Bringing Supply-Chain Clarity to Grain Trading
A data platform that connects farmers, mandis, and processors. The phone calls and paper receipts that used to carry this information are replaced by a live record of stock, price, and quality.
In short: A platform that gives grain traders and processors a live view of stock moving from farm to mandi to warehouse. GrainTech is a platform for grain traders and processors. It digitises procurement, quality grading, and inventory across a network of farms, mandis, and warehouses.
GrainTech is a platform for grain traders and processors. It digitises procurement, quality grading, and inventory across a network of farms, mandis, and warehouses. Operations teams get one record of what stock exists, where it is sitting, and what it is worth. The record updates as things move, not at end of day.
- Procurement data lived in phone calls, WhatsApp photos, and paper receipts. There was no central record.
- Quality grading was manual and inconsistent across mandis. The same lot graded differently at different points, which led to disputes and pricing errors.
- Warehouse inventory counts were days stale. Teams oversold stock they did not have and missed windows for stock that was sitting unsold.
- Field staff carry low-end Android devices on patchy rural networks. The tool had to work offline and sync when connectivity came back.
Offline-First Procurement App
A mobile app for field agents that captures weight, quality grade, and price at the point of purchase. It syncs automatically the moment the device finds a signal.
Automated Quality Scoring
A standardised digital grading rubric with photo capture. The same lot grades the same way at every mandi, which has cut disputes and given traders a consistent quality signal.
Live Inventory Ledger
A real-time inventory ledger that tracks stock from procurement point to warehouse to sale, replacing the end-of-day spreadsheet.
Pricing & Demand Dashboard
A dashboard that gives traders live visibility into regional price trends and warehouse stock levels, so buying decisions are not made on yesterday's data.
Mobile
Backend
Data
Cloud
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Get Free ConsultationFrequently asked questions
How long does a typical project take?
Most MVPs ship in 8 to 12 weeks. Larger products with AI components typically take 12 to 20 weeks. We will give you a realistic timeline once we have had the discovery call.
What does a prototype cost?
Prototypes start at $1,000 for a focused proof of concept. Full MVPs sit between $5,000 and $25,000 depending on complexity, how much AI is involved, and which platforms you need to ship on.
Do you work with early-stage startups?
Yes. About half our clients are pre-seed to Series A. We are used to requirements that move, budgets that are tight, and the occasional pivot.
Can you integrate AI into our existing product?
Yes. We regularly add search, recommendations, automation, and content generation to existing codebases. A full rebuild is rarely required.
What AI models and platforms do you use?
We do not standardise on one vendor. We work with OpenAI GPT, Anthropic Claude, Google Gemini, open-source models like Llama and Mistral, and custom fine-tuned models where the use case calls for it.
How do you handle ongoing maintenance?
We run monthly retainers for post-launch support, monitoring, bug fixes, and feature work. Most clients stay on one after launch.
What if we already have a technical team?
We plug in however fits best. Embedded engineers inside your team, a parallel squad on a separate workstream, or advisory consultants reviewing your roadmap. We work with whatever stack and rhythm your team already uses.