OpenClaw AI Lead-Generation Agent -- 2
Budget: $250 – $750 AUD
AI-Powered Packaging Lead Generation & Outreach Agent
Overview
We are looking for a developer to build an AI agent pipeline that automatically identifies, qualifies, and reaches out to potential customers in the hospitality and food industry based on their packaging usage. The agent will research businesses, analyse their packaging via website menus and images, score them as leads, and send personalised cold emails.
Business Context
We are a packaging supplier that sources products direct from manufacturing partners in China and stores them locally in Australia. We specialise in high-volume consumable lines — primarily packaging and disposables — for businesses in hospitality, food production, bakeries, and retail.
Our ideal customer is a business doing consistent, high volume on core packaging lines (e.g. burger boxes, bags, coffee cups, greaseproof paper, snack boxes) who is currently overpaying through a local distributor.
What We Need Built
A fully automated agent pipeline with the following stages:
Stage 1 — Lead Scraping
Integrate with a lead scraping tool (e.g. Lobstr.io, Outscraper, or Scrap.io) via API
Pull business name, website URL, phone number and email address
Target industries: cafes, restaurants, bakeries, fast food, food production, hospitality
Target location: Australia (initially Perth, WA)
Output: structured list of leads with contact details
Stage 2 — Website & Menu Analysis
Agent visits each business website
Reads and analyses the menu or product pages
Identifies what packaging they are likely using based on the food/products they sell
Examples: burger boxes, coffee cups, paper bags, greaseproof, snack boxes, takeaway containers
Output: list of likely packaging lines per business
Stage 3 — Google Images Analysis
Agent searches Google Images for each business
Uses computer vision (via OpenAI Vision or Claude API) to identify packaging visible in food photos
Confirms and adds to the packaging profile built in Stage 2
Output: confirmed packaging types with confidence score
Stage 4 — Lead Scoring & Ranking
Score each lead based on:
Number of core packaging lines identified
Estimated volume (based on business size, number of locations, menu size)
Match to our target product lines
Rank leads from highest to lowest priority
Filter out low-volume or poor-fit businesses
Output: ranked lead list with score and packaging summary per business
Stage 5 — Personalised Email Generation & Sending
Generate a personalised cold email for each qualified lead
Email should reference the specific packaging lines identified for that business
Follow a provided email template (we will supply the copy and structure)
Integrate with an email sending platform (e.g. Instantly.ai, Smartlead, or similar)
Output: emails sent to ranked leads, results logged
Technology Requirements
AI Agent Framework: OpenClaw (preferred) — open-source agent framework
Vision/LLM: OpenAI Vision API or Claude API for image analysis and content generation
Email Platform: Instantly.ai or Smartlead (we have an account — developer to integrate)
Scraping Integration: API connection to Lobstr.io or Outscraper
Language: Python preferred
Hosting: Agent should be able to run on a schedule (daily or weekly)
All credentials and API keys will be supplied by us
Deliverables
Fully functional agent pipeline covering all 5 stages above
Simple dashboard or log showing leads scraped, scored, and emailed
Ability for us to review and approve leads before emails are sent (optional approval step)
Documentation explaining how to run, update, and maintain the agent
2 weeks post-launch support for bug fixes
Out of Scope
We do not need a CRM built — a simple spreadsheet or Airtable output is fine
We do not need a full website or customer portal
Social media outreach is not required at this stage
Budget & Timeline
Please provide a fixed-price quote for the full build
Indicative timeline: we would like this live within 4–6 weeks
Milestone-based payments preferred (e.g. 50% upfront, 50% on delivery)
What We're Looking For in a Developer
Experience building AI agents or automation pipelines
Familiarity with OpenAI or Claude APIs (vision and text)
Experience with web scraping and lead enrichment tools
Strong communication — we are not technical so plain English updates are important
Portfolio or examples of similar projects highly regarded
To Apply
Please respond with:
Your relevant experience and any similar projects you have built
Your fixed price quote and proposed timeline
Any questions or clarifications you need before quoting
Overview
We are looking for a developer to build an AI agent pipeline that automatically identifies, qualifies, and reaches out to potential customers in the hospitality and food industry based on their packaging usage. The agent will research businesses, analyse their packaging via website menus and images, score them as leads, and send personalised cold emails.
