I run a small business that does specialized, high-value project work, and I'm trying to build out my outreach in a more systematic way. Right now, finding the right prospects and writing personalized emails takes me hours every day, and I'd rather spend that time on the actual work. I'm looking for someone to help me automate most of it. Here's what I'm trying to build, in plain terms: every morning, a system that pulls a list of qualified prospects from public sources (government bid sites, news feeds, industry publications, Google Alerts), filters them against criteria I'll provide, pulls publicly available contact info for the right people, and drafts personalized emails I can review and send. Everything tracked in a CRM with automatic follow-up reminders. It is not an auto-send tool. I want to read and approve every email before it goes out. The goal is just to shrink my morning research and writing from 4-5 hours down to about 15 minutes of review. A few things that matter to me. The drafts have to feel personal, not templated. I have a specific voice and I care about how my outreach reads — so whoever builds this needs to know prompt engineering well enough to make the Claude (or similar) drafts actually sound like me, not like a chatbot. I want to use the Anthropic API or Claude Code as the engine, and I'm open to your input on the rest of the stack — CRM (HubSpot, Airtable, whatever you'd recommend), hosting, how it's scheduled. Web scraping or public data extraction will be part of this, so if you've worked with Apify, Bright Data, or pulled from government bid portals before, that's a plus. On budget and timing: I'm thinking $1,500 for the build, with a few weeks of tuning after. Open to discussion if your scope makes sense. Looking at 3-4 weeks for the initial build. I'd also want you available afterward for occasional fixes and small additions (paid hourly). I'm happy to share specifics about the vertical, criteria, and sources once we've talked and I know we're a fit. I'll put a basic confidentiality agreement in place before getting into details — nothing scary, just standard. If you're interested, tell me briefly: what you've built that's similar, how you'd approach this one, and what stack you'd recommend. I'd rather read three thoughtful replies than fifty copy-paste ones. Thanks.

Forum Intelligence: Project Brief & Initial Rollout 1. Executive Summary & Objective Forum Intelligence is a beginning as a localized data retrieval, processing, and archiving system designed to scrape public municipal records and state legislative data for public oversight. The immediate objective is to build a functional, highly resilient prototype focused on the Tri-Cities region (Burbank, Glendale, and Pasadena, California). The system will autonomously ingest messy, unstructured municipal data (City Council meeting minutes, agendas, public notices, and legislative PDF text, recorded mp4), clean it, and make it fully searchable and queryable via a localized AI agentic framework. 2. Phase 1 Scope: The Tri-Cities Rollout Th engineer will be responsible for building two primary pillars: A. Resilient Scraper Bots • Target Ingestion: Monitor and pull data from Burbank, Glendale, and Pasadena municipal portals and California legislative feeds. • Data Types: Brittle HTML sites, heavily nested tables, public notices, legislative drafts, and massive unstructured PDF archives. • Requirements: The scraping architecture must be exceptionally robust, utilizing intelligent error handling, retry semantics, and pagination tracking to handle frequent municipal website layout changes without breaking the pipeline. B. Ingestion & Vector Pipeline • Parsing: Extracting clean text from poorly formatted documents and scanned PDFs. • Local RAG (Retrieval-Augmented Generation): Chunking and embedding the data locally into a vector database (e.g., pgvector, Chroma, or Milvus) to enable semantically accurate entity linking and contextual search. 3. Targeted Hardware Stack To ensure maximum data security, strict public oversight integrity, and predictable operational costs, Forum Intelligence is skipping commercial cloud APIs in favor of an on-premise, localized NVIDIA enterprise deployment. The production roadmap aligns precisely with the new computing patterns detailed in NVIDIA’s latest hardware roadmap: • Inference & Token Generation: Running local open-weight frontier models (e.g., Neotron 3 Ultra or Claude/Llama equivalents) optimized for reasoning and long-context tool use. • Compute & Orchestration: The backend infrastructure is architected around NVIDIA’s dedicated agentic architecture, utilizing high-instructions-per-clock (IPC) Vera CPUs paired with Vera Rubin GPUs. • Memory & Storage Processing: Utilizing NVIDIA’s unified memory fabric and data processing units (DPUs) for ultra-low latency context management, KV caching, and fast vector database retrieval. 4. Immediate Milestones for the Engineer 1. Architecture Design: Map out the database schema and local inference ingestion loop. 2. Tri-Cities Scraper Deployment: Write and deploy the initial automated bots for Burbank, Glendale, and Pasadena. 3. Local MVP Pipeline: Demonstrate a local RAG pipeline where a user can query the Tri-Cities scraped records and receive grounded answers with exact source attributions. The above was AI generated from months long conversations with Gemini. The goal is to prove the concept then roll out to LA County, state of CA, and then the country.

