AI-Powered Facebook Scraping & Moderation Dashboard

@gotucat

Hi, I reviewed your requirement for an AI-powered Facebook scraper that monitors a list of public business pages, scrapes posts and images, then auto-parses each offer into clean fields for moderation. I’ll build a scrape-and-hold queue using robust API/web scraping, store raw text and media, then integrate AI-assisted parsing to extract promotion type, discount details, date, and start/end times, ready for backend workflow. For the rapid moderation dashboard, I’ll implement an ultra-fast web backend that pre-fills image, original text, and extracted tags, with a single “Approve & Publish” action to push to your app database quickly. Let’s discuss here now.

@seefattechnologi

AI EXPERT----------------I believe I can do this project in an efficient and professional manner---------AI-Powered Facebook Scraping & Moderation Dashboard I am highly proficient to work on this project . I am Passionate Python web scrapper /PHP/Full stack developer having rich experience with all the latest technologies with so many successful Tasks. I have some queries to give you accurate time and price Please ping me to get started and provide you great results. Thanks!!!

@ZohaibRoy

⭐⭐⭐⭐⭐ Build Automated Facebook Scraper & Moderation Dashboard for Your App ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project needs and see you're looking for an Automation & AI Expert to build a Facebook Scraper and Moderation Dashboard. Look no further; Zohaib is here to help you! My team has successfully completed over 50 similar projects, and I'm ready to automate your backend pipeline efficiently. I will create a Scrape-and-Hold Queue and a Rapid-Fire Moderation Dashboard, ensuring you maintain full control over your content. ➡️ Why Me? I have 5 years of experience in automation and AI, specializing in web scraping, text parsing, and dashboard development. My skills include Python, BeautifulSoup, and API integration. I also have a strong grip on backend development using Node.js and database management. This makes me well-equipped to handle your project efficiently. ➡️ Let's have a quick chat to discuss your project in detail and I'll show you samples of my previous work. I look forward to our discussion! ➡️ Skills & Experience: ✅ Python ✅ Web Scraping ✅ BeautifulSoup ✅ Scrapy ✅ OpenAI API ✅ Text Processing ✅ Node.js ✅ Django ✅ Database Mapping ✅ PostgreSQL ✅ MongoDB ✅ API Integration Waiting for your response! Best Regards, Zohaib

@ranjika08

With my comprehensive 12+ years of experience in website development, digital marketing, and business automation, I am incredibly well-suited to deliver on the demands of your project. Particularly, my proficiency in Python (BeautifulSoup, Scrapy), mastery of Open AI API/LLM text processing, and talent in developing backend dashboards using Node.js or Django make me an ideal candidate for automating your Facebook scraping and implementing the AI-assisted parsing system you require. In line with your need for an efficient Rapid-Fire Moderation Dashboard, I assure you that my skill in using low-code frameworks like Retool will ensure peak performance under 2 seconds. Additionally, as an SEO expert and proponent of website maintenance and support, I will guarantee that your new platform functions seamlessly - faster load times mean happier users. My knowledge of databases (PostgreSQL/ PostGIS or MongoDB) is also highly applicable and assures quality database mapping/geocoding. Lastly, as someone who firmly believes in staying ahead of the latest tools and trends; I am familiar with the Facebook Graph API, making me adept at navigating a plethora of Facebook pages. By hiring me for this project, not only are you securing a wealth of experience and a tireless work ethic but also peace of mind knowing that even the minutest detail won't be compromised on. Let's revolutionize your backend pipeline together!

@Walkingdreams

As the lead of Walking Dreamz Technologies, I have dedicated over a decade to building robust web and software solutions, especially integrating AI and automation into systems. Our forte lies in developing MERN stack web applications that cater to specific needs, such as the creation of your envisioned automated Facebook scraping system. Through my tailored approach, we aim to not just meet but exceed your expectations for this project. To bolster our capabilities, we're highly skilled in Python (including tools like BeautifulSoup and Scrapy), essential for automated scraping tasks. Moreover, we are like fine wine - age only brings enhancement. Over 300 projects delivered with a 99% positive review rate stand testimony to our caliber. We fear no deadlines and pride ourselves on delivering clean code and predictable results. Choosing us means an end-to-end solution that not only ticks off extracting data and images from your targeted Facebook pages using a robust scraping mechanism like Facebook Graph API or other alternatives but also implementing an AI-assisted text parser and a rapid-fire moderation dashboard with precision. Our backend development skills extend to Node.js and Django along with proficiency in database mapping and geocoding through PostgreSQL/PostGIS or MongoDB. Partnering with us is investing in a dynamic, reliable, hands-on team that values efficient communication, documentation, and long-term support. Let's unleash the potential of AI in your app!

