When customers ask us about AI, they're asking: does it actually make your product better? Our answer is yes. We use AI in planning insights, customer support, and how our team builds product.
1. Planning Insights
Vintaflow uses machine learning to support demand forecasting and planning decisions.
Forecasting: Demand forecasts account for product and location history.
Demand attribution: Planning reports show which downstream buyers drive each week's demand.
Planner review: Recommendations remain part of the planning workflow, with people in charge of decisions.
2. Customer Support and Knowledge Base
An in-app AI support assistant helps customers with questions about using Vintaflow, with a route to the Vintaflow team when a person is needed.
Helps users understand the platform and reach the team when a question needs further attention.
Over time, it helps customers self-serve more effectively while reducing friction for complex cases.
3. Agentic Engineering
Agentic coding tools are woven into how product managers and engineers work. Product managers use them to generate UX mockups, API schemas, and user-story specs. Engineers leverage them to accelerate coding tasks—boilerplate, refactoring, unit tests, debugging—while owning design and architecture decisions.
The Bottom Line
AI works best when it solves a real problem. We've focused on three areas where it genuinely creates value: smarter customer decisions, frictionless support, and faster shipping. That's how we're thinking about AI adoption.