We measure the layer that decides value.
Every operation that stores sensitive goods knows where its inventory is, how much there is, and what temperature was logged. Almost none know what a specific batch is worth right now. Kryoo reads condition, remaining value, and risk, batch by batch, and turns it into the decision that protects margin.
The thesis
Storage was instrumented over the last decade. Temperature loggers, cold-room sensors, stock counts in the ERP, every layer that got measured became a commodity. The one layer that decides whether a batch earns money or becomes waste, its live condition, was never captured. It lives in the head of whoever last walked the store, and it leaves when they do.
The reason is human. Nobody sustains a data-entry form in a cold room. So condition data has never existed at the batch level, which means the decision that depends on it, what to use first, what to hold, what to stop buying, has always been made from memory. Kryoo exists to capture that layer with almost no new effort, and turn it into a daily instruction the team can act on.
The insight from the floor
Operators already hold both ends of the data. Every delivery creates a goods receipt note, item, supplier, cost, and date. Every discard is weighed and logged before it leaves. What has been missing is the middle: a continuous read of what each batch is worth while it sits in storage. Kryoo connects the receipt to the disposal record and scores everything in between, so perishables get used before they turn rather than counted after they are lost.
How we work
We start narrow and prove value in rupees. A short baseline audit establishes current waste, then a focused pilot scores the highest-loss items daily and reports what was saved against the operator's own waste log. The first version keeps a person in the loop; as graded data accumulates, a computer-vision model learns to read condition from an image, and Kryoo agents take on the routine work with human approval where it counts. We do not claim a model we have not trained.
Where it goes
Food is the wedge because spoilage is visual and the loss is immediate. The same engine reads condition for any goods that degrade with time, temperature, or handling, quick-commerce dark stores, modern-retail fresh, pharma and biologics, and long-distance cold-chain logistics. Kryoo owns no cold rooms and no trucks. Kryoo is the decision layer on top of the assets operators already run, and the record of what happened to each batch, across many operators, is the advantage no single one can build alone.
Team
Umesh Sharma
Builds systems that turn messy physical-world signals into clean, labelled data. MS from Carnegie Mellon University, with production AI systems shipped end to end and a prior venture taken through a fundraise. Leads product, engineering, and the food deployments.
Preeti Sharma
Leads proof-of-concept work for temperature-sensitive pharma and biologics, where condition means potency and compliance. PhD candidate in Bioprocess at the Institute of Chemical Technology (ICT), Mumbai, bringing the scientific rigour these categories demand.
Work with us.
Whether you run a hotel kitchen, a dark store, or a temperature-sensitive supply chain, we would like to understand your waste and show you what Kryoo can recover.