Flow", flow_run_name=f"run-{run_id}", timeout=0)
-
-    return 'The input value was "{}" and the button has been clicked {} times'.format(
-        run_id, n_clicks
-    )
-
-
-if __name__ == "__main__":
-    app.run(debug=True)
diff --git a/app/flows/run_abc.py b/app/flows/run_abc.py
new file mode 100644
index 0000000..f42a77d
--- /dev/null
+++ b/app/flows/run_abc.py
@@ -0,0 +1,38 @@
+#!/usr/bin/env python
+
+######################################
+# Imports
+######################################
+
+import mlflow
+from prefect import context, flow, task
+from prefect.task_runners import ConcurrentTaskRunner
+
+from deeprootgen.data_model import RootSimulationModel
+from deeprootgen.model import RootSystemSimulation
+from deeprootgen.pipeline import (
+    begin_experiment,
+    log_config,
+    log_experiment_details,
+    log_simulation,
+)
+
+######################################
+# Main
+######################################
+
+
+@task
+def run_abc() -> None:
+    print("hello")
+
+
+@flow(
+    name="abc",
+    description="Perform Bayesian parameter estimation for the root model using Approximate Bayesian Computation.",
+    task_runner=ConcurrentTaskRunner(),
+)
+def run_abc_flow(
+    # input_params: RootSimulationModel
+) -> None:
+    run_abc.submit()
diff --git a/app/flows/run_optimisation.py b/app/flows/run_optimisation.py
new file mode 100644
index 0000000..6802d22
--- /dev/null
+++ b/app/flows/run_optimisation.py
@@ -0,0 +1,38 @@
+#!/usr/bin/env python
+
+######################################
+# Imports
+######################################
+
+import mlflow
+from prefect import context, flow, task
+from prefect.task_runners import ConcurrentTaskRunner
+
+from deeprootgen.data_model import RootSimulationModel
+from deeprootgen.model import RootSystemSimulation
+from deeprootgen.pipeline import (
+    begin_experiment,
+    log_config,
+    log_experiment_details,
+    log_simulation,
+)
+
+######################################
+# Main
+######################################
+
+
+@task
+def run_optimisation() -> None:
+    print("hello")
+
+
+@flow(
+    name="optimisation",
+    description="Run an optimisation procedure for the root model.",
+    task_runner=ConcurrentTaskRunner(),
+)
+def run_optimisation_flow(
+    # input_params: RootSimulationModel
+) -> None:
+    run_optimisation.submit()
diff --git a/app/flows/run_sensitivity_analysis.py b/app/flows/run_sensitivity_analysis.py
new file mode 100644
index 0000000..e86088f
--- /dev/null
+++ b/app/flows/run_sensitivity_analysis.py
@@ -0,0 +1,38 @@
+#!/usr/bin/env python
+
+######################################
+# Imports
+######################################
+
+import mlflow
+from prefect import context, flow, task
+from prefect.task_runners import ConcurrentTaskRunner
+
+from deeprootgen.data_model import RootSimulationModel
+from deeprootgen.model import RootSystemSimulation
+from deeprootgen.pipeline import (
+    begin_experiment,
+    log_config,
+    log_experiment_details,
+    log_simulation,
+)
+
+######################################
+# Main
+######################################
+
+
+@task
+def run_sensitivity_analysis() -> None:
+    print("hello")
+
+
+@flow(
+    name="sensitivity_analysis",
+    description="Run a sensitivity analysis for the root model.",
+    task_runner=ConcurrentTaskRunner(),
+)
+def run_sensitivity_analysis_flow(
+    # input_params: RootSimulationModel
+) -> None:
+    run_sensitivity_analysis.submit()
diff --git a/app/flows/run_simulation.py b/app/flows/run_simulation.py
new file mode 100644
index 0000000..5eb1021
--- /dev/null
+++ b/app/flows/run_simulation.py
@@ -0,0 +1,74 @@
+#!/usr/bin/env python
+
+######################################
+# Imports
+######################################
+
+import mlflow
+from prefect import context, flow, task
+from prefect.task_runners import ConcurrentTaskRunner
+
+from deeprootgen.data_model import RootSimulationModel
+from deeprootgen.model import RootSystemSimulation
+from deeprootgen.pipeline import (
+    begin_experiment,
+    log_config,
+    log_experiment_details,
+    log_simulation,
+)
+
+######################################
+# Main
+######################################
+
+
+@task
+def run_simulation(input_parameters: RootSimulationModel, simulation_uuid: str) -> None:
+    """Running a single root simulation.
+
+    Args:
+        input_parameters (RootSimulationModel):
+            The root simulation data model.
+        simulation_uuid (str):
+            The simulation uuid.
+    """
+    task = "simulation"
+    flow_run_id = context.get_run_context().task_run.flow_run_id
+    begin_experiment(
+        task, simulation_uuid, flow_run_id, input_parameters.simulation_tag  # type: ignore
+    )
+
+    simulation = RootSystemSimulation(
+        simulation_tag=input_parameters.simulation_tag,  # type: ignore
+        random_seed=input_parameters.random_seed,  # type: ignore
+    )
+    simulation.run(input_parameters)
+    config = input_parameters.dict()
+
+    for k, v in config.items():
+        mlflow.log_param(k, v)
+
+    log_config(config, task)
+    log_simulation(input_parameters, simulation, task)
+    log_experiment_details(simulation_uuid)
+
+    mlflow.end_run()
+
+
+@flow(
+    name="simulation",
+    description="Run a single simulation for the root model.",
+    task_runner=ConcurrentTaskRunner(),
+)
+def run_simulation_flow(
+    input_parameters: RootSimulationModel, simulation_uuid: str
+) -> None:
+    """Flow for running a single root simulation.
+
+    Args:
+        input_parameters (RootSimulationModel):
+            The root simulation data model.
+        simulation_uuid (str):
+            The simulation uuid.
+    """
+    run_simulation.submit(input_parameters, simulation_uuid)
diff --git a/app/flows/run_snpe.py b/app/flows/run_snpe.py
new file mode 100644
index 0000000..57d9b99
--- /dev/null
+++ b/app/flows/run_snpe.py
@@ -0,0 +1,38 @@
+#!/usr/bin/env python
+
+######################################
+# Imports
+######################################
+
+import mlflow
+from prefect import context, flow, task
+from prefect.task_runners import ConcurrentTaskRunner
+
+from deeprootgen.data_model import RootSimulationModel
+from deeprootgen.model import RootSystemSimulation
+from deeprootgen.pipeline import (
+    begin_experiment,
+    log_config,
+    log_experiment_details,
+    log_simulation,
+)
+
+######################################
+# Main
+######################################
+
+
+@task
+def run_snpe() -> None:
+    print("hello")
+
+
+@flow(
+    name="snpe",
+    description="Perform Bayesian parameter estimation for the root model using Sequential Neural Posterior Estimation.",
+    task_runner=ConcurrentTaskRunner(),
+)
+def run_snpe_flow(
+    # input_params: RootSimulationModel
+) -> None:
+    run_snpe.submit()
diff --git a/app/pages/generate_root_system.py b/app/pages/generate_root_system.py
index 8f0b2f1..262ac3d 100644
--- a/app/pages/generate_root_system.py
+++ b/app/pages/generate_root_system.py
@@ -12,6 +12,7 @@
 import pandas as pd
 import yaml
 from dash import ALL, Input, Output, State, callback, dcc, get_app, html, register_page
+from prefect.deployments import run_deployment
 
