AI/ML supply chain platform development.
We build AI and machine learning supply chain software that your company owns: demand forecasting, replenishment, supplier and lead-time prediction, route optimisation and AI agents that draft the next action for a planner to approve. It runs on the data already sitting in your ERP, WMS and TMS, instead of a planning suite you rent and reshape your process around.
- RReorder proposal draftedWaiting for buyer approval
- SSupplier lead time slippingOpen orders flagged for review
- UUnusual order quantityHeld as an exception
- FForecast error above thresholdRetraining queued
AI/ML supply chain platform development: what it is
AI/ML supply chain platform development is the building of a company's own forecasting, optimisation and decision software on its supply chain data, instead of renting a packaged planning suite.
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What an AI/ML supply chain platform from Moweb does.
Most mid-market supply chains already hold the data that machine learning needs: years of sales orders, purchase orders, receipts, stock movements and deliveries spread across an ERP, a warehouse system and a transport or dispatch tool. What they lack is the layer that turns that history into a forecast, a reorder quantity, a risk flag or a better route, and puts it in front of the person who makes the call. That layer is what we build.
An AI/ML supply chain platform from Moweb is your own software, not a licence. It joins your ERP, WMS and TMS data into one clean foundation, trains models on your products, customers, suppliers and lanes, and returns its recommendations to the screens and systems your team already uses. Planners and buyers stay in charge: the platform drafts, explains and flags, and people approve.
We start with the one or two decisions where better predictions would change the most, such as what to reorder and when, or which supplier orders are likely to arrive late, prove the value on your own data, and then extend the platform one use case at a time.
How we keep supply chain machine learning trustworthy.
A model that looked good in a notebook and drifts quietly in production does more harm than a spreadsheet. These are part of every platform we build, not extras.
Measured against your current method
Before any model goes live we back-test it on your own history and compare it with how you plan today, whether that is a moving average, last year plus a percentage or a planner's judgement. You see where it helps, where it does not, and by how much, on your data.
Humans approve, the system drafts
Purchase orders, transfers, reschedules and exceptions are proposed with the reasons behind them, then approved, edited or rejected by a named person. Nothing is sent to a supplier or carrier without the approval rules you set.
Monitoring, drift and retraining
Forecast error, data freshness and input drift are tracked for every model. When accuracy falls below an agreed threshold or the data changes shape, the platform alerts your team and retrains on a schedule, with every model version logged so you can roll back.
Data you can trust underneath
Most of the work in supply chain ML is the data: matching item codes across systems, handling returns and stock-outs so they do not distort demand, and fixing unit-of-measure mismatches. We build that foundation first and keep it tested.
How we build your AI/ML supply chain platform.
Four stages, each ending in something you can check before we move on. We sign an NDA before discovery, so your data and plans stay confidential from the first conversation.
Discovery and data audit
We map the decisions you want to improve, the systems that hold the data and how clean it is. You get a written view of which use cases your data can support now and which need more history or better capture first.
Proof on your own data
We build the data foundation for the first use case and back-test models against your history and your current planning method, so the decision to go further rests on evidence from your own business.
Build into your workflow
The models are wrapped in a working application: planner screens, approval steps, alerts and integrations that write approved actions back to your ERP, WMS or TMS. We run it alongside your current process before switching over.
Run, monitor and extend
You get monitoring, drift alerts, retraining pipelines and documentation. We then add the next use case on the same foundation, or hand the platform over to your own team.
What we build into an AI/ML supply chain platform.
Each capability can be built on its own or added over time, on one shared data foundation, so later use cases cost less than the first.
Demand forecasting
Forecasts by item, location, customer or channel that learn from your sales history, seasonality, promotions, price changes and, where they help, external signals such as holidays or weather. Planners can see the forecast, the drivers behind it and override it with a reason.
Inventory optimisation and replenishment
Safety stock, reorder points and order quantities calculated per item and location from forecast uncertainty and real supplier lead times, with suggested purchase orders and stock transfers ready for approval.
Supplier risk and lead-time prediction
Models that learn each supplier's actual delivery behaviour from your receipts, predict which open orders are likely to arrive late or short, and flag them early enough for a buyer to act.
