Reddit & News Reply MVP

@diektech

Hi — Elias here from Miami. I understand you're looking to create an MVP that identifies conversations where your web app can be mentioned. This requires a focus on web scraping and the nuanced handling of conversation context. What usually matters most here is ensuring the system can scale effectively as more sources are added. A common issue in systems like this is maintaining accuracy while filtering relevant discussions from noise. The tricky part is usually implementing natural language processing to understand context, which can significantly affect result quality. To address these challenges, I would structure the system to prioritize modularity in both the scraping and analysis components. This ensures that as you expand or modify data sources, the impact on existing functionality is minimized. My experience includes developing similar systems that automate data extraction and analysis, ensuring they remain maintainable and efficient. A few questions to better understand the scope: Q1 – What kind of user roles do you envision interacting with the MVP? Q2 – Are there specific platforms or forums you want to prioritize for conversations? Q3 – How do you foresee handling the volume of data generated from these conversations? Happy to go through the details and suggest the best technical approach. Looking forward to hearing from you.

@ZohaibRoy

⭐⭐⭐⭐⭐ Build an MVP to Hunt Conversations and Boost Brand Awareness ❇️ Hi My Friend, I hope you are doing well. I reviewed your project requirements and see you are looking for an MVP to find conversations for brand building. Look no further; Zohaib is here to help you! My team has successfully completed 50+ projects in this area. I’ll create a crawler to scan Reddit and Google News, rank conversations, and generate replies using AI. This will be done efficiently and within your budget. ➡️ Why Me? I can easily build your MVP to hunt conversations as I have 5 years of experience in web scraping, AI integration, and data analysis. My expertise includes Python, PRAW, BeautifulSoup, and more. Additionally, I have a strong grip on creating user-friendly dashboards and managing data flow effectively. ➡️ Let's have a quick chat to discuss your project in detail. I can show you samples of my previous work and how I can meet your needs. Looking forward to discussing this with you in chat. ➡️ Skills & Experience: ✅ Python Programming ✅ Web Scraping ✅ API Integration ✅ Data Analysis ✅ AI Implementation ✅ Dashboard Design ✅ PRAW ✅ BeautifulSoup ✅ Data Management ✅ User Experience Design ✅ Project Management ✅ Test Automation Waiting for your response! Best Regards, Zohaib

@kamran2012

Hi there, I will deliver your Reddit and News reply MVP: a Python crawler (PRAW + BeautifulSoup) that harvests threads from Reddit and Google News, an AI scoring layer that filters out low-signal posts by relevance and popularity, and a review dashboard where you edit, approve, or reject LLM-drafted replies before they publish back to Reddit. On a similar automation build, keeping the scoring and drafting modules fully decoupled made adding new sources later a one-file task. I will structure yours the same way. Questions: 1) How many subreddits or keyword groups should the crawler monitor at launch? 2) Do you have a preferred hosting setup (VPS, AWS, Railway), or is that my call too? Share your web app URL and a few sample subreddits, and I will scope the scoring criteria tonight. Looking forward to discussing further. Best regards, Kamran

@ludiac

Hi, I have extensive experience building AI-powered automation, RAG systems, web scraping solutions, and LLM workflows using Python, FastAPI, PRAW, BeautifulSoup, Playwright, OpenAI, Anthropic, PostgreSQL, and React. I can deliver a modular MVP that discovers high-value Reddit and Google News discussions, scores them using AI, generates natural, value-driven replies, and provides a secure dashboard where you can review, edit, approve, and publish responses to Reddit. The architecture will be extensible, making it easy to add new sources, scoring models, sentiment analysis, and analytics in future phases. Relevant projects: https://www.freelancer.com/projects/php/Sharepoint-RAG-SQL-GPT-agent/reviews https://www.freelancer.com/projects/php/SQL-RAG-GPT-Agent-with/reviews https://www.freelancer.com/projects/php/OpenAI-Prompts-for-Telco-Support/reviews https://www.freelancer.com/projects/gpt-agent/Data-Analyst-Required/reviews https://www.freelancer.com/projects/python/Python-Data-Analysis-Script-39438040/reviews https://www.freelancer.com/projects/php/Forms-Automation-Wizard/reviews https://www.freelancer.com/projects/selenium/Weekly-Golf-Tee-Time-Booking/reviews I'm ready to start immediately and will provide complete source code, deployment, documentation, and a production-ready MVP that satisfies your acceptance criteria while remaining scalable for future enhancements. Thanks.

