The problem: procurement is a decision, not a record
Agricultural commodity procurement involves continuous decisions around where to buy, when to buy, at what price, what quality to accept, how much inventory to hold and when to move stock.
Yet much of this intelligence remains fragmented across mandi information, brokers, phone calls, WhatsApp conversations, spreadsheets, Tally, physical stock records and individual experience. The data exists — it is simply scattered, and the real decisions still rely on memory and instinct.
Vriti's approach
We are building an intelligence layer that brings procurement, market prices, quality, inventory, logistics and commercial data together. Instead of merely recording transactions, the system helps answer the questions procurement teams face every day:
- Where should we procure today?
- What is our true landed cost?
- How is the market moving?
- Which supplier consistently delivers better quality?
- How much stock do we actually hold?
- What is our exposure if prices move ₹20–₹50 per quintal?
- Should we buy, hold or dispatch?
The result
The outcome is a transition from experience-led procurement to data-assisted procurement — while keeping the trader and procurement team's domain expertise at the centre. The people who know the commodity still decide; the system makes sure they decide with the full picture.
This is particularly powerful because it comes from an actual operational problem rather than an invented AI use case — and the same intelligence-layer pattern extends naturally into adjacent sectors such as automobile and education.