Wilfie AI

Wilfie AI is a platform that integrates artificial intelligence into warehouse management, data analysis, workflow automation, and task delegation. Designed for teams involved in live-selling and ecommerce, it brings together multiple AI-driven tools to streamline operational processes and enhance decision-making within a single environment.

The platform offers an AI-powered warehouse management system (AI WMS) that provides visual controls, barcode execution, and inventory tracking across channels. Features include visual locations, SKU context, and support for receiving, dispatch, and bundled shipping flows. This setup is tailored to the needs of live-selling and ecommerce operations, enabling teams to manage warehouse activities with greater visibility and control.

Wilfie AI also includes AI Data capabilities, which convert operational activity into actionable insights through answers, exports, reports, and forecasting signals. Users can search current stock levels and movements, set up scheduled exports and reporting flows, and generate forecasting inputs to inform replenishment decisions. This functionality is aimed at helping organizations make data-driven choices in real time.

For process automation, the platform provides AI Workflows that allow users to automate multi-step tasks across connected applications. Workflows can be run immediately or scheduled for later, and they support pausing and resuming without losing progress. This feature enables teams to automate repeatable work efficiently and maintain continuity in complex operations.

AI Agents are available within Wilfie AI to assist with answering questions, preparing outputs, and ensuring that work progresses smoothly. These agents can be saved for repeated tasks, offer quick help with tasks and summarization, and are integrated with workflow and app contexts to provide relevant assistance.

Wilfie AI is accessible via a mobile app, supporting on-the-go usage for teams that require flexibility in managing operations. The platform emphasizes a modular approach, allowing teams to start with the feature set that best fits their immediate needs and expand usage as requirements evolve.