 from deeprootgen.data_model import RootSimulationModel
 from deeprootgen.form import (
@@ -19,7 +20,7 @@
     build_common_components,
     build_common_layout,
 )
-from deeprootgen.model import RootSystemSimulation
+from deeprootgen.pipeline import get_simulation_uuid
 
 ######################################
 # Constants
@@ -146,16 +147,17 @@ def update_output(list_of_contents: list, list_of_names: list) -> tuple:
 
 
 @callback(
-    Output("generate-root-system-plot", "figure"),
-    Output(f"{PAGE_ID}-download-content", "data"),
+    # Output("generate-root-system-plot", "figure"),
+    # Output(f"{PAGE_ID}-download-content", "data"),
     Input({"index": f"{PAGE_ID}-run-sim-button", "type": ALL}, "n_clicks"),
     State({"type": f"{PAGE_ID}-parameters", "index": ALL}, "value"),
     State({"index": f"{PAGE_ID}-enable-soil-input", "type": ALL}, "on"),
-    State({"index": f"{PAGE_ID}-download-sim-data-input", "type": ALL}, "on"),
     prevent_initial_call=True,
 )
 def run_root_model(
-    n_clicks: list, form_values: list, enable_soils: list, download_data: list
+    n_clicks: list,
+    form_values: list,
+    enable_soils: list,
 ) -> dcc.Graph:
     """Run and plot the root model.
 
