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Tarlamapp

Snap a photo of a sick plant and get a clear diagnosis with next steps.

Open live sitetarlam.app
  • SaaS
ClientTarlamApptarlam.app
Who it is for
Farm Advisors & Cooperatives
Type
SaaS
Platforms
Web · iOS & Android · REST API
Status
Live

Project story

  1. Need

    Agricultural advisors and cooperatives in Türkiye look after many fields and farmers at once. Spotting a plant disease usually means a site visit and expert judgement, and by the time advice arrives, the problem may have spread.

  2. Solution

    I built a platform where anyone in the field can photograph a leaf and receive an AI-generated diagnosis with practical steps to take. Advisors also track each field's growth stage, talk to a voice assistant, and receive alerts on WhatsApp. It was developed at Teknopark İzmir (İYTE) as part of a TÜBİTAK programme.

  3. Result

    Advisors can now respond to crop problems quickly from a single photo and keep an eye on many fields and farmers from one place.

What it does

  • AI Leaf Analysis

    Upload a photo of a leaf and get an actionable diagnosis instead of a guess.

  • Growth Stage Tracking

    Follow how each crop is developing based on the weather it has had, field by field.

  • Voice Assistant

    Ask questions by voice while out in the field, without typing on a small screen.

  • WhatsApp Alerts

    Diagnoses and warnings arrive on WhatsApp, where farmers and advisors already are.

  • Plans for Every Team

    Each organisation gets its own workspace with a subscription plan that fits its size.

  • Built to Last

    A thoroughly tested foundation keeps the platform reliable as new features are added.

Step by step

  1. Plant Photo from the Field

  2. AI Leaf Analysis

  3. Actionable Diagnosis

  4. WhatsApp Alert

Tech stack

Technical summary

AI-powered crop diagnosis and field management platform for agricultural advisors and cooperatives in Türkiye. A photo of a plant goes in; an actionable diagnosis comes out. Multi-tenant SaaS with plan-based limits, GDD-based growth tracking, a voice assistant and WhatsApp alerts, built on a framework-independent Clean Architecture core with 655 tests and machine-enforced layer boundaries. Developed at Teknopark İzmir (İYTE) as part of a TÜBİTAK programme.

  • Clean Architecture
  • DDD
  • Multi-tenancy
  • Offline-first
  • Laravel
  • React
  • TypeScript
  • Inertia.js
  • React Native
  • TanStack Query
  • MMKV
  • PostgreSQL
  • Redis
  • Meilisearch
  • RabbitMQ
  • Reverb
  • Yapay Zekâ Teşhisi
  • WhatsApp
  • Sesli Asistan
  • Docker
  • Unit & Feature Testleri
  • Mimari Testleri

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