We work with Supply Chain and Planning Platforms looking to embed AI-driven forecasting and decision-making into core planning modules.
These platforms already manage complex planning workflows across inventory, production and distribution, but often rely on static logic or external tools to generate forecasts and decisions.
SolvedBy.Ai engines integrate via API into your existing architecture, enabling you to introduce advanced forecasting and optimisation capabilities directly into your product, without requiring internal development or changes to your existing workflows and user experience.
What solutions we power in supply chain management platforms
AI Demand Forecasting
Forecast demand, supply, sales and throughput using internal data and external drivers.
SolvedBy.Ai generates forward-looking forecasts across products, locations and time horizons by combining internal operational data with deep exogenous data intelligence. This provides a more accurate and responsive view of how demand and supply will evolve, enabling better planning decisions across the supply chain.
AI Inventory Optimisation
Optimise inventory targets, safety stock and buffer levels based on demand, variability and constraints.
Our AI continuously evaluates demand patterns, variability and operational constraints to determine optimal inventory positions across the network. This improves availability while reducing excess stock and working capital, enabling more efficient and resilient inventory strategies.
AI Stock Control
Generate optimised ordering and replenishment decisions across locations and time horizons.
SolvedBy.Ai translates forecasts into actionable ordering and replenishment decisions, ensuring stock is positioned where and when it is needed. This reduces stock-outs and overstocking while improving responsiveness to changing demand conditions.
AI Resource Allocation
Allocate resources (people and assets) to tasks based on predicted workload, capacity and operational constraints.
By forecasting workload and operational demand, our AI enables more effective allocation of labour, equipment and production capacity. This ensures resources are aligned with expected demand, improving utilisation and reducing inefficiencies across the supply chain.
Forecast demand and key drivers across products, locations and time horizons using AI.
SolvedBy.Ai engines ingest demand, inventory and order data via API, combining it with external drivers to produce forecasts across SKUs, locations and time buckets. Forecasts are generated at the levels required for planning, from product-level demand through to aggregated network views.
2
Decide the outcome
Translate forecasts into optimised orders, allocations and production plans.
Forecasts feed directly into optimisation engines that generate procurement quantities, stock movements and production plans. These decisions are shaped by constraints such as lead times, minimum order quantities, capacity and service level targets.
3
Execute in your platform
Decisions are executed within your existing workflows, systems and approval processes.
Outputs are returned to your platform via API and embedded into planning workflows, where users manage procurement, allocation and production decisions within the tools they already use.
4
Improve
Continuously improve accuracy and decisions using feedback loops and performance data.
Forecast accuracy, stock outcomes and execution performance are continuously fed back into the models, enabling recalibration of both forecasting and optimisation as conditions change.
AI Engines that can be used in supply chain management
The engine powers accurate demand forecasting across products, locations and time horizons using internal and external data.
Resource allocation supports decisions on where to deploy limited resources such as space, equipment, capital, and budget. It evaluates options using demand forecasts and expected return.
Leisure leaders use this to decide which facilities to prioritise, where to invest, and where to scale back, improving utilisation and returns from existing assets rather than expanding capacity unnecessarily.
Price optimisation supports pricing and promotion decisions based on expected demand and utilisation impact. Prices adjust in response to changing conditions rather than reacting late through blanket discounts.
In leisure, this helps optimise membership pricing, day passes, peak and off-peak rates, and promotional offers, protecting revenue while improving utilisation across quieter periods.
Opening hours optimisation evaluates when sites or facilities should operate based on expected demand and financial impact. It identifies which hours contribute value and which create unnecessary cost.
This allows leisure operators to adjust opening times by site or facility, maintaining access when demand exists while reducing exposure during low-usage periods.
Budget forecasting builds budgets based on expected demand rather than fixed assumptions. Forecasts adjust as conditions change, giving finance and operations teams clearer visibility of risk and cost pressure.
For leisure organisations, this improves control, reduces variance, and limits late-year corrective action when demand shifts.
(Best suited to asset-heavy leisure operations)
Predictive maintenance identifies early failure risk in critical assets that affect safety, availability, or customer experience.
In leisure, this applies to equipment such as pool systems, HVAC, rides, lifts, and facility-critical infrastructure, reducing unplanned downtime and protecting service and safety.
Supply chain platforms rely on Forecasting for demand across the network and stock, plus resource scheduling for warehouses, production lines and transport operations. We generate forecasts you can feed into your planning, network design and replenishment engines, and we can help schedule the people and capacity needed to meet those plans.
Yes. For ERP/SCM partners, Inventory AI typically sits behind existing purchasing, replenishment, and planning screens. It can output suggested purchase orders, transfer orders, stocking targets, and exception lists that map to your objects and approval flows.
By embedding advanced forecasting, your platform delivers measurable financial value – not just reporting. This helps you differentiate, increase ARR through premium modules, and improve retention as customers rely on your system for critical operational decisions.
No. Many partners start with a single, high‑value AI (often Forecasting) and then layer on Demand, Scheduling or inventory capabilities as they mature or product‑market fit is proven. The commercial model supports this step‑by‑step adoption.
Yes. Many ERP, inventory and supply chain partners embed Forecasting.AI only, using its outputs to drive their own planning or optimisation modules. You can start with Forecasting and add other AIs later when it makes product and commercial sense.
We work with any platform that uses forecasts to drive decisions. Today our focus is: ERP platforms, Workforce Management (WFM) systems, POS and retail platforms, Restaurant Management Systems, Inventory Management systems and Supply Chain Management suites. If your product would benefit from using world class AI derived forecasts to drive staffing, stock, production or resource scheduling, we are likely a good fit.
Partners typically implement:
UI for operational constraints relevant to the domain (min/max coverage, capacity rules, opening/operating windows, targets)
Feeding additional tasks/work that isn’t captured in the main forecast driver
Displaying the resulting requirement curve (required people/capacity per interval)
Yes. The optimiser is designed to balance availability against cost, including holding cost proxies and cash tied up in inventory. This trade-off is often the key ROI driver for supply chain and finance buyers.
Our offering for all partners uses Forecasting as the foundation, this is our north star and something we are world class at. WFM and Restaurant platforms typically add Demand and Scheduling. ERP and Supply Chain systems tend to focus on Forecasting, Stock/Inventory, and sometimes Resource Scheduling. Inventory platforms use Forecasting plus Stock control / Inventory optimisation. We agree the initial scope with you and can expand to additional AIs over time.
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We commonly support 15‑, 30‑ and 60‑minute intervals for WFM and operational use‑cases, and daily or weekly granularity for supply chain, inventory and financial planning. We can also support bespoke intervals where justified.
TL;DR
SolvedBy.AI enables supply chain planning platforms to embed AI-driven forecasting and optimisation via API. We turn demand and workload signals into inventory targets, replenishment decisions and resource allocations, supporting a forecast → decide → execute → improve loop—while you retain planning workflows, UI and customer ownership.