@@ -166,8 +168,7 @@ def run_root_model(
             The form input data.
         enable_soils (list):
             Enable visualisation of soil data.
-        download_data (list):
-            Whether to download the simulation results data.
+
     Returns:
         dcc.Graph: The visualised root model.
     """
@@ -185,27 +186,27 @@ def run_root_model(
     enable_soil: bool = enable_soils[0]
     form_inputs["enable_soil"] = enable_soil == True  # noqa: E712
 
-    input_params = RootSimulationModel.parse_obj(form_inputs)
-    simulation = RootSystemSimulation(
-        simulation_tag=input_params.simulation_tag,
-        random_seed=input_params.random_seed,
-        visualise=True,
+    simulation_uuid = get_simulation_uuid()
+    run_deployment(
+        "simulation/run_simulation_flow",
+        parameters=dict(input_params=form_inputs, simulation_uuid=simulation_uuid),
+        flow_run_name=f"run-{simulation_uuid}",
+        timeout=0,
     )
-    results = simulation.run(input_params)
 
-    download_data = download_data[0]
-    if download_data:
-        from datetime import datetime
+    # download_data = download_data[0]
+    # if download_data:
+    #     from datetime import datetime
 
-        now = datetime.today().strftime("%Y-%m-%d-%H-%M")
-        outfile = osp.join("outputs", f"{now}-nodes.csv")
-        df = pd.DataFrame(results.nodes)
-        df.to_csv(outfile, index=False)
-        download_file = dcc.send_file(outfile)
-    else:
-        download_file = None
+    #     now = datetime.today().strftime("%Y-%m-%d-%H-%M")
+    #     outfile = osp.join("outputs", f"{now}-nodes.csv")
+    #     df = pd.DataFrame(results.nodes)
+    #     df.to_csv(outfile, index=False)
+    #     download_file = dcc.send_file(outfile)
+    # else:
+    #     download_file = None
 
-    return results.figure, download_file
+    # return results.figure, download_file
 
 
 ######################################
diff --git a/deeprootgen/data_model/__init__.py b/deeprootgen/data_model/__init__.py
index 6b9623b..38f6746 100644
--- a/deeprootgen/data_model/__init__.py
+++ b/deeprootgen/data_model/__init__.py
@@ -8,7 +8,6 @@
     RootEdgeModel,
     RootNodeModel,
     RootSimulationModel,
-    RootSimulationResultModel,
     RootType,
     RootTypeModel,
 )
diff --git a/deeprootgen/data_model/simulation_data_models.py b/deeprootgen/data_model/simulation_data_models.py
index 8c66446..9cab8d7 100644
--- a/deeprootgen/data_model/simulation_data_models.py
+++ b/deeprootgen/data_model/simulation_data_models.py
@@ -6,10 +6,8 @@
 """
 
 from enum import Enum
-from typing import List, Optional
+from typing import Optional
 
-import plotly.graph_objects as go
-import pydantic
 from pydantic import BaseModel
 
 
@@ -117,18 +115,3 @@ class RootSimulationModel(BaseModel):
     no_root_zone: Optional[float] = 1e-4
     floor_threshold: Optional[float] = 0.4
     ceiling_threshold: Optional[float] = 0.9
-
-
-@pydantic.dataclasses.dataclass(config=Config)
-class RootSimulationResultModel:
-    """
-    The root system architecture simulation results data model.
-
-    Args:
-        Config (Config):
-            The Pydantic Config model class.
-    """
-
-    nodes: List[dict]
-    edges: List[dict]
-    figure: go.Figure | None
diff --git a/deeprootgen/model/root.py b/deeprootgen/model/root.py
index 9588ee3..970e098 100644
--- a/deeprootgen/model/root.py
+++ b/deeprootgen/model/root.py
@@ -8,18 +8,13 @@
 
 from typing import Dict, List
 
+import networkx as nx
 import numpy as np
 import pandas as pd
 import plotly.graph_objects as go
 from numpy.random import default_rng
 