Route and dispatch optimisation
Delivery routes and dispatch plans that respect vehicle capacity, delivery windows, driver shifts and customer priorities, built into your dispatch screens or a driver app rather than a separate tool.
Anomaly detection
Unusual orders, sudden demand spikes, stock discrepancies, duplicate invoices and data errors caught automatically and routed to the right person, instead of being found at month end.
AI agents for purchase orders and exceptions
AI agents that read the forecast, stock position and supplier status, draft purchase orders, expedite requests or exception notes in plain language, and queue them for a buyer or planner to approve before anything is sent.
Data foundation across ERP, WMS and TMS
A cleaned, joined data layer that brings your ERP, warehouse and transport data together with consistent item, location and supplier codes, owned by you and usable for reporting as well as machine learning.
MLOps: monitoring, drift and retraining
Versioned models, automated retraining, accuracy and drift dashboards, and alerts when a model or a data feed needs attention, so the platform keeps working after launch.
Why supply chain teams work with Moweb.
Building your own platform is a serious commitment. Here is what sits behind us.
Distribution software already shipped
We built EA Foods Limited's system: custom software, IoT and mobile apps for a Tanzanian food distribution business, covering customer management with credit scoring, product and distribution management, and sales team operations with route planning.
Certified security and process
Moweb is ISO 27001:2022 certified and CMMI Level 3 appraised. We sign an NDA before discovery, and your operational and supplier data is handled under those controls.
Honest advice on build versus buy
If a packaged planning suite fits your size and process better, we will say so. We recommend a custom platform when your data, your process or your need to own the result makes it the better choice.
Engagement that fits the work
Fixed cost for a well-defined phase, time and material while use cases are still being proven, or a dedicated team with a three-month minimum, then month to month.
Ways to partner with our team.
Select the model that fits your business needs - a dedicated team, a fixed-cost project, or a flexible time-and-material arrangement.
Dedicated Team
Total control over the project
- Dedicated resources
- Close collaboration
- Scalable team size
- Seamless communication
- Long-term commitment
Fixed Cost
Predefined budget
- Well-defined project scope
- Predictable costs
- Reduced financial risks
- Better budget planning
- Best for fixed requirements
Time & Material
Adaptable to changing needs
- Easily track project progress
- Adjusts project scope or requirements
- Best for projects with uncertain needs
- Allows for incremental development
- Full authority over the project
Supply chains we build AI/ML platforms for.
When to build your own platform and when to buy.
Packaged planning suites such as Kinaxis, Blue Yonder, o9 Solutions and SAP Integrated Business Planning are built for large enterprises with many sites, complex multi-tier networks and the budget and internal teams to run a major implementation. If that describes you and your process is close to how those products work, a suite is often the right answer, and we will tell you so.
A custom AI/ML supply chain platform tends to make more sense for mid-market companies: when your data or process is specific enough that a suite would need heavy configuration anyway, when you only need a few high-value capabilities rather than a full planning suite, when you want to own the models and the intellectual property, or when your ERP is regional, heavily customised or in-house. It can also sit alongside a suite you already run and fill the gaps it leaves.
Either way, the new layer has to work with your existing ERP. We integrate through the ERP's own APIs, database views or file exchange, read the data the models need, and write approved purchase orders, transfers and plans back, so your ERP stays the system of record.
Built with the right tools.
Production-grade technology, chosen to fit your stack and constraints.
Questions about AI/ML Supply Chain Platform.
What teams ask before they start.
Buy when you are a large enterprise whose process fits a suite such as Kinaxis, Blue Yonder, o9 or SAP IBP and you can support a major implementation. Build when you are mid-market, need a few specific capabilities rather than a whole suite, have data or processes a suite would struggle with, or want to own the models and IP. We give you an honest view on which applies after discovery.
Proof
Work we have shipped.
Put your supply chain data to work.
Tell us which decisions you want to make better, whether that is forecasting, replenishment, supplier risk or routing, and which systems hold the data. We will tell you honestly whether to build, buy or combine the two.
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