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Fajar Rizwan's avatar
Fajar Rizwan
Lahore, Pakistan
CS student & designer automating the future with AI.
New to Contra
CS student & designer automating the future with AI.
Cover image for Taking corporate email automation beyond
Taking corporate email automation beyond basic template generation. 🚀 I just open-sourced a new project: Autonomous Cold Email & Inbound Replier Agent! This is a modular, production-ready system built completely in pure Python using CrewAI for multi-agent orchestration and Streamlit for a clean, modern interactive UI. As shown in image_ea414f.png, the system moves away from single-prompt generation and splits the operational workload into specialized, sequential steps to ensure high-quality enterprise triage: Dynamic Context Parsing: Ingests dynamic company names, specific roles, and product offerings to craft completely personalized pitch assets based on an internal knowledge base. Multi-Agent Orchestration: Uses a CrewAI sequential flow to separate analysis from execution. A Triage Officer handles data categorization while a Business Correspondent handles context-aware drafting. 100% Free-Tier & Cost Compliance: Powered entirely by high-performance models via free-tier API orchestration (utilizing gemini-2.5-flash via Google AI Studio and Groq Cloud AI as a high-speed secondary model). Interactive UI Safety: Features a polished Streamlit interface (onee.py (http://onee.py)) to monitor active server queues and act as a human-in-the-loop gatekeeper to approve drafts before they go live. The repository is modularly structured, completely production-ready, and optimized with strict exception handling to respect rate limits safely. 🔗 Check out the code here: https://github.com/26FajarRizwan/Cold_Email_Replier_Agent #CrewAI #Streamlit #AIEngineering #Python #GenerativeAI #LLMs #OpenSource #Automation #GoogleGemini
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Cover image for 🎮 Level Up: Built a
🎮 Level Up: Built a Multi-Agent AI Game Designer with CrewAI (https://www.linkedin.com/company/getcrewai/) & Groq (https://www.linkedin.com/company/groq/)! 🚀 I'm thrilled to share my latest projecta modular hashtag#AI (https://www.linkedin.com/search/results/all/?keywords=%23ai&origin=HASH_TAG_FROM_FEED) Agent system designed to transform a simple text idea into a full, production-ready Game Design Document (GDD)! 🕹️🤖 As game development gets more complex, brainstorming core mechanics, balance, and narrative loops manually can take days. I built this automation agent to instantly structure wild game ideas into comprehensive design blueprints. 🛠️ How It Works: Dynamic Terminal Prompting: Captures unique, raw gameplay ideas directly from user input via the terminal. AI Game Designer Agent: Powered by Groq’s lightning-fast Llama-3.3-70b-versatile model, it acts as a veteran designer with 10+ years of AAA experience. Custom Stability Patch: Implemented a robust dynamic litellm execution patch to strip out incompatible caching fields, ensuring 100% crash-free API calls. Structured GDD Output: Automatically generates core gameplay loops, combat systems, character arcs, and world-building documentation. 🏗️ Modular Architecture & Tech Stack: Framework: CrewAI (https://www.linkedin.com/company/crewai-inc/) (Multi-Agent Architecture) Inference Engine: Groq (https://www.linkedin.com/company/groq/) API Cloud LLM: Llama (https://www.linkedin.com/company/ai-deepseek/)-3.3-70b-versatile Environment Management: Python (https://www.linkedin.com/company/learn-python-programming/) hashtag#python (https://www.linkedin.com/search/results/all/?keywords=%23python&origin=HASH_TAG_FROM_FEED)-hashtag#dotenv (https://www.linkedin.com/search/results/all/?keywords=%23dotenv&origin=HASH_TAG_FROM_FEED) & hashtag#strict (https://www.linkedin.com/search/results/all/?keywords=%23strict&origin=HASH_TAG_FROM_FEED) .hashtag#gitignore (https://www.linkedin.com/search/results/all/?keywords=%23gitignore&origin=HASH_TAG_FROM_FEED) protocol to ensure zero leakage of private hashtag#API (https://www.linkedin.com/search/results/all/?keywords=%23api&origin=HASH_TAG_FROM_FEED) credentials. By separating my automation projects into clean, isolated ecosystems, I'm building a highly scalable portfolio of production-grade AI tools. 