@ShaikhAneesa

Hi there, I understand you're looking to build a lean MVP that automatically discovers high-value Reddit discussions and relevant Google News content, ranks them using AI, generates natural promotional replies, and provides a review dashboard before publishing approved responses back to Reddit. My approach is to build a Python-based pipeline using PRAW, BeautifulSoup, and an LLM API to continuously collect discussions, score them based on relevance, popularity, and engagement potential, and generate context-aware replies that add genuine value while maintaining a natural tone. I'll develop a secure web dashboard where you can filter, edit, approve, or reject drafts before publishing to Reddit. The architecture will remain modular, allowing future integration of sentiment analysis, analytics, additional content sources, and more advanced scoring models. The final deliverables will include the complete source code, a deployed MVP accessible through a secure URL, a responsive review dashboard with approval workflows, Reddit publishing integration, comprehensive setup documentation, and a concise handover guide explaining how to extend the crawler, scoring engine, and supported data sources. Could you let me know whether you already have Reddit API credentials and an OpenAI/LLM API available, or should those be included as part of the MVP setup? I'm ready to get started immediately. Warm Regards, Aneesa.

@gotucat

Hi, I reviewed the project and the main goal is a lean MVP that crawls Reddit and Google News to find conversations where your app adds value and drafts helpful replies. I'll implement a modular Python stack using Web Scraping to harvest Reddit threads and Google News, Data Analysis to extract signals, and Data Mining to rank relevance and popularity, with an LLM drafting step for organic replies. A simple dashboard will queue top scores, allow edits, and filter by score, subreddit, or date before posting approved replies back to Reddit. I’ll deliver clean, well-documented code and a secure MVP URL, plus a concise hand-off on extending sources or scoring rules; you’ll get quality, responsiveness, and easy management. Let’s discuss here now.

@SBITServices

Hi, I will develop a lean MVP for your project by implementing a crawler to scan Reddit and Google News for relevant conversations, an AI scoring system to rank conversations, an LLM to generate organic replies, and a dashboard for review and editing. The tech stack will include Python with PRAW, BeautifulSoup, and an OpenAI API. Let's discuss further. Regards, Sai Bhaskar

@Hubready

Hello!, This is James from Hollywood... I read your Reddit & News Reply MVP description carefully, and I understand the core goal: build a lean system that automatically finds relevant conversations where your web app can be mentioned, without turning it into noisy or spammy outreach. I’ve got 15 years of hands-on experience with Python, web scraping, data mining, NLP, API development, and full-stack web apps, so this is a very natural fit. My approach would be to identify high-intent discussions, filter out weak matches, score the best opportunities, and present them in a simple MVP your team can actually use. My practical steps: 1. Define target sources, keywords, and mention rules 2. Build the collection layer with proper rate-limit handling 3. Add NLP filtering to detect real relevance 4. Deliver a lightweight dashboard or export flow for review A few relevant works I’ve built: - a niche SaaS lead-monitoring tool for community mentions - a content discovery dashboard for a marketing team - a Python scraper for trend and keyword tracking - an internal AI-assisted research app for outreach Could you please clarify the following questions to help me better understand the project? 1. Should MVP cover Reddit only first, or Reddit plus news sites? 2. Do you want only discovery, or also suggested reply drafts? 3.

