Build Autonomous CMO AI Platform

@Srashtasoft

I can take your Android app from initial concept to a fully tested and production-ready Google Play release with a scalable architecture, modern Material Design UI, stable API/database integration, and clean, maintainable code built for long-term growth. I have experience managing the complete Android development lifecycle, including planning, UI/UX implementation, backend/API integration, testing, optimisation, and Play Store deployment. I focus on creating responsive, high-performance applications that work reliably across a wide range of Android devices. The project will include: ✔ Clean and scalable Android architecture ✔ Modern Material Design-based UI/UX ✔ Secure API & database integration ✔ Thorough QA and device compatibility testing ✔ Well-commented source code & build files ✔ Deployment and handoff documentation ✔ Google Play release support I can handle the entire process from prototyping to final submission while keeping communication clear and development structured for smooth delivery. Ready to discuss your app idea, recommended tech stack, timeline, and development roadmap to get started immediately.

@vishal1145

Your autonomous CMO system will fail if you try to build everything at once. I've architected similar multi-agent platforms for 2 marketing agencies, and the ones that succeeded started with a narrow scope - content intelligence and publishing - then expanded. Quick question - you mentioned 3500 URLs for initial scraping. What's your current server infrastructure? If you're on shared hosting, you'll hit rate limits within the first 100 requests. Also, are these competitor sites behind Cloudflare or similar bot protection? That changes the scraping architecture entirely. Here's the phased approach: - PYTHON + SCRAPY: Build a distributed scraping system with rotating proxies and headless browsers to bypass bot detection. Store raw HTML in S3, not your database, to avoid bloating storage costs. - LANGCHAIN + CLAUDE API: Create a RAG pipeline that ingests scraped content, builds vector embeddings, and feeds context to content generation agents. This prevents hallucinations and keeps output grounded in competitor data. - PHP CMS INTEGRATION: Since you mentioned existing website structure, I'll build MCP connectors for WordPress/custom CMS to auto-publish drafts with human approval gates. No manual copy-paste. - GOOGLE SEARCH CONSOLE + GA4 APIs: Set up automated performance tracking that feeds back into the content planner. If a topic underperforms, the AI adjusts future content strategy without human intervention. - AGENTIC ORCHESTRATION: Use LangGraph to coordinate master/sub-agents - one for SEO audits, one for content generation, one for social scheduling. Each agent has specific tools and doesn't step on others' toes. Your Rs 1L budget is tight for 6 months of guaranteed support. Running costs alone will be Rs 15-20K monthly (Claude API at scale, proxy services, vector database hosting). That leaves Rs 40K for development, which means we need to reuse existing frameworks aggressively - no custom builds from scratch. I've built 3 similar systems where AI reduced content production time by 70% while maintaining quality. Let's discuss version 1 scope and which automation delivers ROI fastest before committing to the full vision.

@kishanbwts

This project has many moving parts, so I suggest we start by defining a clear, lean version 1 that delivers core AI-powered content creation, SEO audit/fixes, and competitor scraping with human-in-loop checks. From my experience building a similar AI content workflow for a SaaS client, using a master agent setup coordinating subagents with Claude or an LLM API backend works well. For quick landing page tweaks, integrating directly with your existing CSS and structure via a lightweight UIUX module is straightforward. Considering your need for continuous updates and cross-channel content output, combining open-source tools like OpenClaw for scraping plus Claude or Cursor APIs for chat-driven planning and content generation is practical and within a $50-$100 monthly API cost. Python scripts can handle custom RPA tasks where no API exists, as I’ve done for automating SEO audits and social media post scheduling in past projects. How frequently do you expect SEO audits and social listening reports? And will human reviews be daily or weekly? This affects task scheduling and agent design. Also, should the system integrate deeply with your GA and GSC dashboards or pull their data periodically for analysis? I’m ready to draft a version 1 plan focusing on delivering the full pipeline from scraping through content publishing, including cost estimates and timelines. Once you share your NDA, I can begin immediately.

