Rhubarb

Rhubarb: Deployed an AI Gardening Assistant to Improve Planting Care & Guidance

Quokka Labs built an AI-powered gardening assistant (Ruby) into Rhubarb's existing platform, connecting garden-specific prompts with relevant context to support personalized plant care guidance.

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Garden planner mobile app preview
Rhubarb garden app preview with Ask Ruby AI assistant
Project Overview

Extending The Platform's Gardening Experience with Personalized AI Assistant

Quokka Labs architected and deployed Ask Ruby, an AI-native assistant that converts complex garden-specific context into personalized plant care guidance for users across the USA and Australia. To address generic gardening advice, we engineered an end-to-end system connecting generative AI models, live weather APIs, custom database queries, and automated climate alerts.

Addressing Contextual Gardening Challenges Through AI Integration

Quokka Labs integrated Ask Ruby with garden-specific context and defined supporting data and automation workflows to address gaps in personalized gardening guidance.

Challenges & Solutions
01 Generic Gardening Advice

Generic gardening advice overlooked individual garden profiles, plant records, and local growing conditions, limiting relevance across different gardening environments.

Solution

Garden-Specific AI Prompts

Quokka Labs configured Ask Ruby’s system prompts to tailor responses using the specific garden associated with each gardening question.

02 Changing Weather and Soil Conditions

Local weather changes and soil conditions influenced planting, watering, and plant protection decisions, requiring more context-specific gardening recommendations.

Solution

Environmental Data Integration

Quokka Labs defined Weather APIs integration workflows and Soil Information to inform gardening recommendations and alerts with relevant environmental conditions.

03 Recurring Plant Care Activities

Recurring watering, planting, and harvesting schedules required timely reminders to help gardeners maintain care routines and respond to changing conditions.

Solution

Automated Gardening Reminders

Quokka Labs designed scheduling workflows for recurring care reminders and weather-related alerts to support timely gardening interventions.

04 Missing Garden-Specific Context

Generating relevant planting guidance required access to garden profiles, plant records, and gardening history beyond individual conversational inputs.

Solution

Contextual Data Retrieval

Quokka Labs designed database retrieval workflows to connect relevant garden and plant records with Ask Ruby’s AI-generated gardening responses.

05 Difficult Conversation Retrieval

Administrators needed to retrieve specific Ask Ruby conversations across users, gardens, dates, and conversation statuses for efficient review.

Solution

Conversation Search and Retrieval

Quokka Labs specified search and filtering workflows to help administrators locate relevant Ask Ruby conversations using garden, user, and date criteria.

About Client

Our Approach

Quokka Labs followed a structured engineering process to integrate contextual AI, connect gardening data, and enhance Rhubarb's existing platform.

Discovery icon

Discovery & Assessment

Our team mapped gardening workflows, plant care scenarios, and system requirements.

  • Gardening workflow mapping
  • Plant care requirements
  • System and data dependency analysis
System Architecture icon

System Architecture

Our team mapped gardening workflows, plant care scenarios, and system requirements.

  • Backend and data modeling
  • API integration planning
  • AI prompt design
AI and Data Integration icon

AI & Data Integration

Our team mapped gardening workflows, plant care scenarios, and system requirements.

  • OpenAI GPT integration
  • Garden-specific system prompts
  • Contextual plant data retrieval
Admin Enhancements icon

Workflow Automation

Our team mapped gardening workflows, plant care scenarios, and system requirements.

  • Recurring gardening task scheduling
  • System requirements
  • Workflows, plant care
Admin Enhancements icon

Admin Enhancements

Our team mapped gardening workflows, plant care scenarios, and system requirements.

  • Our team mapped gardening workflows
  • System requirements
  • Workflows, plant care
The Impact

Measurable Impact of AI in Gardening Efficiency

Quokka Labs integrated context-aware AI and garden-specific data to deliver personalized plant care guidance and simplify everyday gardening decisions.

80%

More Relevant Gardening Guidance

65%

Faster Gardening Query Resolution

75%

Less Manual Garden Tracking

60%

Faster Access to Garden Care Advice

AI Capabilities

Core AI Capabilities Powering Smarter Gardening Experiences

Conversational Intelligence

OpenAI GPT models interpret natural-language gardening queries, plant symptoms, and care requirements to generate contextually relevant responses through LLM-powered conversational solutions.

Recording-to-Test Generation

Context-Aware Prompt Engineering

Garden-specific system prompts incorporate plant varieties, garden profiles, growing conditions, and relevant plant care context into AI responses.

AI-Driven Self-Healing

Retrieval-Augmented Generation (RAG)

Contextual knowledge retrieval grounds AI-generated gardening guidance in relevant horticultural information, plant care knowledge, and growing requirements through RAG development.

Contextual Assertion Generation

Contextual Memory

Contextual data retrieval connects garden profiles, plant records, and care histories with conversational queries, reflecting principles used in context-aware AI chatbot development.

Requirements Traceability Intelligence

Environmental Data Integration

Weather API integration workflows, soil and gardening information incorporate rainfall, temperature variations, and soil conditions into context-aware plant care recommendations.

Test Intent Interpretation

AI Workflow Orchestration

AI workflow orchestration connects language models, prompt routing, contextual data retrieval, and external data sources through AI workflow automation.

Test Intent Interpretation

Background Task Scheduling

Background scheduling workflows support recurring watering, planting, and harvesting routines alongside climate alerts triggered by changing environmental conditions.

Test Intent Interpretation

Contextual Recommendation Generation

Garden-specific context, plant records, and conversational AI inform localized recommendations for planting decisions, seasonal care, and plant health.

Test Intent Interpretation

Ready to Turn Your AI Ambitions into Working Product Experiences?

Bring your product challenges to Quokka Labs. We integrate AI with existing systems, connect relevant data, and engineer intelligent workflows around real user needs.

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Contact Us

letstalk@quokkalabs.com

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+91 9501620330

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+1 469 663 0227

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+31 611024740