Fresh Route Coordinator

For

Market gardeners with a van

Solves

Farmers harvest without knowing who will buy and waste resources driving half empty trucks.

Delivers

Live catalogue, delivery route sheet and sold inventory list

Built in

10 days of creation time, MVP in 2 days

Investment

$5,500 for the MVP, $16,500 for the full product

Run it

Inside your business, or as part of your offer to clients

For market gardeners, turn daily harvest photos and local demand into a live delivery route and sold inventory, and the problem it addresses.

1. Identify crop and grade via photo.
2. Set dynamic pricing based on freshness.
3. Cluster orders by neighbourhood.
4. Generate shortest delivery loop.
5. Handle voice reorders and substitutions.
6. Print or speak route instructions.

What goes in, what comes out

The workflow

1. In
   Start with

   Daily harvest photographs and crop varieties

2. 1

   Capture harvest

3. 2

   Identify and price items

4. 3

   View live orders

5. 4

   Generate route

6. 5

   Pack by stop

7. 6

   Deliver

8. Out
   Finish with

   Live catalogue, delivery route sheet and sold inventory list

AI does the heavy lifting, people stay in charge

Use computer vision to recognise and grade produce from photos. Use routing algorithms to optimise collection and drop off loops. Use voice agents to handle customer reorders and substitutions. A farmer confirms the harvest grade and pricing before the route is generated.

What your team sees

Key screens: Harvest capture, live catalogue, route planner. Use a camera interface for crop identification, a grid view for neighbourhood orders, and a map view for the delivery loop. Display real time inventory levels and order status. In this product, the first view is harvest capture, followed by live catalogue and route planner.

Accounts and administration

Farmer accounts, order history, route versions, approval states, inventory audit trail and delivery status tracking.

Integrations and data access

Local Facebook groups for household invitations and basic payment gateways.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   2 days

   One buyer segment, one recurring use case. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   3 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   5 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will market gardeners with a van use it to solve "farmers harvest without knowing who will buy and waste resources driving half empty trucks"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Run a pilot with one market gardener to prove zero waste and increased revenue compared to wholesale prices.
4. Measure, then decide. Track percentage of harvest sold and reduction in transport costs. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. One market gardener, one neighbourhood, thirty households invited via local group. The farmer photographs six crop types each morning. A single retrieval augmented generation agent writes the catalogue, confirms orders, and prints a route sheet. No app to install. No inventory dashboard. Just a photo, a list, and a drive.

After the MVP. Route density increases and neighbouring farms join the standby network to ensure catalogue fullness.

What the build depends on. Computer vision libraries, routing algorithms and voice generation APIs.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a 15 percent commission on each sale.

Message to test

Turn your morning harvest into a sold inventory before the truck leaves.

Where to find buyers

Local community groups and neighbourhood social media pages.

Lead magnet

A free demonstration of the morning route generation.

The first 30 days

1. Week 1: Set up one farm account and invite thirty households.
2. Week 2: Test the vision model on six crop types.
3. Week 3: Refine pricing and routing logic.
4. Week 4: Analyse waste reduction and order volume.

Paid pilot

Run a pilot with one market gardener to prove zero waste and increased revenue compared to wholesale prices.

Success metrics

Percentage of harvest sold and reduction in transport costs.

Retention and expansion

Repeat orders from households and route density growth.

Why clients would pick it

Network effects between farms and the density of local delivery routes.

Alternatives and positioning

Wholesale markets, grocery stores and manual WhatsApp coordination groups.

Main delivery costs

Compute costs for vision and routing models and the standby network of partner farms.

Delivery radius limits, substitution approval rules and grade rejection thresholds.