Job Title: Automation & AI Developer — Solar Interconnection Workflow System Project Overview: We are a small but fast-growing startup in the Texas solar/energy sector looking for an experienced automation developer to build a multi-portal workflow automation system. This system will eliminate manual data entry, automate government and utility portal submissions, and use AI to analyze and validate photos. This is a paid project with strong potential for ongoing Phase 2 work as the platform grows. What You Will Build: 1. Multi-Portal Web Automation Using Playwright or equivalent browser automation tools you will automate login, navigation, form filling, file uploads, button clicks, page load waiting, and data extraction across multiple web portals including a utility interconnection portal, a project submission portal with existing API access, and a city permit portal. The utility portal specifically requires multi-page form completion, calculate button interactions with 5-15 second page refresh waits, file downloads, and triggering DocuSign email delivery to customers. 2. API Integration One portal has existing API access. You will build direct API calls for data submission and photo uploads to that portal rather than browser automation. 3. AI Photo Analysis — Two Functions First, field photos of electrical equipment must be analyzed using AI vision (Claude, GPT-4V or equivalent) to automatically extract technical data and pre-fill intake forms — eliminating manual data entry. Second, homeowner-submitted photos received via SMS must be automatically analyzed for completeness and quality. If a photo is blurry, incorrect, incomplete, or unusable the system must prompt the homeowner to retake and resubmit before the photo enters the workflow. 4. Automated Customer Notifications Immediately following the utility portal DocuSign email trigger the system must automatically send the homeowner an SMS message instructing them to check their email and sign the DocuSign document. 5. Status Monitoring & Polling The system must automatically check utility portal application statuses on a scheduled basis over a multi-day period and alert the team when a status changes or receives approval. If a DocuSign link expires without being signed the system must reinitiate the email and send the homeowner a new SMS notification automatically. 6. Mobile Application Integration This automation system will need to integrate with a proprietary mobile application currently in development. All work must be built with clean integration in mind from day one — API-ready, well-documented code is required throughout. This system will also need to support incoming and outgoing webhooks with an existing CRM for specific workflow triggers. Thorough documentation is required as a deliverable, not an afterthought. The developer must treat all systems, workflows, and code as strictly confidential. 7. Central Dashboard A simple internal dashboard to view all active jobs, their current stage in the pipeline, status updates, visual graphs or charts for easy review and identification of issues, and any items requiring human attention or intervention. Required Skills: Playwright or Puppeteer browser automation, REST API integration, AI vision API experience (Anthropic Claude or OpenAI), backend development (Python or Node.js), webhook and SMS integration (Twilio or equivalent), scheduled job and polling workflow experience, basic frontend for internal dashboard, experience building systems designed for third party app integration. Important: All code and intellectual property produced under this contract is owned exclusively by the client. A work-for-hire and IP assignment agreement must be signed prior to project commencement. An NDA is also required. Do not apply if you are unwilling to sign these agreements. To Apply: Please share examples of similar automation or RPA projects you have built, specifically any experience with government or utility portal automation, multi-step form automation, or AI vision integration. Include your proposed timeline and fixed-fee project quote.

