been using clay for lead scraping but tried building my own n8n flow instead. way more work but way cheaper and u have full control over what data u grab. anyone else just diy this stuff or is clay worth it

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Hey everyone! 👋 I'm Takeichi, an AI & Full-Stack Engineer based in Japan. I've spent the past 10+ years building production software, with the last several years focused on AI systems and automation. Most of my work has been around: - 🤖 AI Agents & Agentic Workflows - 🧠 LLM Applications & RAG Systems - ⚡ Workflow Automation - 🐍 Python (FastAPI, Flask), TypeScript/Node.js - ⚛️ React & Next.js - 🔗 API integrations and backend architecture - 👁️ Computer Vision & OCR I've built AI research agents, document intelligence platforms, multi-agent workflows, AI voice systems, and automation tools that integrate with third-party services and enterprise systems. I'm here to: - Learn from other builders - Share ideas and technical knowledge - Exchange AI automation workflows - Connect with people building real-world AI products Looking forward to meeting everyone! Feel free to say hi or reach out if you're working on AI agents, automation, or LLM-powered products. 🚀 Portfolio: https://contra.com/takeichi_inoue_65rexfis/about Email: [email protected] Telegram: https://t.me/HustorAI WhatsApp: +81 80-9299-0062

We're building speech infrastructure for India — high-performance Text-to-Speech (TTS) and Automatic Speech Recognition (ASR) models with support for 15 Indic languages. Some of our current benchmarks and capabilities: TTS latency: 192 ms ASR latency: 203 ms Deployment: On-premise and edge-ready architecture for enterprise environments Customization: Enterprise-grade model adaptation and fine-tuning for domain-specific use cases We're working with companies building: Voice agents for BFSI Customer support and contact center automation Healthcare assistants EdTech and learning platforms Government and citizen-service applications Logistics and field operations Retail and commerce voice experiences Voice-enabled IoT and smart devices A lot of our recent conversations have been around organizations that require data privacy, low latency, and complete deployment control, where cloud-only solutions aren't a fit. If you're building voice-first products, conversational AI, or need Indic speech models deployed on-prem, I'd love to connect and learn more about your use case. [email protected]

new models dropped again but the bottleneck on most builds isn't the model, it's the prompts and system design lol. been using the same model for my phone bot for 6 months and my clients still just want reliable not fancy. what are yall actually changing when a new drop comes out or do you stick with whatever's working?