Build a Custom AI Sales Research Agent (Clay.com Alternative)

@avinashdubeyg209

Claygent is a powerful model to base your custom AI Sales Research Agent on, and I've recently developed a similar tool for analyzing Shopify traffic patterns using BuiltWith API. The critical challenge seems to be accurately estimating order volume through traffic and social engagement data. Have you considered incorporating social scraping tools to enhance data accuracy? Let me know if you're available to discuss a more detailed plan; with the right data points, we could significantly refine lead targeting.

@chiragardeshna

Hi there, Strong alignment with this project comes from experience building AI agents for large-scale data sourcing, enrichment, and automation workflows. Clear understanding of the requirement to develop a Clay-like research agent with lead sourcing, qualification, deep scraping, and multi-step enrichment pipelines. Hands-on expertise with Python, LangChain/LangGraph, scraping tools, and API orchestration ensures scalable processing, clean data pipelines, and reliable outputs. Risk is minimized through modular architecture, retry logic, rate-limit handling, and structured data validation. Available to start immediately happy to discuss approach and share similar work. Recent work: https://www.freelancer.com/u/chiragardeshna Regards Chirag

@AhmadXpert2410

Hi there, I can build a scalable AI-powered “Research & Enrichment” system that automates sourcing, qualification, and deep analysis of 10,000+ e-commerce companies. Using Python with LangChain/LangGraph or CrewAI, I will design an agentic pipeline that integrates search APIs (Serper/BuiltWith), detects Shopify stores, estimates activity levels, and performs structured website scraping for SKU count, sourcing signals, and tech stack identification. The enrichment layer will include a robust multi-step waterfall for email discovery (Apollo → Hunter → Prospeo/Proxycurl) with verification via ZeroBounce or MillionVerifier, ensuring high-quality outputs. Data will be cleaned, deduplicated, and synced into Google Sheets or PostgreSQL, while batch processing (500–1000 leads) will be optimized for performance and cost control with proper API orchestration and retries. You’ll receive a working backend with a simple dashboard to trigger jobs and export results, along with clear documentation on API key rotation and scaling. I’ve built similar AI agent pipelines for large-scale scraping and enrichment, focusing on reliability, structured outputs, and actionable data. Regards, Ahmad

@nafiskabbo30

Just spent time actually understanding your research tool ask - the sourcing location detection, the multi-API email fallback, the batch processing logic. I think, Firecrawl is solid, CrewAI can be overkill, and your biggest cost lever is API rotation strategy. I can do this for you. I know your getting a lot of dms, so wanted to share something more real and personalized instead of some chatgpt haha. Shoot me a message and let’s get started. Kabbo

@Ebendewater

I focus on delivering work that’s done properly, clear, polished, and aligned with exactly what you need. As a new freelancer I’m focused on building my reputation, so I offer competitive rates while putting in extra effort to ensure high quality results, reliable communication, and work I stand behind. My approach to development aligns perfectly with the requirements of your project. I have significant experience with Python, AI, web scraping, and automation - all fundamental aspects needed for this project. With respect to this particular undertaking, I have utilized technologies such as GPT-4o and powerful scraping tools like Firecrawl to scrape important data from websites for deep research. In terms of my familiarity with Shopify and experience in estimating business metrics using traffic data and social engagement, I'm confident that my skills would be essentially useful in developing the Lead Qualification Filters. Additionally, I've worked on a range of e-commerce platforms including WooCommerce and Shopify on complex backends, so building this custom research tool will be well within my competency.

@MaxCodeX

I can build a fast and reliable Python script to extract Google Maps reviews using efficient request-based methods (no browser automation). The script will collect and structure review data such as date, rating, and content, and deliver it in clean JSON format. I can also apply filtering based on your requirements (for example by source or keywords). I focus on writing clean, maintainable code and can deliver a working solution quickly. I can also provide a demo before final delivery.