I’m looking for a developer to help me build a platform that predicts World Cup match results and refines those predictions with real-time data. The project will involve leveraging AI algorithms, machine learning models, historical match data, player stats, and live performance metrics to create accurate match predictions. The platform will need to continuously update and vet these predictions based on new data as the tournament unfolds. If you're passionate about soccer, AI-driven solutions, and real-time systems, this could be an exciting challenge for you. The role will involve developing a scalable platform using technologies like React, Node.js, and possibly Python for data analysis and machine learning. You'll integrate real-time data through APIs to pull match stats and player performance information. AI will be central to the prediction system, with algorithms that analyze historical trends and live data to improve accuracy. You’ll also create a vetting process to ensure predictions remain sharp and reliable as the tournament progresses. The platform must be able to handle high traffic during live events while offering a seamless user experience. I’m looking for someone with experience in AI-based prediction systems, strong web development skills (React, Node.js), and familiarity with working with APIs for real-time data integration. If you have a background in machine learning, real-time data processing, and sports analytics, that would be a major plus.

I'm looking for an experienced Multi-Agent AI Engineer to review and improve an existing AI agent orchestration platform. The ideal candidate will be able to quickly understand a complex codebase, identify architectural and performance bottlenecks, and recommend practical solutions for enhancing the system. This engagement is not focused solely on implementing new features. We are seeking someone who can thoroughly analyze the current architecture, evaluate existing workflows, identify areas for improvement, and provide both strategic and technical recommendations to make the platform more scalable, reliable, and maintainable.

We are looking for an experienced backend developer to help maintain and improve an existing lead data automation platform. The platform currently involves website visitor data files being generated from a third-party pixel/vendor system, delivered through FTP or cloud storage, processed through a structured workflow, enriched through an external data provider/API, and then routed to client-specific destinations such as FTP folders, cloud storage, email delivery, or eventually CRM systems. This is not a brand-new idea-stage project. We already have the business model, workflow logic, vendor relationships, and early architecture defined. We need a reliable developer who can help stabilize, document, and expand the automation. Primary responsibilities may include: Review existing workflow, scripts, AWS Lambda setup, S3 configuration, and file routing logic Help automate ingestion of daily CSV or text files from FTP/cloud folders Match incoming files to the correct client based on tag ID, client ID, file naming rules, or config file Send files to an enrichment provider through API or approved transfer method Retrieve enriched output files and route them to the proper client destination Help build a clean configuration structure for adding new clients Improve error handling, logging, alerts, and operational visibility Document the system clearly so it is not dependent on one developer Maintain strict confidentiality around source code, workflows, vendor details, and client data Useful experience: Python AWS Lambda Amazon S3 EventBridge or scheduled automation FTP/SFTP workflows CSV/data file processing API integrations Webhook workflows CRM integrations such as HubSpot, Salesforce, Zoho, or similar Secure handling of data files Basic DevOps/documentation skills The ideal developer is practical, communicative, organized, and able to work in phases. We are not looking for someone who overcomplicates the system. We need someone who can help us move from a semi-manual/early automation process into a stable, repeatable operating system. Before starting, the developer will need to sign confidentiality and work-product ownership agreements. Please respond with: Examples of similar automation, data pipeline, API, FTP/S3, or CRM integration work Your preferred backend language and cloud stack How you would approach reviewing an existing system before changing it Your availability over the next 2 to 4 weeks Whether you are comfortable signing confidentiality and work-product assignment agreements

Texas Municipality Data Collection Tool Built a custom web scraping and data aggregation system to collect and organize public information from Texas municipal websites. The tool automated data extraction across multiple sources, standardized the results, and exported structured datasets for analysis and reporting. Technologies: React, Node.js, Web Scraping, APIs, Data Processing, MongoDB/PostgreSQL

I am real estate investor in need of help to set up and maintain a data scrap app for lead research. App would download PDFs and scrap data, then dump into a spreadsheet. Once data is scraped and in excel, then app needs to go to 4 differnet platforms to process and optimize the leads. Looking for long term help maintaining the programs.