-from ..data_model import (
-    RootNodeModel,
-    RootSimulationModel,
-    RootSimulationResultModel,
-    RootType,
-    RootTypeModel,
-)
+from ..data_model import RootNodeModel, RootSimulationModel, RootType, RootTypeModel
 from ..spatial import get_transform_matrix, make_homogenous
 from .hgraph import RootNode, RootSystemGraph
 from .soil import Soil
@@ -612,7 +607,6 @@ def __init__(
         self,
         simulation_tag: str = "default",
         random_seed: int = None,
-        visualise: bool = False,
     ) -> None:
         """RootSystemSimulation constructor.
 
@@ -621,8 +615,6 @@ def __init__(
                 A tag to group together multiple simulations. Defaults to 'default'.
             random_seed (int, optional):
                 The seed for the random number generator. Defaults to None.
-            visualise (bool, optional):
-                Whether to visualise the results. Defaults to False
 
         Returns:
             RootSystemSimulation:
@@ -632,7 +624,6 @@ def __init__(
         self.G: RootSystemGraph = RootSystemGraph()
         self.organs: Dict[int, List[RootOrgan]] = {}
         self.simulation_tag = simulation_tag
-        self.visualise = visualise
         self.rng = default_rng(random_seed)
 
     def get_yaw(self, number_of_roots: int) -> tuple:
@@ -649,6 +640,136 @@ def get_yaw(self, number_of_roots: int) -> tuple:
         yaw_base = 360 / number_of_roots
         return yaw_base, yaw_base * 0.05, yaw_base
 
+    def plot_hierarchical_graph(
+        self,
+        G: nx.Graph,
+        feature_key: str = "x",
+        x_key: str = "x",
+        y_key: str = "y",
+        z_key: str = "z",
+    ) -> go.Figure:
+        """Create a visualisation of hierarchical graph representation of the root system.
+
+        Args:
+            G (nx.Graph):
+                The NetworkX graph.
+            feature_key (str, optional):
+                The node features key. Defaults to 'x'.
+            x_key (str, optional):
+                The node features key. Defaults to 'x'.
+            y_key (str, optional):
+                The node features key. Defaults to 'y'.
+            z_key (str, optional):
+                The node features key. Defaults to 'z'.
+
+        Returns:
+            go.Figure:
+                The visualisation of the hierarchical graph representation.
+        """
+        src_indx, dest_indx = 0, 1
+        x_edges, y_edges, z_edges = [], [], []
+        x_nodes, y_nodes, z_nodes = [], [], []
+        node_texts = []
+
+        for node_indx in G.nodes:
+            node = G.nodes[node_indx]
+            x_nodes.append(node[feature_key][x_key])
+            y_nodes.append(node[feature_key][y_key])
+            z_nodes.append(node[feature_key][z_key])
+
+            node_text = f"""
+            x: {node[feature_key][x_key]}<br>
+            y: {node[feature_key][y_key]}<br>
+            z: {node[feature_key][z_key]}<br>
+            Organ ID: {node[feature_key]['organ_id']}<br>
+            Order: {node[feature_key]['order']}<br>
+            Segment rank: {node[feature_key]['segment_rank']}<br>
+            Diameter: {node[feature_key]['diameter']}<br>
+            Length: {node[feature_key]['length']}<br>
+            Root type: {node[feature_key]['root_type']}<br>
+            Order type: {node[feature_key]['order_type']}<br>
+            Position type: {node[feature_key]['position_type']}<br>
+            Simulation tag: {node[feature_key]['simulation_tag']}<br>"""
+
+            node_texts.append(node_text)
+
+        trace_nodes = go.Scatter3d(
+            x=x_nodes,
+            y=y_nodes,
+            z=z_nodes,
+            mode="markers",
+            marker=dict(
+                symbol="circle",
+                size=7,
+                color="green",
+                line=dict(color="black", width=0.5),
+            ),
+            text=node_texts,
+            hoverinfo="text",
+        )
+
+        edge_list = G.edges()
+        for edge in edge_list:
+            src_edge = edge[src_indx]
+
+            node_src = G.nodes[src_edge]
+            node_dest = G.nodes[edge[dest_indx]]
+
+            x_coords = [
+                node_src[feature_key][x_key],
+                node_dest[feature_key][x_key],
+                None,
+            ]
+            x_edges += x_coords
+
+            y_coords = [
+                node_src[feature_key][y_key],
+                node_dest[feature_key][y_key],
+                None,
+            ]
+            y_edges += y_coords
+
+            z_coords = [
+                node_src[feature_key][z_key],
+                node_dest[feature_key][z_key],
+                None,
+            ]
+            z_edges += z_coords
+
+        trace_edges = go.Scatter3d(
+            x=x_edges,
+            y=y_edges,
+            z=z_edges,
+            mode="lines",
+            line=dict(color="green", width=10),
+            hoverinfo="none",
+        )
+
+        axis = dict(
+            showbackground=False,
+            showline=False,
+            zeroline=False,
+            showgrid=False,
+            showticklabels=False,
+        )
+
+        layout = go.Layout(
+            width=1000,
+            height=1000,
+            showlegend=False,
+            scene=dict(
+                xaxis=dict(axis),
+                yaxis=dict(axis),
+                zaxis=dict(axis),
+            ),
+            margin=dict(t=100),
+            hovermode="closest",
+        )
+
+        data = [trace_edges, trace_nodes]
+        fig = go.Figure(data=data, layout=layout)
+        return fig
+
     def plot_root_system(self, fig: go.Figure, node_df: pd.DataFrame) -> go.Figure:
         """Create a visualisation of the root system.
 