📂 Check out the GitHub Repository here: https://lnkd.in/dFecvgBc (https://lnkd.in/dFecvgBc)What kind of game would you ask this agent to design first? Let's connect and discuss the power of fast inference in creative automation! 👇 hashtag#AI (https://www.linkedin.com/search/results/all/?keywords=%23ai&origin=HASH_TAG_FROM_FEED) hashtag#GenerativeAI (https://www.linkedin.com/search/results/all/?keywords=%23generativeai&origin=HASH_TAG_FROM_FEED) hashtag#CrewAI (https://www.linkedin.com/search/results/all/?keywords=%23crewai&origin=HASH_TAG_FROM_FEED) hashtag#Groq (https://www.linkedin.com/search/results/all/?keywords=%23groq&origin=HASH_TAG_FROM_FEED) hashtag#Llama3 (https://www.linkedin.com/search/results/all/?keywords=%23llama3&origin=HASH_TAG_FROM_FEED) hashtag#GameDesign (https://www.linkedin.com/search/results/all/?keywords=%23gamedesign&origin=HASH_TAG_FROM_FEED) hashtag#Python (https://www.linkedin.com/search/results/all/?keywords=%23python&origin=HASH_TAG_FROM_FEED) hashtag#Automation (https://www.linkedin.com/search/results/all/?keywords=%23automation&origin=HASH_TAG_FROM_FEED) hashtag#ArtificialIntelligence (https://www.linkedin.com/search/results/all/?keywords=%23artificialintelligence&origin=HASH_TAG_FROM_FEED) hashtag#SoftwareEngineering (https://www.linkedin.com/search/results/all/?keywords=%23softwareengineering&origin=HASH_TAG_FROM_FEED)
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Cover image for Just Built: A Multi-Agent AI
Just Built: A Multi-Agent AI CV/Resume Tailor using CrewAI & Google Gemini 2.5 Flash! 📝 Huge thanks to Skill2Success for giving me this platform and helping me in making these type of projects and also Zarmina Sanam for guiding me in best way!!!! Job hunting is tough, but tailoring your resume for every single job description shouldn't take hours. To solve this real-world problem, I built an automated multi-agent system that optimizes resumes for ATS algorithms in seconds! 🛠️ How it works: Local PDF Extraction: Uses pypdf to read the candidate's resume directly via file paths (supporting drag-and-drop inputs). ATS Specialist Agent: Analyzes the target Job Description (JD), evaluates keyword density, and flags technical or formatting gaps. Executive Resume Writer Agent: Automatically re-architects and rewrites resume bullet points using the impact-driven STAR methodology without fabricating skills. 🏗️ Tech Stack: Orchestration: CrewAI Framework LLM Backbone: Google Gemini 2.5 Flash (Ultra-fast & accurate processing) Security: strict .gitignore configuration to safeguard personal API credentials. This project isolates production environment workflows perfectly and delivers tailored markdown resumes ready for corporate submissions! 📂 Check out the GitHub Repository here: https://lnkd.in/dvT4BK2S Let's connect and discuss building autonomous agents for productivity workflows! 👇
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Cover image for  rule-based chatbot built in Python
 rule-based chatbot built in Python that replies to greetings, questions, and casual conversation using keyword matching — no AI/ML involved. Includes an advanced version with jokes, time/date, and emotion responses, plus a bonus HTML/CSS/JS chat UI. CodeAlpha Python Internship Task 4.
