Below is an approximate development road map of significant new features in StockIQ.
These features and functions are subject to be moved up, down, added, removed etc., but this is provided a rough guideline so you know what items are next on the development list in the grand scheme of things. Small items typically are worked in among these larger feature efforts.
This list last updated: April 2026
2026 H1
- Performance Tuning - We are making efforts in several areas to improve application performance for both screen loading, saving, and report generation
- Item-Level ABC Stratification - Allow for more network-wide awareness of a SKUs importance, versus simply at a single site. (By Site Group)
- Item Dashboard - An item dashboard to see all activity on an item, groupable by site.
- Buyer Dashboard - Executive or manager-level view to see buyer activity, such as forecast views, orders placed, alerts reviewed, and more.
- Customer Stratification - Customer Stratification feature allows you to classify and rank your customers, and this becomes visible in the StockIQ application. Use this to know how important certain orders are to be filled, which SKUs you should retain because they are bought by important customers, and more. Use customer rank and stratification to modify SKU stratification, so critical items for critical customers are always available.
- Sales Order Fulfillment Customer Alerting - Building on the customer stratification, a new report for notifying customers about late orders is available, and you can prioritize fulfillment of orders based on FIFO, or on customer rank if necessary.
- Inventory Aging - A customizable inventory aging report is now available for finance to get a read on inventory age and state, which can be used on combination with the Executive Dashboard to get a good, high-level view of inventory state and performance.
2026 H2:
- Integrated AI Assistant - Natural language interaction with applications via LLMs has become the norm, and StockIQ will be riding this wave as well. We will be rolling out an AI assistant via chat interface to make the StockIQ user experience as easy as possible. The agent will be able to answer questions, generate reports, utilize StockIQ's features, and act as an agent for automating actions such as forecast changes and order placement or approval.
- AI/ML: Forecasting - External Data / POS / Leading Indicators - The next big gains in forecast accuracy are from exogenous/additional data series to correlate such as Point-Of-Sale data, customer-on-hand, and customer stores/doors. StockIQ's AI engine will determine the correlation and benefit of additional data sets you can provide, as well as provide some out-of-the-box options, and use these to improve forecast accuracy.
- AI/ML Forecasting - Demand Sensing - Building from our Due To Buy screen, where we evaluate customer purchasing patterns, StockIQ will also be adding Demand Sensing to examine near-term customer purchasing patterns to modify close-in forecasts on a customer-by-customer basis where possible.
- Scenario Planning - Full system-wide scenario planning and saving of scenarios to enable more complete SIOP what-if scenarios
- StockIQ MCP Server - the AI Assistant in StockIQ will be built upon an MCP server to allow it to have the most powerful combination of LLM capabilities, and our well-vetted, deterministic optimization algorithms. This MCP will be available in the same way as our REST API, so that StockIQ's intelligence can be utilized outside the systems as well.
2027 H1:
- Budget-based Purchasing / Open-To-Buy - With inventory levels at all-time highs, organizations are having to prioritize some of their purchasing based on budgets. Additional examples/requests being sought.
- AI/ML: Customer Sentiment Analysis Module - We intend to expand on our AI technology to introduce a new module for customer analysis that extends the Due To Buy screen, to help answer questions such as who is over due to buy, who are you at risk of losing as a customer, and so on.
- AI/ML: Price Elasticity Modeling - AI-based automated Price Elasticity modeling will allow increased forecast accuracy, markdown planning, and improved promotion analysis.