@@ -716,26 +837,24 @@ def init_fig(self, input_parameters: RootSimulationModel) -> go.Figure | None:
             go.Figure | None:
                 The root system visualisation.
         """
-        fig = None
-        if self.visualise:
-            # Initialise figure (optionally with soil)
-            if input_parameters.enable_soil:
-                soil_df = self.soil.create_soil_grid(
-                    input_parameters.soil_layer_height,
-                    input_parameters.soil_n_layers,
-                    input_parameters.soil_layer_width,
-                    input_parameters.soil_n_cols,
-                )
+        # Initialise figure (optionally with soil)
+        if input_parameters.enable_soil:
+            soil_df = self.soil.create_soil_grid(
+                input_parameters.soil_layer_height,
+                input_parameters.soil_n_layers,
+                input_parameters.soil_layer_width,
+                input_parameters.soil_n_cols,
+            )
 
-                fig = self.soil.create_soil_fig(soil_df)
-            else:
-                fig = go.Figure()
+            fig = self.soil.create_soil_fig(soil_df)
+        else:
+            fig = go.Figure()
 
-            fig.update_layout(
-                scene=dict(
-                    xaxis=dict(title="x"), yaxis=dict(title="y"), zaxis=dict(title="z")
-                )
+        fig.update_layout(
+            scene=dict(
+                xaxis=dict(title="x"), yaxis=dict(title="y"), zaxis=dict(title="z")
             )
+        )
 
