The warehouse is full. The shelf is empty. Somewhere between those two facts sits a planner with a spreadsheet, wondering why possession has proved such a poor substitute for availability. Inventory has a peculiar talent for being abundant in the wrong place. Algo has built a business around that talent.
- Algo connects demand forecasts with decisions about stock, materials and production.
- Its January 2026 purchase of Intuiflow’s maker broadens that connection into manufacturing.
- Customers include Microsoft and JB Hi-Fi; Intuiflow cases add industrial operations such as Flogistix.
- The useful test: can you release working capital while keeping customers supplied?
The forecast was not the first thing to fail
Consider Microsoft’s Amazon channel. Amazon’s published account describes a planning operation dependent on electronic data interchange, or EDI, and manually updated Excel files. Transfers sometimes took six business days or more. When Amazon withdrew EDI connectivity for Microsoft, Algo had to build a different route.
It adopted Amazon’s Selling Partner API, consolidating the feeds and gathering sales daily and inventory weekly. In another partner example, the new reporting identified approximately $2 million in revenue that EDI had missed. That was visibility into existing revenue, rather than new sales manufactured by an algorithm.
The distinction matters. If the observation is late or incomplete, even a sophisticated prediction begins at a disadvantage. Before asking whether the forecast is clever, ask whether the business can see what happened. The least glamorous part of the system may be carrying the most consequential risk.
- 01See demandSales + consumption
- 02Make a planForecasts + constraints
- 03Move stockBuy + build + replenish
Each handoff matters. A fresh signal is useful only if somebody can act on it.
A forecast meets a factory
On January 13, 2026, Algo announced the acquisition of Demand Driven Technologies, the maker of Intuiflow. The deal pairs Algo’s forward-looking demand intelligence with Intuiflow’s consumption-based supply planning. Financial terms were undisclosed.
The distinction is easy to picture. A forecast asks what customers might buy. Consumption-based planning keeps attention on what is actually being used, and what must be replenished. Bring those views together and a planner can consider tomorrow’s demand without allowing yesterday’s assumptions to dictate every materials decision.
“anchor their operations to what customers actually consume”Erik Bush / then CEO and co-founder, Demand Driven Technologies
The acquisition makes strategic sense as a bet on the handoff. Predicting sales is one problem. Deciding which materials to order, which work to schedule and where to place inventory is another. A company can perform the first task beautifully and still leave a production team waiting for parts.
Today’s Intuiflow offering spans demand planning, materials, inventory, sales and operations planning, scheduling and analytics. Its practical ambition is a connected chain of decisions: a changed demand signal should have consequences beyond a revised chart. It should reach the people buying, building and replenishing.
Two numbers, one useful test
Flogistix gives the proposition some arithmetic. Algo’s customer case describes a business struggling with visibility across its network and inconsistent measures between locations. The objective was a common view of inventory that could support better purchasing.
The reported result: inventory value fell from $35 million to $30 million while service level rose from 93% to 98%. A five-percentage-point service improvement accompanied a $5 million inventory reduction. These are customer-case figures published by Algo, rather than a promise about the next implementation.
$35M → $30M
Looking at both numbers prevents a convenient accounting trick. Cutting inventory is easy if you stop worrying about the customer. Raising availability is easy if you buy enough of everything. The interesting work is finding a better relationship between the two.
This suggests a more useful buying question than “How accurate is your AI?” Ask what happens to inventory, service and purchasing behavior together. A demonstration can make a dashboard attractive. A pilot should make a decision better.
Christmas is an unforgiving project manager
The retail version has a deadline. JB Hi-Fi needed a tailored inventory platform before the high-volume Christmas period. Algo’s case describes a rapid deployment combining demand forecasts, replenishment and allocation plans, and collaboration with key vendors. The forecasting models ran on Microsoft Azure.
JB Hi-Fi managing director Cameron Trainor credited Algo with contributing to the retailer’s stock, sales and working-capital targets. The public account is useful because it describes an operating arrangement, not simply a model score: the retailer and trading partners were planning around shared information.
Consumer electronics adds a particularly awkward wrinkle. A new product arrives without the comforting sales history of an old one. Categories sell at different rates. A forecast, a launch plan and a replenishment order must agree sufficiently for stock to arrive while the customer still wants it.
That is where Algo fits: between the data held by retailers and suppliers and the choices those organizations have to make together. Its expertise combines analytical software with implementation and planning support. The human work includes agreeing which figures matter and who changes the plan when those figures move.
Buy the software, or buy the forecast
Algo sells B2B cloud software alongside managed services. Its November 2025 Demand Forecasting Services launch offers a different entry point: customers provide data and receive updated forecasts for use in existing planning or ERP tools. The announcement sets a 90-day target for forecast-ready data.
This is a sensible commercial distinction. Some teams want a planning platform. Others want the forecasting workload handled without taking on another application. The choice depends on where the bottleneck lives: analysis, coordination or execution.
Other offers address adjacent decisions. Price Planner, launched in August 2024, compares pricing scenarios and their implications for demand and inventory. The January 2025 Beye partnership adds generative business intelligence, aiming to let business users explore data without depending on a reporting queue.
In March 2026, Algo announced expanded investment in native Intuiflow for NetSuite. The release describes daily-adjusting buffers and an indented bill-of-materials view that exposes shortages inside nested assemblies. A cheap missing component can hold up an expensive shipment; its purchase price is a poor guide to its importance.
The expansion has financing behind it. Algo announced $15 million in institutional investment in 2020, led by Integrity Growth Partners with The K Fund participating, and $20 million from Vistara Growth in January 2024. Between those announcements, it merged with V Net Solutions in December 2023. Those events describe capital raised and business combinations, rather than a customer’s cost of ownership.
Copy the handoff
Algo operates in a crowded planning market. Netstock is an alternative the company explicitly discusses. ERP planning and the existing spreadsheet are alternatives too. Algo’s positioning rests on breadth across planning and execution, supported by its own implementation team. Buyers should test that combination against their workflow rather than treating a vendor’s comparison table as a verdict.
The lesson a reader can copy is modest. Select one product family. Establish a common record of sales, inventory and replenishment. Agree who acts when a signal changes. Then measure service and stock together. This is an evaluation approach drawn from the cases, not a claim that every company should adopt the same software.
It depends on accessible data, usable replenishment rules and people able to change purchasing decisions. If information cannot leave its silo, or an approved plan never reaches the buyer, another forecast may add little. The productive question is wonderfully unromantic: which decision will be different on Monday?