01/05/2026
We didn’t think much about temperature in the beginning. Our focus was simple. Get the tofu right. Good soybeans. Clean process.
For a while, that felt enough. Until we saw something we couldn’t explain.
Two blocks, made the same way, didn’t always behave the same a few days later. Sometimes the texture felt off. Sometimes shelf life didn’t match expectations. Nothing was obviously broken at our end.
We looked inward first. Beans. Water. Process. Tightened controls. Standardised steps. Repeated batches.
That’s when it clicked. The problem wasn’t just how it was made. It was how it was handled after.
Cold chain infra in the the country is still nascent. It sounds binary. Maintained or broken. In reality, it bends.
A crate waits outside a dark store warehouse waiting for inbound traffic. A chiller in a retail store runs, but not at optimal load. The door opens a thousand times a day. SOPs exist, but context and training across partners vary.
No single failure point. Just small deviations that add up. Most times, not in our direct control.
So we reframed the question. Not where is it going wrong, but where do we have control. We don’t control most of the journey. But we control the beginning.
So we built for that.
Each of our cold room, freezer, and chiller sends real time data. alerts on mobile, loud buzzers on the floor. If temperature shifts, we know. If power fails, automatic backups take over.
We can’t control everything outside our walls, but inside, intention and reality now stay close.
Next stage, we move from monitoring to prediction, using AI/ML to learn patterns and flag early signs of tempe drift before it happens.
