Picking-week and tonnage calendars so FPOs can sell fruit before harvest
TL;DR Pickweek gives a farmer producer organisation a rolling three-week view of which member plots will be ready to pick and roughly how many tonnes each will yield. The FPO uses it to sell ahead, book crates and trucks, and stagger picking. FPOs and the buyers they supply pay a seasonal fee.
India loses a good chunk of its fruit and vegetables before they even leave the farm. A national study for the food processing ministry found losses of 6.02% to 15.05% across 11 fruits and 4.82% to 11.61% across 14 vegetables, with harvesting and sorting on the farm among the largest single steps[1]. Guava lost 11.58% in farm operations alone. Tomato lost most at sorting and grading, and the study pointed to a shortage of crates and poor roads[1].
Behind those numbers sits a timing problem. When a whole cluster ripens in the same week, crates, pickers and trucks run short, traders cut their offers and fruit waits in the sun. The same study priced all post-harvest losses at ₹1,52,790.42 crore, with fruit making up 19.34% of it[1].
First, the important bit - this is harvest planning and sales information only. Pickweek gives no agronomic prescriptions and doesn't trade produce, so no sector licence applies. Member data falls under the DPDP Act.
An FPO enrols its members' plots for one crop, say mango or tomato. A village field worker logs flowering or fruit-set dates and a quick count on sample trees or rows each week, and satellite greenness for each plot fills the gaps between visits. A model trained on those visits and on each season's actual pickups gives every plot a likely picking week and a tonnage range. The FPO sees a three-week calendar by grade, shares a cleaned version with buyers, and books crates, picking crews and vehicles against it. After each season the forecasts are scored against what was really picked.
I reframed the seed, which pitched AI yield prediction as the fix for harvest loss. A yield number on its own saves nothing, because the loss happens when picking, sorting and selling are out of step. So Pickweek sells the schedule, and the forecast is only the input to it.
The user is the FPO's business manager, who today plans the season from phone calls with members. The FPO pays a per-season fee per crop, which I haven't priced, so treat any figure as an assumption to test. Buyers like processors, exporters and modern-trade sourcing teams are a second payer, because a dated supply forecast lets them plan their own intake. One agri-analytics company sells similar planning to large agribusinesses[2] but publishes no prices, so there's no public benchmark.
The 2022 loss study gave crop-by-crop figures for where in the chain losses happen, which lets you show a buyer a before-and-after[1]. The FPO base has grown too - SFAC alone listed 3,711 FPOs under the 10,000 FPO scheme in February 2025[5]. Satellite crop monitoring is now routine in government, and the national crop forecast centre runs district-level forecasts under its FASAL programme[3].
I found no public figure for what Indian FPOs spend on harvest forecasting. The narrowest number you can stand on is the FPO count, 3,711 under SFAC alone in February 2025[5], each a possible customer for one or two crops. The ₹1,52,790.42 crore loss estimate[1] is adjacent context and not your market, because most of it sits in commodities and steps a calendar can't touch.
One agri-analytics company sells production intelligence covering yield, quality and harvest readiness to enterprises, and says it works with 250+ enterprise clients in 103 countries[2]. The Mahalanobis National Crop Forecast Centre makes district, state and national forecasts for major crops, which serve government planning rather than one FPO's selling[3]. A farm-sensor startup sells sensors with pest and irrigation advice to horticulture growers, and its site shows no harvest forecasting[4]. The gap is a plot-level picking calendar built for an FPO with a few hundred members and priced for one.
| Difficulty | Moderate (40/100) |
| Starting capital | ₹60 L–1.2 Cr |
| Time to launch | 6–9 months |
The software is the easy part. Plot-level forecasts for fruit are noisy, and each crop gives you one season a year to learn from. You need field workers who log counts honestly every week and an FPO manager who actually sells against the calendar. Buyers will trust it only after a season in which the forecasts held.
No sector licence applies to forecasts or planning software, so you only need the baseline.
Building this outside India? The categories above usually have a local equivalent, so check with your own regulator.
Don't trust AI to give agronomic advice or promise yields to buyers. Pickweek only plans the harvest, and every calendar shows ranges, not guarantees.
Want to work out the AI layer for Pickweek? Talk to Yash →
Here's what can go south -
Worth trying if you've worked inside an FPO or a fresh-produce sourcing team and can manage field staff. If you want a pure software business then skip it, because the weekly field visits are the product. Prove first, in one crop belt and one season, that picking-week forecasts land within a week for at least 70% of plots and that one buyer pre-books against them.
Plan for roughly ₹60 L–1.2 Cr, mostly for the software, field workers and the first seasons of data.
No sector licence applies to planning software. You need the usual company registration, GST and DPDP compliance for member data, plus a state marketing licence if you later take commissions on produce.
Yes, wherever smallholder groups sell fruit or vegetables together. Check your local data protection law and agricultural marketing rules before you launch.
The free Pickweek validation kit has the line-by-line capital breakdown, the effort scoring, the data-consent checklist, a 14-day validation sprint with pass/fail targets, a 90-day launch plan, 10 interview questions for FPOs and buyers, and 5 assumptions to test. Download the kit →
Thinking about building Pickweek or something close to it? The make-or-break work is getting picking-week forecasts right in the first season, before buyers stop listening, and I'm happy to think that through with you. If you need a hand, you know where to find me. Talk to Yash →
For illustration only. Names are fictional and ideas hypothetical; sourced facts are real but may be out of date. Nothing here is legal, financial or professional advice, and Yash Khatri is not personally liable for any use of it. Read the full disclaimer.