@snehamehta525

Hello, I can build your AI-powered research and enrichment tool using Python with agentic frameworks, handling lead sourcing, scraping, and multi-step data enrichment. I have experience with large-scale scraping, API integrations, and automated workflows for accurate, structured outputs. I will deliver a scalable system with batch processing, database/Google Sheets sync, and clear documentation.

@harshitaakhade21

Hi! This project is exactly the kind of AI system I enjoy building. I have experience with Python, LLMs, and scraping pipelines, and I can create a scalable research & enrichment agent using tools like LangChain/CrewAI, Serper, and Firecrawl. I’ll handle lead sourcing, qualification, deep research, and email enrichment with a clean output to Google Sheets or PostgreSQL. I’ll also ensure batch processing, cost optimization, and clear documentation. Would love to work on this with you! — Harshita Akhade

@ayushp632

I’m an expert Python/AI developer focused on building scalable agentic workflows for web research, scraping, and enrichment. I can develop a custom Claygent-style system that sources e-commerce brands across the USA, UK, and EU, qualifies Shopify stores, estimates brand traction, extracts SKU and sourcing intelligence from websites, enriches decision-maker contacts with waterfall logic, verifies emails, and syncs clean data into Google Sheets or PostgreSQL. I can deliver a batch-ready backend for 500-1000 leads per run, a simple dashboard to trigger jobs and export CSVs, plus documentation for API key rotation, monitoring, and cost control.”

@huqq

AI & Python Developer with 5+ years of experience in LLM applications (RAG, AI Agents, Dify/LangChain), Python backend (FastAPI, Redis, Docker), and computer vision (OCR, OpenCV, PyTorch). Completed production OCR project with 2-month retainer. Quick response, clear communication, open to long-term collaboration. Let's discuss your project!

@paragparmar254

I have deep experience with langchain and langgraph agents which are the best way to create flexible and complex agents(where complexity is required) an LLM agent would be the best way currently to verify if a page matches your niche requirements. I have extensive scraping experience so I am confident in the technical part. the agentic flow would also help in the email finding part. the output can be done in excel and postgres both. we can also do a simple JS frontend or a prettier react frontend based on the requirement. for the backend api's I'll try to keep it in a organised format such that it would be easier to scale and integrate for the frontend user.

@srdank001

Hello I’ve built AI-driven data pipelines and research agents using Python, LangChain/LangGraph, and LLM APIs for large-scale lead enrichment and automation. For your system, I’d design an agentic pipeline that handles sourcing, filtering, and enrichment in stages: • Lead discovery via Serper/Tavily + niche queries • Qualification checks (Shopify detection, traffic estimation) • Deep scraping using Firecrawl/Jina for SKU count, tech stack, and sourcing clues • Multi-step email enrichment (Apollo → Hunter → Prospeo) with verification via ZeroBounce • Structured output to PostgreSQL or Google Sheets The system would support batch processing (500–1000 leads), API key rotation, and cost control, with a simple dashboard to trigger jobs and export CSVs. This architecture ensures scalable, reliable enrichment with clear data flow and high accuracy. I can also include documentation for easy maintenance and scaling.

@shishirt49

This is exactly the kind of system we’ve built before — AI-powered lead sourcing and enrichment pipelines handling large datasets (10k+ records). We have strong experience with: • Python + AI agents (LangChain / CrewAI) • Large-scale web scraping (Firecrawl, headless browsers) • Search APIs (Serper, Tavily, BuiltWith) • Data enrichment + email waterfall logic (Apollo, Hunter, etc.) • LLMs like GPT-4o for intelligent extraction and classification Approach • Build an agent-based pipeline for sourcing → filtering → deep research • Implement Shopify detection, SKU scraping, and sourcing insights • Multi-step email enrichment + verification • Batch processing (500–1000 leads/run) with retry + rate handling • Output to Google Sheets / PostgreSQL Optional: Simple dashboard to trigger jobs and export data. Why us • Delivered 10+ AI/automation systems • Experience with scalable scraping + enrichment workflows • Focus on clean, usable, and cost-optimized solutions Ready to start immediately and can share relevant work examples in chat.