Projects using Google Apps in KarnatakaProjects using Google Apps in Karnataka
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Cover image for Live Webinar: The AI-Ready Leader
Live Webinar: The AI-Ready Leader — Leading & Communicating in the Age of AI I designed and delivered a 2-hour live interactive webinar titled "Leading & Communicating in the Age of AI: THE AI-READY LEADER" — helping professionals navigate the intersection of leadership, communication, and AI in today's corporate world. The central question I posed to participants: "AI can generate words. But can it build trust?" What the session covered: How to communicate with authenticity in an AI-driven workplace Using AI as a co-writer without losing your human voice Building trust through clarity and empathy Leading people through AI-driven change Making better decisions with AI-assisted thinking Practical frameworks for AI-powered communication Format: Live online, fully interactive — with polls, real-time exercises, and participant Q&A Audience: Mid to senior professionals, team leads, managers, and entrepreneurs Date: 12 August 2026 | 4:00 PM IST This session is part of my ongoing work helping professionals lead with purpose and communicate with impact — even as AI reshapes the way we work.
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Cover image for Built a retrieval-augmented generation chatbot
Built a retrieval-augmented generation chatbot for a blockchain/digital ecosystem client whose product documentation was scattered across files, leaving users and internal teams with no fast, reliable way to get answers. The bot pulls strictly from the client's own docs — a Google Drive folder acts as the single source of truth, where any file created or updated is automatically downloaded, chunked, embedded with Cohere, and upserted into a Supabase vector store, so the knowledge base stays current without manual re-indexing. The chat agent, running on a Groq-hosted LLM for fast responses, is instructed to always query the vector store first, optimizing each user question into a targeted search before answering — and it's explicitly constrained to respond only from retrieved data, admitting when nothing relevant is found rather than guessing. Postgres-backed chat memory keeps context across a session, so it handles natural follow-ups instead of treating every message as a fresh conversation. The result: a self-updating support assistant that answers accurately and never fabricates product details.
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Cover image for Ember
Ember
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