AI-Based Competitive Social Media Tracker
Budget: $8 – $15 USD
# AI-Powered Social Media Intelligence & Content Generation Platform
## Project Overview
We are looking for an experienced AI Automation Engineer / AI Developer to build a social media intelligence platform that continuously monitors our competitors, identifies their best-performing content, analyzes why it performed well, and automatically generates improved versions for our own brand.
The goal is not simple content scraping. The goal is to build an AI-powered content research and content creation engine that helps us consistently outperform competitors on LinkedIn and X (Twitter).
---
## Objective
The system should:
1. Monitor selected competitor accounts.
2. Identify high-performing / viral content.
3. Analyze engagement patterns and content structure.
4. Use AI to improve the content.
5. Generate new text, graphics, and posting recommendations.
6. Present everything in a dashboard for approval before publishing.
---
## Platforms
### Phase 1
* LinkedIn
* X (Twitter)
### Phase 2
* Instagram
* Facebook
* YouTube
* Reddit
---
## Core Workflow
### Step 1: Competitor Monitoring
We will provide a list of competitors.
Example:
* Competitor A
* Competitor B
* Competitor C
* Up to 50 competitors
The system should continuously track:
* New posts
* Engagement metrics
* Comments
* Shares/Reposts
* Likes
* Views (where available)
---
### Step 2: Viral Content Detection
The AI should identify:
* Top performing posts
* Fastest growing posts
* Most engaged posts
* Trending content themes
* Content formats producing strongest results
Examples:
* Carousel posts
* Thought leadership posts
* Industry insights
* Founder stories
* AI content
* Case studies
* Contrarian opinions
---
### Step 3: Content Intelligence Analysis
For each successful post, AI should analyze:
#### Content Structure
* Hook
* Body
* CTA
* Formatting style
* Post length
#### Emotional Triggers
* Curiosity
* Authority
* Fear of Missing Out
* Data-driven insights
* Storytelling
* Contrarian viewpoints
#### Engagement Drivers
* Why it worked
* Why people interacted
* Why it was shared
---
### Step 4: AI Content Enhancement Engine
The platform should generate:
#### Option 1
Improved version of the original concept.
#### Option 2
Completely rewritten version.
#### Option 3
Higher-authority version.
#### Option 4
More engaging viral version.
#### Option 5
Version optimized for our specific company and audience.
The output must NOT copy competitor content.
It should generate original content inspired by the underlying topic and engagement patterns.
---
### Step 5: AI Graphic Generation
The system should generate matching visuals.
Examples:
* LinkedIn carousels
* Infographics
* Data graphics
* Quote cards
* Industry insights graphics
* Founder-style visuals
Preferred AI image integrations:
* OpenAI
* Midjourney
* Flux
* Stable Diffusion
The system should automatically create visual concepts and generate ready-to-post graphics.
---
### Step 6: Content Scoring
AI should provide:
* Viral score
* Engagement prediction
* LinkedIn score
* X score
* Brand alignment score
And explain:
* Why this version is expected to perform better.
---
### Step 7: Dashboard
Web dashboard required.
Features:
* Competitor management
* Content feed
* Viral post detection
* AI-generated content suggestions
* Graphic previews
* Approval workflow
* Search
* Filtering
---
## Preferred Tech Stack
Open to suggestions, but preferably:
### Backend
* Python
* FastAPI
### AI
* OpenAI
* Claude
* Gemini
### Workflow Automation
* n8n
* LangGraph
* CrewAI
* Custom agents
### Database
* PostgreSQL
* Supabase
### Frontend
* Next.js
* React
### Hosting
* AWS
* Vercel
* Digital Ocean
---
## Deliverables
### MVP
* Competitor monitoring
* Viral content detection
* AI analysis
* AI content generation
* Dashboard
### Final Version
* Multi-platform monitoring
* Graphic generation
* Content approval workflow
* Scoring engine
* Scalable architecture
---
## Required Experience
Please apply only if you have experience with:
* AI agents
* LLM systems
* Social media automation
* LinkedIn automation
* X/Twitter automation
* OpenAI APIs
* AI workflow tools
* Content intelligence systems
* Data scraping and APIs
Please provide:
1. Similar projects completed.
2. Recommended architecture.
3. Estimated timeline.
4. Fixed-price estimate.
5. Suggested improvements to this concept.
Please when you have read it all, start your post with XYZ so we know you have read it all. All other we will not consider and delete.