**Title:** Build Automated Weekly Business Listing Scraper + Email Digest **Budget:** $100–$200 (fixed price) **Overview:** I'm an active buyer looking to acquire a small business in the $800K–$3M range. I need a simple automated system that scrapes business-for-sale listings from multiple websites weekly, filters them by my criteria, and emails me a clean digest every Monday morning. **Sources to scrape (at minimum):** - BizBuySell.com (Wisconsin + Minnesota + broader Midwest filter) - Sunbelt Business Advisors (sunbeltnetwork.com) - Lake Country Advisors - BusinessBroker.net (Wisconsin/Midwest) - BizQuest.com (Wisconsin/Midwest) **Filter criteria:** - Location: Milwaukee area first, Wisconsin/Minnesota second, Midwest broadly - Industries: Manufacturing, Landscaping, Trades (HVAC, plumbing, electrical, similar) - Seller's Discretionary Earnings (SDE): $200K–$800K - Asking price: $800K–$3M - Exclude: Restaurants, bars, franchises, retail - Established businesses only (no startups) **Email digest format (every Monday ~8am CT):** - Business name/title - Asking price - SDE or cash flow (if listed) - Location - Brief description (1-2 sentences) - Direct link to listing - Source site - Date first seen (flag NEW listings vs. ones already sent) **Technical requirements:** - Deployed on a cloud server (e.g. DigitalOcean, AWS, Heroku) — I should NOT need to run anything on my own computer - Scheduled to run automatically every week with no intervention from me - Email sent to my Gmail address - Duplicate suppression — don't re-send listings I've already received - Basic error handling so it doesn't silently fail - Simple documentation so another developer could maintain it if needed **Deliverables:** 1. Working scraper deployed and running on cloud infrastructure 2. First test email sent to confirm it works 3. Brief setup doc explaining what was built and how to update criteria in the future **Nice to have (bonus):** - A simple way for me to update search criteria without needing a developer (e.g. a config file or Google Sheet I can edit) - Alerts if a listing matches ALL criteria especially well (e.g. SDE over $500K) **About me:** I'm a serious, qualified buyer — not a casual browser. I've been evaluating acquisitions for over a year. I want this tool to surface deals efficiently so I can focus my time on outreach and diligence. Please include in your proposal: - Which sites you've successfully scraped before - Your preferred tech stack for this project - Estimated timeline - How you'll handle sites that block scrapers

Title: Backend Developer — AI Data Pipeline, Vector DB & Real-Time Push API Post: We are building an automated backend system that continuously crawls public web sources, processes and indexes content using AI, and delivers updates via webhooks. Looking for someone who has built this type of system before and can move fast. NDA required before project details are shared. What you’ll build: • Web crawler network —. • AI processing pipeline — cleans, deduplicates, chunks, and embeds ingested content into a vector database using an LLM embedding model. Quality scoring and incremental updates required. • Push API — monitors for significant content changes and delivers updates via webhook endpoints automatically. Includes configurable push schedules per subscriber, REST query endpoint, API key authentication, and token usage tracking per key. Tech stack (flexible — use what you know best): • Python (FastAPI) or Node.js • Any vector DB — Pinecone, ChromaDB, Supabase • Any LLM API — Anthropic or OpenAI • Any scheduler — n8n, APScheduler, cron • Redis for queue management • Railway, Render, or AWS for deployment Requirements: • NDA signed before kickoff — non-negotiable • Must have built RAG pipelines or vector DB systems in production — not tutorials • Must have experience with web crawlers and scheduled job pipelines • Must have experience with webhook delivery systems • GitHub or portfolio showing relevant deployed work required • 95%+ Job Success Score preferred • Individual contractors only — no agencies To apply include: • Example of a similar system you’ve built — web crawler, RAG pipeline, or push notification API • Your preferred stack for this type of build • Brief technical approach in 3–5 sentences • Hourly rate and availability to start Budget: $50–$80/hr Timeline: 3 weeks — focused sprint with daily check-ins