@kishanbwts

You want to automate scraping Facebook pages for food and drink deals, parse the posts with AI to extract key details, and quickly moderate and publish through a simple dashboard. I’ve helped a local deals app automate data collection by building a scraping pipeline with API fallbacks, combined with AI text parsers to classify promotions and dates—cutting manual work by 80%. For your scraper, would you prefer Facebook Graph API first, falling back to scraping only if needed? That can avoid rate limits. For the AI parsing, I suggest a lightweight GPT-4o-mini model to keep parsing fast and cost-effective. The moderation dashboard can be a fast web app displaying each post’s image and parsed info in editable fields with an “Approve & Publish” button triggering the database update immediately. I recommend a minimal Node.js backend with React or Retool for quick UI development. If you want, I can also set up geo-tagging to place promotions precisely on your interactive map. I’m ready to start building your end-to-end pipeline that frees you from manual sourcing while keeping you in full control. Just let me know your preferred stack or APIs, and I’ll get going.

@JustinJcob

I got you! I can build your automated Facebook scrape-and-hold queue, AI parser, and rapid moderation dashboard so your hyper-local food/drink promotions flow from Facebook posts into your app database with full human approval control. I’m ready to handle the scraping/API setup, GPT-4o-mini parsing, image/text review queue, editable fields, and one-click “Approve & Publish” workflow. I’m young, a fast learner, and available 24/7. Get the demo first before you pay. A couple of quick questions: Do you already have an app database/API where approved deals should be published, or should I design that layer too? Also, is your Facebook page list fixed initially, and do you prefer Graph API compliance or a scraping-based fallback where API access is limited? Let’s chat and discuss these answers so I can propose the fastest build path. Kind regards, Haroon Z

@AndrewJSMAN

I've built Facebook page monitoring systems with Graph API and scrapers handling 500+ pages daily, so this is straightforward. I’ll set up a Python-based queue with `facebook-sdk` for Graph API pulls, store raw posts in PostgreSQL with PostGIS for geocoding, then run `gpt-4o-mini` via OpenAI API to parse offers into structured fields—date, time, type, discount. The moderation dashboard will be a Django backend serving a React frontend; each post pre-loads AI-extracted data into editable fields, with a single `POST` to the mobile app’s API for live push in <2s. I’ll include rate-limit handling and error logging to avoid API throttling or failed publishes. I can start immediately. Thanks, Andrii.

@longngoc2307

"AI FACEBOOK SCRAPE-AND-HOLD PIPELINE" — you need reliable offer extraction with fast human approval. ==== Hi - Truong here ==== I’d build the flow as Scrape → Queue → AI Parse → Review → Publish, keeping the raw Facebook post alongside the structured promotion data. That makes AI corrections safe and lets the moderation screen stay fast without hiding the original source. For each post, I’d validate dates, times, offer type and missing fields before publishing, with duplicate detection so repeated Facebook posts do not create repeated promotions. The scraper layer can support API-based access where available and an appropriate scraping method for permitted public sources. Which database/API currently powers the mobile app, and should the first version monitor a fixed page list or support adding pages directly from the dashboard? Looking forward to work with you.

@TechWagger2026

As a seasoned Full-Stack Developer with a relentless drive for innovation and adaptability, I'm confident that my comprehensive skill set aligns perfectly with your requirements for this AI-powered Facebook scraping and moderation project. Not only am I proficient in Python, utilising tools like BeautifulSoup and Scrapy essential for automated scraping, but I'm also well-acquainted with API integration such as the Facebook Graph API that could be beneficial for your project. Additionally, my established experience in backend development using Django, Node.js, and low-code frameworks gives me an edge in creating your rapid-fire moderation dashboard. In tandem with your vision, I will engage lightweight AI parsers like Open AI API or GPT-4o-mini to intelligently extract the pertinent information from scraped text and images. To ensure you can exercise full control over the final content published, I'll develop a streamlined moderation dashboard accessible on a quick-loading web application. The dashboard will present all the scraped information alongside extracted details filled into input fields for easy reviewing and editing if required before just a single click on "Approve & Publish" pushes it live within 2 seconds. Choose me to actualize your project vision proficiently!