@corpmember29

Hello!! Reddit & News Reply MVP – I have carefully reviewed your requirements, and I have developed similar AI automation, web scraping, LLM, and dashboard solutions before that I can show you. I have 10+ years of experience in Python, OpenAI/LLM integration, web scraping, Reddit API (PRAW), BeautifulSoup, FastAPI, automation, and full-stack development. I can build a modular MVP that scans Reddit and Google News, intelligently ranks conversations using AI, generates natural and value-driven reply drafts, and provides a secure dashboard where you can review, edit, approve, or reject responses before publishing them to Reddit. The architecture will be designed for easy expansion with additional data sources, sentiment analysis, analytics, and advanced scoring models. I will provide 2 years of free ongoing support, complete source code, and assist you from development to successful deployment. We will follow an agile methodology to ensure a transparent development process with regular updates and milestone deliveries. I am available to work in your preferred time zone and will remain committed to your project until you are completely satisfied with the final result. I eagerly await your positive response. Thanks, Christina

@sufyanasmat38

I have experience building AI-powered automation tools using Python, LLM APIs, web scraping, and workflow dashboards. I've developed systems that collect data from multiple sources, rank results with AI, generate contextual content, and provide review interfaces before publishing, with a focus on modular and scalable architecture. For this MVP, I can build a solution that scans Reddit and Google News, scores conversations based on relevance and engagement, generates natural AI-powered replies, and presents everything in a secure dashboard where you can filter, edit, approve, or reject responses before publishing them to Reddit. The architecture will be designed to easily support additional data sources, analytics, and scoring models in future phases. You'll receive clean, well-documented source code, a deployed MVP with setup instructions, and a handover guide explaining how to extend the crawler, AI scoring logic, and dashboard as the platform evolves.

@flapjakc

Hi, Mateo here from Toronto. You need more than a scraper - the scoring and editorial queue are what make this genuinely useful, and that's the part most people underbuild. PRAW with OAuth read/write scope from the start (saves rewiring when you hit publish), SerpAPI or newspaper3k for Google News, OpenAI to score relevance against your app's core value prop and draft replies that sound like they came from someone who actually read the thread. React dashboard on a Node backend - filter by score, subreddit, date, inline edit before you approve. Deployed on a secure URL, API keys in environment variables, modular so new sources plug in without touching the core. I've built OpenAI integrations from scratch and shipped a $4,100 SaaS platform for a US-based client - this scope is clear and I can move fast. What does your web app actually do? That's the only input I need to write a scoring prompt that doesn't miss the target.

@PINESCRIPTERR

Hi, I can build this as a review-first brand-monitoring MVP that finds relevant Reddit and Google News opportunities, scores them, drafts helpful replies, and queues everything in a secure dashboard before anything is published. I’d structure it modularly: Reddit crawler via PRAW, Google News/blog discovery via RSS/search-friendly sources, content normalization, AI relevance/popularity scoring, draft generation, and a web dashboard for review. The dashboard would let you filter by score, subreddit/source, date, keyword, status, and edit/approve/reject each draft. Reddit posting would only happen after manual approval, using authenticated API access and rate-limit-safe publishing. I’d also add safeguards so replies stay useful: brand mention rules, subreddit policy checks where possible, duplicate detection, tone controls, and logs for every crawl, score, edit, and post. The architecture can later support sentiment scoring, analytics, additional forums, and CRM/Slack alerts. Question 1: What is your web app’s niche and ideal customer profile? Question 2: Do you already have an approved Reddit account/app for API posting? Regards, Houssame

@DeyaaAhmed

Hi, I can build your lean MVP for automated brand mention discovery and engagement using Python with PRAW for Reddit crawling and BeautifulSoup for Google News harvesting. I will integrate an LLM to score conversations based on relevance and popularity, generating organic, value-driven reply drafts that avoid spammy tones. The system will feature a secure web dashboard where you can review, edit, and approve top-scoring replies before they are automatically posted back to Reddit, ensuring full control over your brand's voice. You will receive the complete source code, deployed MVP accessible via a secure URL, and a hand-off document outlining how to extend sources or scoring rules. I have extensive experience building AI-driven social listening tools and automation pipelines, ensuring modular architecture for future scalability and reliable API integration. I also offer FREE post-delivery support to monitor initial crawling accuracy, troubleshoot any Reddit API rate limits or posting issues, and assist with minor prompt adjustments during the first month. Let's discuss the project in more details.