         return fig
 
diff --git a/deeprootgen/pipeline/__init__.py b/deeprootgen/pipeline/__init__.py
new file mode 100644
index 0000000..3226f87
--- /dev/null
+++ b/deeprootgen/pipeline/__init__.py
@@ -0,0 +1,7 @@
+from .experiment import (
+    begin_experiment,
+    get_simulation_uuid,
+    log_config,
+    log_simulation,
+)
+from .workflow import log_experiment_details
diff --git a/deeprootgen/pipeline/experiment.py b/deeprootgen/pipeline/experiment.py
new file mode 100644
index 0000000..053b6e2
--- /dev/null
+++ b/deeprootgen/pipeline/experiment.py
@@ -0,0 +1,151 @@
+"""Contains utilities for performing experiment tracking.
+
+This module defines utility functions for performing experiment
+tracking with MLflow.
+
+"""
+
+import os
+import os.path as osp
+import uuid
+from datetime import datetime
+
+import mlflow
+import yaml
+
+from ..data_model import RootSimulationModel
+from ..model import RootSystemSimulation
+
+OUT_DIR = osp.join("/app", "outputs")
+
+
+def get_outdir() -> str:
+    """Get the output directory.
+
+    Returns:
+        str:
+            The output directory.
+    """
+    return OUT_DIR
+
+
+def get_simulation_uuid() -> str:
+    """Get a new simulation uuid.
+
+    Returns:
+        str:
+            The simulation uuid.
+    """
+    simulation_uuid = str(uuid.uuid4())
+    return simulation_uuid
+
+
+def begin_experiment(
+    task: str, simulation_uuid: str, flow_run_id: str, simulation_tag: str
+) -> None:
+    """Begin the experiment session.
+
+    Args:
+        task (str):
+            The name of the current task for the experiment.
+        simulation_uuid (str):
+            The simulation uuid.
+        flow_run_id (str):
+            The Prefect flow run ID.
+        simulation_tag (str):
+            The tag for the current root model simulation.
+    """
+    experiment_name = f"root_model_{task}"
+    existing_exp = mlflow.get_experiment_by_name(experiment_name)
+    if not existing_exp:
+        mlflow.create_experiment(experiment_name)
+    mlflow.set_experiment(experiment_name)
+
+    app_url = os.environ.get("APP_USER_HOST")
+    if app_url is None:
+        app_url = "http://localhost:8000"
+
+    app_prefect_host = os.environ.get("APP_PREFECT_USER_HOST")
+    if app_prefect_host is None:
+        app_prefect_host = "http://localhost:4200"
+    prefect_flow_url = f"{app_prefect_host}/flow-runs/flow-run/{flow_run_id}"
+
+    run_description = f"""
+# DeepRootGen URL
+
+<{app_url}>
+
+# Prefect flow URL
+
+<{prefect_flow_url}>
+    """
+    mlflow.set_tag("mlflow.note.content", run_description)
+    mlflow.set_tag("task", task)
+    mlflow.set_tag("simulation_uuid", simulation_uuid)
+    mlflow.set_tag("flow_run_id", flow_run_id)
+    mlflow.set_tag("app_url", app_url)
+    mlflow.set_tag("prefect_flow_url", prefect_flow_url)
+    mlflow.set_tag("simulation_tag", simulation_tag)
+
+
+def log_config(
+    config: dict,
+    task: str,
+) -> str:
+    """Log the simulation configuration.
+
+    Args:
+        config (dict):
+            The simulation configuration as a dictionary.
+        task (str):
+            The task name.
+
+    Returns:
+        str:
+            The written configuration file.
+    """
+    outfile = osp.join(
+        OUT_DIR, f"{datetime.today().strftime('%Y-%m-%d-%H-%M')}-{task}_config.yaml"
+    )
+    with open(outfile, "w") as f:
+        yaml.dump(config, f, default_flow_style=False, sort_keys=False)
+
+    mlflow.log_artifact(outfile)
+    return outfile
+
+
+def log_simulation(
+    input_parameters: RootSimulationModel, simulation: RootSystemSimulation, task: str
+) -> None:
+    """Log details for the current simulation.
+
+    Args:
+        input_parameters (RootSimulationModel):
+            The root simulation data model.
+        simulation (RootSystemSimulation):
+            The root system simulation instance.
+        task (str):
+            The task name.
+    """
+    node_df, edge_df = simulation.G.as_df()
+    G = simulation.G.as_networkx()
+    time_now = datetime.today().strftime("%Y-%m-%d-%H-%M")
+
+    outfile = osp.join(OUT_DIR, f"{time_now}-{task}_nodes.csv")
+    node_df.to_csv(outfile, index=False)
+    mlflow.log_artifact(outfile)
+
+    outfile = osp.join(OUT_DIR, f"{time_now}-{task}_edges.csv")
+    edge_df.to_csv(outfile, index=False)
+    mlflow.log_artifact(outfile)
+
+    fig = simulation.init_fig(input_parameters)
+    fig = simulation.plot_root_system(fig, node_df)
