The product

You ask. Your agent runs the analysis.

SCMotif is a hosted analysis workspace with an MCP server. Your agent in ChatGPT or Claude connects to it, builds workflows and runs analyses. You inspect the data, scenarios and results in your browser.

One analysis, from start to finish

One question leads to the next.

A European wine and spirits network. A quarter of shipment data. The question: which delivery routes reduce costs? This tour follows an executed demo case using example data.

Illustrative conversation, real product captures from the demo project.

01 / The network

You

Show me how our network delivers today.

  • shipment-export-q3.csv
  • sites.xlsx
  • carrier-rate-card-2026.xlsx
  • product-prices.csv

Your agent

The Athens distribution centre is missing coordinates in your site file. May I use 37.9838° N, 23.7275° E for Athens?

You

Yes, those coordinates are right. Prepare the data and build the network.

Your agent

The baseline network is ready. Here is the map; the workflow records the preparation and calculations.

Open the baseline map in SCMotif

In SCMotif

The baseline network on the map.
The baseline network on the map. Open full size ↗

Your agent builds and runs the workflow: from 833 export rows it removes 9 duplicates and 14 cancelled shipments, matches site names and normalizes amounts and units. This produces 72 flows. The baseline scenario holds the network together with its data and assumptions.

Inspect the workflow the agent built
Files, preparation and calculations in one saved sequence.
Files, preparation and calculations in one saved sequence. Open full size ↗

Date errors need to be identified; those date fields are not used to build the flows.

See the flows as a flow diagram
The same flows as a flow diagram.
The same flows as a flow diagram. Open full size ↗
Inspect the original shipment export
The shipment export before preparation begins.
The shipment export before preparation begins. Open full size ↗

02 / The alternative

You

Could we cut costs by supplying some markets directly?

Your agent

I’ll use the existing lane rates and calculate higher per-pallet costs where shipments can’t fill a truck. The delivered quantities will stay the same. Shall I use these assumptions for the comparison?

You

Yes. Use these assumptions for this comparison.

Your agent

I’ve calculated an alternative plan using the agreed costs and constraints. Transport costs for the quarter fall from €689,210 to €505,623 — a saving of €183,587 (26.6%). The plan is saved as a separate scenario alongside the baseline. The flow diagram shows which deliveries now skip the hubs.

Open the optimized plan in SCMotif

In SCMotif

The optimized plan as a flow diagram. Flows that skip both hubs are direct deliveries.
The optimized plan as a flow diagram. Flows that skip both hubs are direct deliveries. Open full size ↗

The saving depends on the supplied rates and the calculated premiums for partially filled trucks.

See the optimized plan on the map
The full network under the optimized plan.
The full network under the optimized plan. Open full size ↗
What this comparison assumes
Comparison basis
The baseline uses flows and freight costs from the cleaned shipments. The optimized plan uses the rate card. Both cover the same quarter and delivered quantities.
Routes and truck utilization
The supplied rates already include direct routes. The workflow keeps the full-truck rate and calculates higher per-pallet rates for 80% and 60% fills: base rate × 0.95 ÷ fill fraction. Existing LTL rates stay unchanged. Inventory assumptions set replenishment frequency and therefore which fill levels are feasible.
Capacity and costs
Supplier capacity is unconstrained. Hub handling and financing of duty-paid inventory use the supplied assumptions. Site fixed costs are outside this comparison.
What this run establishes
This run does not show sensitivity to different rates or inventory assumptions. It is a first model comparison; changed assumptions need another run.

03 / The explanation

You

Where do the savings come from? Put the comparison together for me.

Your agent

About 2,684 pallets now travel directly from producers to distribution centres. Previously, every delivery passed through a hub. For example, the plan sends 580 pallets of still red wine directly from Bavarian Vintners to Berlin. This reduces hub handling; the total quantity delivered stays the same. Here is the comparison.

Same quarter. Same quantity delivered.
MeasureBaselineOptimized
Pallets delivered9,6609,660
Pallets delivered directly02,683.9
Transport costs€689,210€505,623
Hub handling costs€113,914€80,473

Transport and handling are separate cost components. This table shows selected metrics, not a complete total-cost calculation.

Open the dashboard in SCMotif

In SCMotif

The demo project dashboard compares the baseline and optimized plan.
The demo project dashboard compares the baseline and optimized plan. Open full size ↗

The savings shown belong to this demo case and its assumptions. Your network needs an analysis using your own data.

Trace one result

Example: still red wine from Bavarian Vintners to Berlin, delivered directly by truck.

Rate card input
€50 per pallet on the Bavarian Vintners → DC Berlin FTL lane.
Volume in the optimized result
580 pallets on this lane for the quarter.
Transport cost on this lane
580 × €50 = €29,000. This amount appears in the optimized flow.

This checks one lane’s transport cost; it does not attribute the entire saving to that lane.

Tools for your next question

The workflow follows your question. These analyses are available alongside the example above.

Flow maps
See where the volume actually goes.
Center of gravity
Where a site should sit, given the flows.
XYZ segmentation
Sorts items by how steady their demand is, before anything is planned around them.
What-if scenarios
Build several and compare them side by side.
Network optimization
Solves a mixed-integer model instead of guessing the answer.

Fit & limits

Does SCMotif fit your analysis?

What can I bring in?
Tabular data as CSV or Excel (XLSX, XLS). The fields you need depend on the question: a map needs different inputs from a cost optimization.
What are the size limits?
The default configuration allows up to 1 GiB per file and 1,000,000 data rows per parsed table. XLSX also has a 200 MiB uncompressed limit and a maximum compression ratio of 100:1. The default storage budget is 5 GiB per account, including computed data. Your workspace configuration may differ.
How large can an optimization model be?
The file limit is not a promise about solvable network size. Runtime and memory depend on products, routes and constraints. No universal maximum site count is promised here; we assess the fit using your analysis during the beta.
What remains after a run?
The saved workflow, generated scenarios and a dashboard in the workspace. You can inspect results as tables and visualizations, and run the workflow again.
How do I get access?
Access to the hosted workspace and MCP server is through the private beta. Bring a concrete analysis and the data it needs.

Bring a question from your own work.

The private beta starts with a concrete analysis you need to deliver.

Explore beta access →