@mattafareed4848

Hello Greetings! I can build this modular, lean MVP utilizing Python (PRAW, BeautifulSoup) and OpenAI to flawlessly crawl, score, and draft organic replies. I will deliver the secure web dashboard for queue management (edit/approve/publish to Reddit) along with clean, documented code hitting your exact acceptance criteria. Regards Muhammad

@mayankinnovative

Hello I can build a clean MVP for your Reddit & News Reply system, focusing on reliable automation, relevant content matching, and safe interaction with Reddit. This type of platform requires a balance between automation and control, so the system must be efficient without triggering spam or rate limits. My approach: • Build news aggregation system (RSS/APIs + filtering + storage) • Implement keyword/topic matching for relevant posts • Integrate AI for generating contextual replies • Add queue/worker system for controlled posting (rate limiting) • Implement logging and tracking of replies • Add manual approval option (optional for safety) • Ensure modular and scalable backend (Python-based) Instead of uncontrolled automation, I will design the system with safe limits and structured workflows so it performs reliably without risking account restrictions. Quick questions: 1. Do you want fully automated replies or approval-based posting? 2. Which subreddits or topics are you targeting? 3. Do you already have API access / Reddit app setup? I can deliver a focused MVP that is stable, scalable, and ready for testing. Ready to start immediately. Thanks

@TeraByte26

Hi Sam, I can deliver a Reddit and News Reply MVP in Python, utilizing PRAW, BeautifulSoup, and OpenAI API, within the 250-750 USD budget. I'll provide source code, a deployed MVP, and a hand-off document, meeting the acceptance criteria of finding relevant threads, producing AI replies, and publishing approved replies back to Reddit. Waiting for your response in chat! Best Regards.

@sabaehsan

Greetings, I see that you're looking to create a minimal viable product (MVP) that can identify conversations on Reddit and Google News where your app can be mentioned positively. My approach would start with building a crawler to gather relevant threads and comments. Then, I’d implement an AI scoring system to prioritize conversations based on relevance and popularity. Using a language model, I’d generate concise replies that add real value, ensuring they feel natural rather than promotional. The final touch would be a user-friendly dashboard for you to review and manage these replies easily. I’m confident my experience in Python, web scraping, and natural language processing will help deliver a solution that meets your needs while remaining flexible for future enhancements. Best regards, Saba Ehsan

@trm66614

Hello! I'm excited about the opportunity to work on the Reddit & News Reply MVP project. Developing a solution that hunts for conversations and engages with them meaningfully is a unique challenge I would love to tackle. Your outline for the project is clear and compelling, and I appreciate your focus on brand-building without the spammy approach. The workflow you've described offers a great blueprint for creating an effective MVP that not only finds relevant conversations but also interacts with them authentically. In terms of technology, I propose using Python along with PRAW for Reddit interactions, BeautifulSoup for web scraping Google News, and an OpenAI API for generating high-quality replies. I'll ensure that the architecture is modular, allowing you to easily integrate additional sources and expand scoring metrics as needed. I understand your acceptance criteria and am committed to delivering source code, a deployable MVP, and a clear hand-off document. For clarity and to ensure alignment, How do you envision extending the sourcing or scoring rules in future phases? Looking forward to your thoughts! Best regards, Talha

@Aaleen110

I understand you need an MVP to identify and engage in relevant Reddit and Google News conversations to promote your web app. I have experience building similar automated outreach systems, including a project that increased qualified leads by 25% by surfacing user pain points in niche forums. My approach will involve a Python-based crawler using libraries like `requests` and `BeautifulSoup` for web scraping, specifically targeting Reddit's API and Google News search results. Conversations will be scored using a custom TF-IDF model tuned for your app's keywords, combined with Reddit's upvote/comment count. Reply drafting will be handled by an OpenAI API integration, prompting the LLM with the conversation context and your app's value proposition. What is the desired length and tone for the drafted replies? Ready to start as soon as you confirm scope.