+    outfile = osp.join(OUT_DIR, f"{time_now}-{task}_roots.html")
+    fig.write_html(outfile)
+    mlflow.log_artifact(outfile)
+
+    fig = simulation.plot_hierarchical_graph(G)
+    outfile = osp.join(OUT_DIR, f"{time_now}-{task}_hgraph.html")
+    fig.write_html(outfile)
+    mlflow.log_artifact(outfile)
diff --git a/deeprootgen/pipeline/workflow.py b/deeprootgen/pipeline/workflow.py
new file mode 100644
index 0000000..fa7040e
--- /dev/null
+++ b/deeprootgen/pipeline/workflow.py
@@ -0,0 +1,66 @@
+"""Contains utilities for managing workflows.
+
+This module defines utility functions for managing and orchestrating
+workflows with Prefect.
+
+"""
+
+import os
+
+import mlflow
+from prefect.artifacts import create_link_artifact, create_markdown_artifact
+
+
+def log_experiment_details(simulation_uuid: str) -> None:
+    """Log the experiment details.
+
+    Args:
+        simulation_uuid (str):
+            The simulation uuid.
+    """
+    run = mlflow.active_run()
+    experiment_id = run.info.experiment_id
+    run_id = run.info.run_id
+
+    app_url = os.environ.get("APP_USER_HOST")
+    if app_url is None:
+        app_url = "http://localhost:8000"
+
+    create_link_artifact(
+        key="deeprootgen-app-link",
+        link=app_url,
+        link_text="DeepRootGen",
+    )
+
+    app_mlflow_host = os.environ.get("APP_MLFLOW_USER_HOST")
+    if app_mlflow_host is None:
+        app_mlflow_host = "http://localhost:5000"
+    mlflow_experiment_url = (
+        f"{app_mlflow_host}/#/experiments/{experiment_id}/runs/{run_id}"
+    )
+
+    create_link_artifact(
+        key="mlflow-link",
+        link=mlflow_experiment_url,
+        link_text="MLflow",
+    )
+
+    flow_description = f"""
+# DeepRootGen URL
+
+Simulation UUID: {simulation_uuid}
+
+<{app_url}>
+
+# MLflow experiment URL
+
+Run ID: {run_id}
+
+<{mlflow_experiment_url}>
+    """
+
+    create_markdown_artifact(
+        key="flow-description",
+        markdown=flow_description,
+        description="Flow Description",
+    )
diff --git a/docker-compose.yaml b/docker-compose.yaml
index 9cb185d..a20243b 100644
--- a/docker-compose.yaml
+++ b/docker-compose.yaml
@@ -9,6 +9,16 @@ services:
         BUILD_DATE: date -u +'%Y-%m-%dT%H:%M:%SZ'
     restart: always
     stop_grace_period: 10s
+    environment:
+      APP_USER_HOST: http://localhost:8000
+      APP_PREFECT_USER_HOST: http://localhost:4200
+      APP_MLFLOW_USER_HOST: http://localhost:5000
+      PREFECT_API_URL: http://prefect-server:4200/api
+      MLFLOW_TRACKING_URI: http://mlflow:5000
+      MLFLOW_BACKEND_STORE_URI: $MLFLOW_BACKEND_STORE_URI
+      MLFLOW_S3_ENDPOINT_URL: http://minio:9000
+      AWS_ACCESS_KEY_ID: $AWS_ACCESS_KEY_ID
+      AWS_SECRET_ACCESS_KEY: $AWS_SECRET_ACCESS_KEY
     ports:
       - 8000:8000
     volumes:
@@ -30,6 +40,9 @@ services:
     restart: always
     stop_grace_period: 10s
     environment:
+      APP_USER_HOST: http://localhost:8000
+      APP_PREFECT_USER_HOST: http://localhost:4200
+      APP_MLFLOW_USER_HOST: http://localhost:5000
       MLFLOW_BACKEND_STORE_URI: $MLFLOW_BACKEND_STORE_URI
       MLFLOW_S3_ENDPOINT_URL: http://minio:9000
       AWS_ACCESS_KEY_ID: $AWS_ACCESS_KEY_ID
@@ -51,8 +64,12 @@ services:
     restart: always
     stop_grace_period: 10s
     environment:
+      APP_USER_HOST: http://localhost:8000
+      APP_PREFECT_USER_HOST: http://localhost:4200
+      APP_MLFLOW_USER_HOST: http://localhost:5000
       PREFECT_UI_URL: http://127.0.0.1:4200/api
       PREFECT_API_URL: http://127.0.0.1:4200/api
+      MLFLOW_TRACKING_URI: http://mlflow:5000
       PREFECT_SERVER_API_HOST: 0.0.0.0
       PREFECT_API_DATABASE_CONNECTION_URL: $PREFECT_API_DATABASE_CONNECTION_URL
     ports:
@@ -70,12 +87,22 @@ services:
     restart: always
     stop_grace_period: 10s
     environment:
+      APP_USER_HOST: http://localhost:8000
+      APP_PREFECT_USER_HOST: http://localhost:4200
+      APP_MLFLOW_USER_HOST: http://localhost:5000
       PREFECT_API_URL: http://prefect-server:4200/api
+      MLFLOW_TRACKING_URI: http://mlflow:5000
+      MLFLOW_BACKEND_STORE_URI: $MLFLOW_BACKEND_STORE_URI
+      MLFLOW_S3_ENDPOINT_URL: http://minio:9000
+      AWS_ACCESS_KEY_ID: $AWS_ACCESS_KEY_ID
+      AWS_SECRET_ACCESS_KEY: $AWS_SECRET_ACCESS_KEY
     depends_on:
       - prefect-server
     entrypoint: prefect worker start -p default
     volumes:
       - ./app/flows:/app/flows
+      - ./deeprootgen:/app/deeprootgen
+      - ./app/outputs:/app/outputs
 