We are looking for a long-term technical partner, not just a developer.
## Project Overview
We are looking for an experienced AI Automation Engineer / AI Developer to build a social media intelligence platform that continuously monitors our competitors, identifies their best-performing content, analyzes why it performed well, and automatically generates improved versions for our own brand.
The goal is not simple content scraping. The goal is to build an AI-powered content research and content creation engine that helps us consistently outperform competitors on LinkedIn and X (Twitter).
---
## Objective
The system should:
1. Monitor selected competitor accounts.
2. Identify high-performing / viral content.
3. Analyze engagement patterns and content structure.
4. Use AI to improve the content.
5. Generate new text, graphics, and posting recommendations.
6. Present everything in a dashboard for approval before publishing.
---
## Platforms
### Phase 1
* X (Twitter)
### Phase 2
* YouTube
---
## Core Workflow
### Step 1: Competitor Monitoring
We will provide a list of competitors.
Example:
* Competitor A
* Competitor B
* Competitor C
* Up to 50 competitors
The system should continuously track:
* New posts
* Engagement metrics
* Comments
* Shares/Reposts
* Likes
* Views (where available)
---
### Step 2: Viral Content Detection
The AI should identify:
* Top performing posts
* Fastest growing posts
* Most engaged posts
* Trending content themes
* Content formats producing strongest results
Examples:
* Carousel posts
* Thought leadership posts
* Industry insights
* Founder stories
* AI content
* Case studies
* Contrarian opinions
---
### Step 3: Content Intelligence Analysis
For each successful post, AI should analyze:
#### Content Structure
* Hook
* Body
* CTA
* Formatting style
* Post length
#### Emotional Triggers
* Curiosity
* Authority
* Fear of Missing Out
* Data-driven insights
* Storytelling
* Contrarian viewpoints
#### Engagement Drivers
* Why it worked
* Why people interacted
* Why it was shared
---
### Step 4: AI Content Enhancement Engine
The platform should generate:
#### Option 1
Improved version of the original concept.
#### Option 2
Completely rewritten version.
#### Option 3
Higher-authority version.
#### Option 4
More engaging viral version.
#### Option 5
Version optimized for our specific company and audience.
The output must NOT copy competitor content.
It should generate original content inspired by the underlying topic and engagement patterns.
---
### Step 5: AI Graphic Generation
The system should generate matching visuals.
Examples:
* LinkedIn carousels
* Infographics
* Data graphics
* Quote cards
* Industry insights graphics
* Founder-style visuals
Preferred AI image integrations:
* OpenAI
* Midjourney
* Flux
* Stable Diffusion
The system should automatically create visual concepts and generate ready-to-post graphics.
---
### Step 6: Content Scoring
AI should provide:
* Viral score
* Engagement prediction
* LinkedIn score
* X score
* Brand alignment score
And explain:
* Why this version is expected to perform better.
---
### Step 7: Dashboard
Web dashboard required.
Features:
* Competitor management
* Content feed
* Viral post detection
* AI-generated content suggestions
* Graphic previews
* Approval workflow
* Search
* Filtering
---
## Preferred Tech Stack
Open to suggestions, but preferably:
### Backend
* Python
* FastAPI
### AI
* OpenAI
* Claude
* Gemini
### Workflow Automation
* n8n
* LangGraph
* CrewAI
* Custom agents
### Database
* PostgreSQL
* Supabase
### Frontend
* Next.js
* React
### Hosting
* AWS
* Vercel
* Digital Ocean
---
## Deliverables
### MVP
* Competitor monitoring
* Viral content detection
* AI analysis
* AI content generation
* Dashboard
### Final Version
* Multi-platform monitoring
* Graphic generation
* Content approval workflow
* Scoring engine
* Scalable architecture
---
## Required Experience
Please apply only if you have experience with:
* AI agents
* LLM systems
* Social media automation
* LinkedIn automation
* X/Twitter automation
* OpenAI APIs
* AI workflow tools
* Content intelligence systems
* Data scraping and APIs
Please provide:
1. Similar projects completed.
2. Recommended architecture.
3. Estimated timeline.
4. Fixed-price estimate.
5. Suggested improvements to this concept.
Please when you have read it all, start your post with XYZ so we know you have read it all. All other we will not consider and delete.
We are looking for a long-term technical partner, not just a developer.
Related categories:
Web Scraping
Data Scraping
Data Analysis
Automation
Content Creation
OpenAI
AI Development
AI Agents