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Ahmad Saddiqui's avatar
Ahmad Saddiqui
Lahore, Pakistan
Senior AI Engineer | AI Agents, Automation & SaaS Solutions
New to Contra
Senior AI Engineer | AI Agents, Automation & SaaS Solutions
Cover image for Full Project Description NAOO is a
Full Project Description NAOO is a React Native mobile application with social, marketplace, and location-based product features. I worked on multiple core modules across the app, focusing on clean mobile implementation, analytics tracking, user behavior events, and improving the reliability of important user flows. My work involved implementing and refining analytics events across the application using tools such as Firebase Analytics, CleverTap, and Firehose. This included tracking user sessions, post impressions, post interactions, search behavior, profile activity, map usage, chat actions, invite flows, and wallet milestone events. I also worked with React Native modules such as feed screens, user profiles, map-based offers, search results, chat flows, wallet activity, and onboarding-related improvements. The goal was to make the app easier to measure, debug, and optimize from a product and growth perspective. The project required close attention to event consistency, session handling, screen-level tracking, and reliable data flow across multiple app modules. My Role React Native Developer I contributed to mobile app development, UI UX, product analytics implementation, event tracking architecture, and feature-level improvements across the NAOO mobile application.
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Cover image for 1. Executive Summary Auto Social
1. Executive Summary Auto Social Publishing is a SaaS automation platform that allows businesses and agencies to publish social media content at scale using Excel spreadsheets. The platform enforces admin approvals, prevents duplicate posting, provides real‑time execution visibility, and tracks usage‑based costs for transparent billing. It is built for operational teams and agencies that require control, reliability, auditability, and predictable pricing when automating social media workflows. 2. What This Automation Is A hosted SaaS system that: Converts Excel files into social media posts Publishes to Instagram and Facebook using Ayrshare Enforces approval‑based access control Streams real‑time execution logs Tracks per‑client usage and cost
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Cover image for Proposals & Contract Automation is
Proposals & Contract Automation is a fully hosted SaaS platform designed to streamline the creation, delivery, tracking, and signing of proposals and contracts. It replaces fragmented workflows involving documents, emails, follow-ups, and manual approvals with a unified, AI- assisted system. The platform reduces sales cycle time, improves close rates, and provides a professional client experience through automated workflows, secure public access links, and centralized tracking. This automation is an end-to-end deal-to-signature system that enables businesses to: • Create proposals and contracts from templates • Use AI to assist content drafting • Send documents securely to clients • Track acceptance, rejection, and signatures • Automate reminders and expirations • Manage users and approvals at scale
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Cover image for RagChatBot is a fully hosted
RagChatBot is a fully hosted AI Knowledge Assistant that allows businesses to convert their internal documents (PDFs, policies, FAQs, guides) into an intelligent, customer‑facing chatbot. The system uses Retrieval‑Augmented Generation (RAG), meaning the AI answers questions only from company‑provided data, with traceable citations. This removes hallucinations, improves trust, and makes AI responses audit‑friendly. The product is delivered as a SaaS platform. Clients do not install anything locally. They sign up, upload documents, and deploy a chat widget on their website within minutes This automation replaces: - Manual knowledge lookup by staff - Static FAQ pages - Repetitive customer support conversations RagChatBot acts as a 24/7 AI employee that understands company knowledge and answers questions consistently and instantly
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Saud Saleem's avatar
Saud Saleem
proLahore, Pakistan
Top Rated Plus Freelancer & Top 1% Talent
$5k+
Earned
2x
Hired
5.0
Rating
16
Followers
Top Rated Plus Freelancer & Top 1% Talent
Cover image for Anchor Down - Transport & Logistics Platform
Anchor Down - Transport & Logistics Platform
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Cover image for Business Development AI Workflow
Business Development AI Workflow
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Cover image for ADHD-Friendly AI Automation Workflows
ADHD-Friendly AI Automation Workflows
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Cover image for AI Function Calling Agent
AI Function Calling Agent
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