@KasjanovaEste

Hello, "FB Scrape Queue + AI Parsing + 2‑Second Moderation Flow" — you need a pipeline that pulls posts, parses offers, and lets you approve/publish instantly. I’ll build a scraper using Graph API where possible (falling back to robust scraping only when needed), push new posts into a queue, run them through an OpenAI/GPT‑4o‑mini parser to extract offer type, discount, dates and times, then surface everything in a fast moderation dashboard. Approve → publish will be a single action with sub‑2‑second latency. I’ve delivered similar automation flows before, including a logistics SaaS where ingestion, AI parsing and human review had to run in one tight loop: https://www.freelancer.com/u/kasjanovaEste . One thing to confirm early is whether your current app database already stores promotions in a structured schema — that determines how the dashboard pushes approved items live. Which promotion fields matter most for your map/calendar: offer type, date/time, or tags? Looking forward to working with you. Fernando

@chiragpipal

⚠️ If you're not happy, you don’t pay. ⚠️ Hi, Thank you for checking my proposal and sharing the detailed project brief. I can build your Facebook Scraper, AI Parser, and Moderation Dashboard using Python and Node.js with a fast, efficient design. I will deliver: • Automated Scraping Queue to monitor and retrieve posts from specified Facebook pages • AI-Assisted Text Parsing to extract promotion types, offers, and timings • Rapid-Fire Moderation Dashboard for quick reviews and approvals • Integration with PostgreSQL for seamless data storage • Real-time updates for instant content visibility You will also receive: • Comprehensive documentation for easy usage • Ongoing support post-launch I am confident I can execute your vision professionally and efficiently. Looking forward to discussing the timeline and next steps. Best regards, Chirag Pipal

@SkillCrafts

I understand you're seeking to automate the aggregation of Facebook food and drink promotions, similar to how I've previously developed automated content pipelines for real-time data feeds, ensuring data integrity and efficient processing. My experience in building robust scraping solutions and implementing AI-driven parsing aligns directly with your need for a "Scrape-and-Hold Queue" and "AI-assisted parsing." My proposed approach involves leveraging Python with libraries like `Scrapy` for efficient and robust Facebook page scraping, handling rate limits and dynamic content effectively. For AI-assisted parsing, I'll integrate a pre-trained Named Entity Recognition (NER) model (e.g., spaCy or a fine-tuned BERT variant) to extract key information like offer type, discount details, dates, and times. This parsed data will then be stored in a PostgreSQL database, forming the basis for your "Rapid-Fire Moderation Dashboard." The dashboard itself will be built using a lightweight framework like Flask or FastAPI, providing an intuitive interface for manual review and approval. Given your focus on maintaining full content control, how do you envision handling edge cases where the AI parser might have lower confidence scores, and would you prefer a tiered approval system based on confidence levels? I’m eager to discuss how we can tailor this solution precisely to your operational needs.

@TheSecondSource

Good day! Automating your hyper-local promotions pipeline calls for a reliable flow from Facebook data collection through AI extraction and human approval, without sacrificing your control over what gets published. We can build that complete scrape-and-hold workflow with a fast moderation layer designed around your app. We can develop the scraping/API integration to monitor your growing list of public business pages, capture posts and images, and send the content through an AI parser to extract promotion type, offer, dates, times, and relevant tags. The moderation dashboard can present the original content alongside pre-filled AI results, allowing quick edits and a single-click approval that writes clean data into your application database. Our stack can combine Python for the ingestion and processing pipeline, OpenAI API for structured extraction, and Django/Node.js or Retool for the moderation interface, with PostgreSQL/PostGIS where mapping and geolocation are required. We’ll build the system modularly, with logging, validation, error handling, and a workflow designed for rapid moderation and dependable publishing.