@ashinnd84

Hello there, we are a senior team of Automation engineers, Full Stack Web and Mobile App Developers and we can do this project in no time. Thanks Ashish Kumar.

@redspector

I have architected and deployed numerous enterprise-grade automation systems. Building 'Build Autonomous CMO AI Platform' correctly is exactly what I do best. I have reviewed your requirement carefully: "An Agentic AI expert who can help me build an end to end CMO (Chief marketing officer) which can do: - SEO - copy of ...". I know exactly what needs to be done. I will architect a seamless, highly optimized solution using Python, PHP, Web Scraping, ensuring it works flawlessly from day one. Given the scope, I will structure this professionally with clear milestones, ensuring high-quality delivery at every phase without delays. Best regards, Abdullah Z Freelancer: redspector

@chiragardeshna

Hi there, Strong alignment with this requirement comes from experience building agentic AI systems, RAG workflows, autonomous content pipelines, SEO automation, and AI orchestration platforms with human-in-loop approval systems. Clear understanding of the vision to build an Autonomous CMO platform handling SEO, competitor monitoring, content planning, publishing, social automation, analytics tracking, and continuous AI improvement using Claude, Cursor, Gemini, MCP, and custom agents. Hands-on expertise with LangChain, CrewAI, Python automation, scraping systems, vector databases, AI APIs, publishing workflows, analytics integrations, and scalable multi-agent architectures for long-term MVP execution. A lean V1 can realistically be built within the proposed budget using hybrid APIs, RAG memory, automation agents, and human approval flows while keeping operational costs around $80–$250/month depending on scale. Recent work: https://www.freelancer.com/u/chiragardeshna Regards Chirag

@srujank0903

I can help you build a complete Agentic AI-powered CMO system tailored to your requirements. The solution will include: End-to-end SEO (audits, fixes, and ongoing optimisation) Automated website copy, UI/UX tweaks, and landing page setup Competitive content scraping and monitoring with knowledge graph/RAG updates AI-driven content planning, creation, and fine-tuning with human-in-loop oversight Automated publishing to CMS and social platforms, with task generation for manual posts RPA via Python for gaps where APIs are unavailable Continuous performance tracking via GA, GSC, socials, and internal dashboards Scalable monthly output: 30-40 articles, 100+ social posts, 100+ short videos, and scripts for full videos I will advise on the most efficient stack (Cursor, Claude APIs, Gemini where suited, plus open-source integrations) and deliver a Version 1 + roadmap for Version 2. The system will be optimised for your Rs 1L budget, ensuring 6 months of operational support with issue resolution. Let’s collaborate to create a tireless AI CMO with sub-agents that continuously learn, adapt, and scale your marketing operations seamlessly.

@dushyant317

Hello, I have hands-on experience building agentic AI workflows using Claude, OpenAI, Gemini, LangGraph, RAG pipelines, browser automation, and multi-agent orchestration systems for SEO, content automation, research, publishing, and growth operations. Your CMO vision is achievable in phased execution using a hybrid architecture (custom orchestration backend + Claude/Gemini/OpenAI APIs + Cursor/Claude Code workflows + MCP/RPA agents), and I can help architect a scalable V1 within your budget while planning a production-grade V2 with continuous learning, human-in-loop approvals, analytics feedback loops, and autonomous content operations.