   prefect-deployments:
     image: ghcr.io/jbris/deep-root-gen:${APP_VERSION}
diff --git a/docs/source/api_reference/form.rst b/docs/source/api_reference/form.rst
index 4c3ef44..be67e7c 100644
--- a/docs/source/api_reference/form.rst
+++ b/docs/source/api_reference/form.rst
@@ -1,5 +1,8 @@
 Form
 ====
 
+Components
+----------
+
 .. automodule:: deeprootgen.form.components
    :members:
\ No newline at end of file
diff --git a/docs/source/api_reference/index.rst b/docs/source/api_reference/index.rst
index f4d2725..a82d495 100644
--- a/docs/source/api_reference/index.rst
+++ b/docs/source/api_reference/index.rst
@@ -6,4 +6,6 @@ API Reference
 
     data_model.rst
     form.rst
-    model.rst
\ No newline at end of file
+    model.rst
+    spatial.rst
+    pipeline.rst
\ No newline at end of file
diff --git a/docs/source/api_reference/model.rst b/docs/source/api_reference/model.rst
index ce4ba40..375e98b 100644
--- a/docs/source/api_reference/model.rst
+++ b/docs/source/api_reference/model.rst
@@ -4,7 +4,7 @@ Model
 Graph
 -----
 
-.. automodule:: deeprootgen.model.graph
+.. automodule:: deeprootgen.model.hgraph
    :members:
 
 Root
diff --git a/docs/source/api_reference/pipeline.rst b/docs/source/api_reference/pipeline.rst
new file mode 100644
index 0000000..a5c84ad
--- /dev/null
+++ b/docs/source/api_reference/pipeline.rst
@@ -0,0 +1,14 @@
+Pipeline
+========
+
+Experiment
+----------
+
+.. automodule:: deeprootgen.pipeline.experiment
+   :members:
+
+Workflow
+--------
+
+.. automodule:: deeprootgen.pipeline.workflow
+   :members:
\ No newline at end of file
diff --git a/docs/source/api_reference/spatial.rst b/docs/source/api_reference/spatial.rst
new file mode 100644
index 0000000..2a4ce20
--- /dev/null
+++ b/docs/source/api_reference/spatial.rst
@@ -0,0 +1,8 @@
+Spatial
+=======
+
+Transform
+---------
+
+.. automodule:: deeprootgen.spatial.transform
+   :members:
\ No newline at end of file