Business Context
We are a packaging supplier that sources products direct from manufacturing partners in China and stores them locally in Australia. We specialise in high-volume consumable lines — primarily packaging and disposables — for businesses in hospitality, food production, bakeries, and retail.
Our ideal customer is a business doing consistent, high volume on core packaging lines (e.g. burger boxes, bags, coffee cups, greaseproof paper, snack boxes) who is currently overpaying through a local distributor.
What We Need Built
A fully automated agent pipeline with the following stages:
Stage 1 — Lead Scraping
Integrate with a lead scraping tool (e.g. Lobstr.io, Outscraper, or Scrap.io) via API
Pull business name, website URL, phone number and email address
Target industries: cafes, restaurants, bakeries, fast food, food production, hospitality
Target location: Australia (initially Perth, WA)
Output: structured list of leads with contact details
Stage 2 — Website & Menu Analysis
Agent visits each business website
Reads and analyses the menu or product pages
Identifies what packaging they are likely using based on the food/products they sell
Examples: burger boxes, coffee cups, paper bags, greaseproof, snack boxes, takeaway containers
Output: list of likely packaging lines per business
Stage 3 — Google Images Analysis
Agent searches Google Images for each business
Uses computer vision (via OpenAI Vision or Claude API) to identify packaging visible in food photos
Confirms and adds to the packaging profile built in Stage 2
Output: confirmed packaging types with confidence score
Stage 4 — Lead Scoring & Ranking
Score each lead based on:
Number of core packaging lines identified
Estimated volume (based on business size, number of locations, menu size)
Match to our target product lines
Rank leads from highest to lowest priority
Filter out low-volume or poor-fit businesses
Output: ranked lead list with score and packaging summary per business
Stage 5 — Personalised Email Generation & Sending
Generate a personalised cold email for each qualified lead
Email should reference the specific packaging lines identified for that business
Follow a provided email template (we will supply the copy and structure)
Integrate with an email sending platform (e.g. Instantly.ai, Smartlead, or similar)
Output: emails sent to ranked leads, results logged
Technology Requirements
AI Agent Framework: OpenClaw (preferred) — open-source agent framework
Vision/LLM: OpenAI Vision API or Claude API for image analysis and content generation
Email Platform: Instantly.ai or Smartlead (we have an account — developer to integrate)
Scraping Integration: API connection to Lobstr.io or Outscraper
Language: Python preferred
Hosting: Agent should be able to run on a schedule (daily or weekly)
All credentials and API keys will be supplied by us
Deliverables
Fully functional agent pipeline covering all 5 stages above
Simple dashboard or log showing leads scraped, scored, and emailed
Ability for us to review and approve leads before emails are sent (optional approval step)
Documentation explaining how to run, update, and maintain the agent
2 weeks post-launch support for bug fixes
Out of Scope
We do not need a CRM built — a simple spreadsheet or Airtable output is fine
We do not need a full website or customer portal
Social media outreach is not required at this stage
Budget & Timeline
Please provide a fixed-price quote for the full build
Indicative timeline: we would like this live within 4–6 weeks
Milestone-based payments preferred (e.g. 50% upfront, 50% on delivery)
What We're Looking For in a Developer
Experience building AI agents or automation pipelines
Familiarity with OpenAI or Claude APIs (vision and text)
Experience with web scraping and lead enrichment tools
Strong communication — we are not technical so plain English updates are important
Portfolio or examples of similar projects highly regarded
To Apply
Please respond with:
Your relevant experience and any similar projects you have built
Your fixed price quote and proposed timeline
Any questions or clarifications you need before quoting