@manoval09

Hi, building an autonomous CMO requires more than feeding marketing prompts to an LLM—you need multi-agent orchestration with memory, tool access, and iterative strategy refinement. I see you're looking for an end-to-end system at a constrained budget; I'd propose starting with a focused MVP rather than trying to build everything at once. My approach: I'll architect this around LangChain agents with a ReAct pattern (Reasoning + Acting), so your CMO can break down campaigns into research → strategy → execution. I'll integrate market research APIs, build a strategy memory store using vector embeddings for learned context, and create hooks for your actual marketing tools (email, social, analytics). Python + FastAPI for the backend lets us iterate quickly and validate assumptions. First 24 hours: I'll scope exactly which marketing function matters most for your initial version—campaign planning, content strategy, or performance analysis—then build a working prototype for that single capability. This gives us a proven foundation before discussing the timeline for full scope. What's the one marketing capability you'd want the AI to handle first? Best regards, Val

@ahmadraza001912

As a dedicated full-stack developer with experience across various domains, including web scraping and Python development, I see great potential in partnering with you for your ambitious CMO AI Project. My technical skills and intuitive understanding of your project's scope make me a strong contender. Not only have I engineered production-grade applications using Python (Django, FastAPI) and RESTful APIs extensively, but I'm also adept at large-scale web scraping and data analysis. Furthermore, my experience in deploying mobile app APIs, app analytics, cloud infrastructure (including GCP), DevOps workflows adds breadth to the stack choices we could make. Regarding your budget, I proactively engage in cost optimization while guaranteeing top-notch performance and functionality. Whether through claude or custom app, Cursor or API of Gemini–I'll leverage my skills to recommend what fits your vision within the budget constraints. Lastly, my prior collaborations have entailed adapting open-source solutions to customized needs efficiently and responsibly within set agreements like NDA and Non-competes. I excel in clear communication, maintaining transparency at every stage of the project—ensuring your legal requirements are met while delivering on-time and on-budget. Given the complexity of your project and need for consistent relationship over 6 months, my dedication won't be debated; it will be indomitable! Reach out to put our talented collaboration into action!

@harryharukih

Hi, Your vision for an AI-native CMO system is absolutely achievable with the right architecture and phased execution strategy. I specialize in building AI automation systems, agentic workflows, RAG pipelines, scraping infrastructures, SEO/content engines, and human-in-loop orchestration platforms using modern LLM stacks. After reviewing your requirements carefully, I believe the correct approach is not a single “magic AI agent,” but a scalable multi-agent marketing operating system consisting of: • Master orchestration agent • Specialized sub-agents (SEO, content, analytics, social, CRO, publishing, research, competitor monitoring, etc.) • RAG + knowledge graph memory layer • Human approval workflows • Automation pipelines with analytics feedback loops • Continuous learning/improvement from human commentary and performance data

@raja861318

I'm interested in working with our full potential and my honesty seen in my behaviour so please give me details of work and dm me for job ?

@karthikresonite

Hello, Resonite Technologies specializes in AI agent ecosystems, RAG systems, SEO automation, content engines, MCP/API integrations, and autonomous workflow platforms. Your AI-powered CMO vision is achievable with a phased MVP approach. Recommended V1 includes: ✔ AI master agent orchestration ✔ SEO audits & competitor scraping ✔ Knowledge Graph / RAG pipeline ✔ Content planner + human-in-loop workflows ✔ Blog/social draft generation & publishing ✔ GA/GSC/social analytics monitoring ✔ CMS/API/MCP integrations ✔ Python RPA automation where APIs are unavailable Recommended stack: • LangGraph / CrewAI • Claude + Gemini + OpenAI hybrid • FastAPI/Node.js backend • PostgreSQL + Qdrant vector DB • Playwright/Scrapy scraping pipelines We recommend building a custom agentic platform instead of relying only on Cursor/ClaudeCode. Those tools can support development, but autonomous AI operations need dedicated backend orchestration. Estimated infra/API costs can start around ₹8k–₹25k/month depending on scale and automation frequency. We are comfortable signing NDA/non-compete agreements before project discussion. Warm Regards, Karthik B Resonite Technologies

@gauravk19

Built scalable AI automation systems using Claude, Gemini, RAG, MCP, Python RPA, and agent workflows. Can architect your AI CMO MVP within ₹1L using reusable proven open-source stacks. Technical Open Questions: Which CMS, social platforms, GA/GSC, and invoicing tools need integration? Preferred LLM stack: Claude, Gemini, OpenAI, or hybrid orchestration? Should RAG use vector DBs like Weaviate/Pinecone or self-hosted Chroma? Video generation scope: scripts only or AI voice/video automation too? Hosting preference: local VPS, cloud GPU, or serverless architecture?

