Our second vertical AI experiment is on the way — this time in project scheduling.
Here's what we've noticed: the AI itself isn't the bottleneck. Any capable LLM today can reason through scheduling logic, dependencies, and constraints just fine. The real friction is in getting your data in and out.
Most people interact with AI through a chat interface. That means exporting your schedule, pasting or uploading it, waiting for a response, then manually pulling the output back into your workflow. Do a few rounds of iteration and it gets old fast. Trying to compare different scenarios or versions? Even worse when everything lives inside a chat thread.
Some scheduling tools offer APIs, but wiring those up to an AI model is a development project in itself — not something most project teams have the bandwidth or budget for.
We're building a tool that removes that friction. Native AI integration with project scheduling — no copy-paste loops, no manual file exchange, no middleware headaches.
More to share soon. In the meantime, here's a one-minute preview — https://www.asvino.com/