@owenm221

Hi, I have carefully reviewed your CMO AI Platform requirements and I'm confident I can help build this end-to-end. I bring strong skills in Python, JavaScript, HTML/CSS and AI development. I can help build and integrate: AI-powered SEO audit and fixes Automated website copywriting features Landing page generation following your existing CSS structure Content creation automation AI model integration and prompt engineering I have hands-on experience with AI tools, prompt engineering and building AI-powered web applications. I can start immediately. Can we discuss your current stack and what's already been built? Best regards, Owen M.

@mehulp55

✅992+ Projects Delivered ✅500+ Happy Clients I can help you build a scalable Agentic AI CMO system that automates SEO, content, and growth workflows efficiently. Your challenge of combining multiple agents, automation, and human‑in‑loop learning into one system is exactly what I deliver. With my expertise, you’ll get: ✅ Clear V1 architecture (LLMs, RAG, automation stack) ✅ Scalable content, SEO, and social pipelines ✅ Smart agent workflows with continuous learning ✅ Cost‑optimized setup with practical API usage You’ll receive a working AI growth engine ready to scale. Let’s connect on a call to discuss more in detail and grow together as a team. Thanks!

@sebastianb462

We recently assisted a client with a similar setup, ensuring their application ran seamlessly on the new environment without disrupting existing workflows. I can help design and implement an end to end CMO system tailored to your needs, integrating AI-powered SEO, content automation, and analytics tracking with smooth human oversight. Together, we’ll choose the ideal stack and tools, balancing open source and paid APIs to deliver scalable performance within your budget. This is exactly the kind of project where a structured, detail focused approach makes all the difference, and that’s what I bring. Your requirement for a clean, user friendly system that evolves with human input shows a clear vision I’m ready to realize. Regards Sebastian

@YanRane

Agentic CMO is exactly the architecture I build. Modular approach for your stack: **Core Agents:** 1. SEO Agent — audit + fix pipeline (integrates with your MCP/developer, Screaming Frog-style crawler) 2. Competitor Intel Agent — scrapes target sites on schedule, extracts content changes via diff, feeds into RAG knowledge graph (LlamaIndex + ChromaDB) 3. Content Planner Agent — generates strategy from competitor RAG + brand brief → content calendar to Notion/Sheets 4. Copy & Landing Page Agent — produces copy following your existing CSS/structure, passes HTML to dev 5. Social/Ads Monitor Agent — tracks performance metrics, alerts on anomalies **Tech stack:** Python + LangGraph for agent orchestration, Playwright for scraping, Claude/OpenAI API for generation, FastAPI orchestration layer **Timeline:** - Week 1: Competitor scraper + RAG pipeline live - Week 2-3: SEO audit + content calendar agents - Week 4+: Ads monitoring + full CMO dashboard I can start immediately. Two quick questions: What's your primary CMS? And are you already using any AI tools in the current workflow?

@ramprakash08

Hi, Thank you for sharing the detailed vision. The concept is very exciting and I genuinely believe a phased AI-driven marketing system can be built using a combination of Claude/OpenAI/Gemini APIs, automation workflows, scraping pipelines, RAG systems, and human-in-the-loop processes. My current focus is on AI workflow orchestration, automation research, and implementation using existing tools/frameworks rather than building every infrastructure component fully from scratch. I would be interested in discussing: - realistic V1 vs V2 scope - best stack and tooling choices - workflow automation possibilities - API and operational cost optimization - reusable open-source integrations I appreciate the structured approach around NDA/non-compete before technical discussions and would be open to reviewing the requirements further once formalities are completed. Looking forward to connecting. Best regards, Ram