Video
Learn how AI tools support marketing work, from prompt engineering and content generation to market research and sentiment analysis. See examples with ChatGPT, Gemini, DeepSeek, Grok and Perplexity for practical campaign tasks.
Building an AI agent in Microsoft Copilot requires no programming, and Martin Kuvandzhiev, CEO of encorp.ai, walks through the whole process step by step. Together with him you build a real business agent called Invoice Processor: you upload an invoice in the chat, the agent reads it, extracts company, date, invoice number, amount, VAT, type and line items, adds them to a shared register and saves the result to SharePoint. The video covers Agent Builder, describing the agent in plain language, Instructions, Skills, Cloud Files, Knowledge Base, Suggested Prompts, testing with a real invoice, working with Excel, adding Copilot Connectors, and sharing the agent with the whole company with different permissions for using and editing. Martin explains the approach Encorp often uses: AI creates the first version, a person reviews it, and then specific business rules are added. He also lists other agents you could build the same way, such as procurement, HR, sales, compliance and internal policy assistants. Useful for managers and teams on Microsoft 365 who want a shared agent that everyone uses the same way.
An AI customer support agent built with n8n and RAG can read hundreds of past support cases and draft the right replies to new customer emails. In this tutorial Martin Kuvandzhiev, CEO of encorp.ai and n8n Ambassador for Bulgaria, builds exactly that from scratch. Starting from a demo document of 300 fictional support cases, he turns it into a knowledge base using embeddings and a vector store (the PDF becomes 425 searchable items), then gives it to an AI Agent as a tool. You see why the whole knowledge base should not go into the system prompt, how a weak first prompt makes the agent ignore the vector store, and how fixing it and structuring the data improves accuracy. Then the system is connected to Gmail: an AI classifier labels each incoming email as support or other, the agent searches the knowledge base and creates a ready Gmail draft, keeping a human in the loop. Martin also explains what he would use in production, such as PostgreSQL/pgvector, Supabase or Pinecone. For automation builders and support teams.
ChatGPT for conference networking is the AI hack Martin Kuvandzhiev, CEO of encorp.ai, demonstrates in this video. Facing a conference with 4,000 attendees and only two days, he gives ChatGPT Work browser access to the conference platform and lets it analyze participants instead of scrolling through the app himself. In the demo, using the Bits & Pretzels platform, he asks ChatGPT to find potential clients suitable for Encorp.ai, then requests an Excel file with company, person, position, likelihood of needing the services, why they are a good prospect, two AI use cases and a conversation opener. The result is a shortlist of 18 priority contacts, each with priority, name, company, use cases and an outreach angle. Martin notes the same approach works for sales prospecting, company research, lead qualification, partnerships, market research and recruitment, and reminds viewers to follow corporate policies and access rules when using such tools with company accounts. Aimed at sales, business development and founders who attend conferences.
Learn how AI tools support marketing work, from prompt engineering and content generation to market research and sentiment analysis. See examples with ChatGPT, Gemini, DeepSeek, Grok and Perplexity for practical campaign tasks.
Building an AI agent in Microsoft Copilot requires no programming, and Martin Kuvandzhiev, CEO of encorp.ai, walks through the whole process step by step. Together with him you build a real business agent called Invoice Processor: you upload an invoice in the chat, the agent reads it, extracts company, date, invoice number, amount, VAT, type and line items, adds them to a shared register and saves the result to SharePoint. The video covers Agent Builder, describing the agent in plain language, Instructions, Skills, Cloud Files, Knowledge Base, Suggested Prompts, testing with a real invoice, working with Excel, adding Copilot Connectors, and sharing the agent with the whole company with different permissions for using and editing. Martin explains the approach Encorp often uses: AI creates the first version, a person reviews it, and then specific business rules are added. He also lists other agents you could build the same way, such as procurement, HR, sales, compliance and internal policy assistants. Useful for managers and teams on Microsoft 365 who want a shared agent that everyone uses the same way.
An AI customer support agent built with n8n and RAG can read hundreds of past support cases and draft the right replies to new customer emails. In this tutorial Martin Kuvandzhiev, CEO of encorp.ai and n8n Ambassador for Bulgaria, builds exactly that from scratch. Starting from a demo document of 300 fictional support cases, he turns it into a knowledge base using embeddings and a vector store (the PDF becomes 425 searchable items), then gives it to an AI Agent as a tool. You see why the whole knowledge base should not go into the system prompt, how a weak first prompt makes the agent ignore the vector store, and how fixing it and structuring the data improves accuracy. Then the system is connected to Gmail: an AI classifier labels each incoming email as support or other, the agent searches the knowledge base and creates a ready Gmail draft, keeping a human in the loop. Martin also explains what he would use in production, such as PostgreSQL/pgvector, Supabase or Pinecone. For automation builders and support teams.
ChatGPT for conference networking is the AI hack Martin Kuvandzhiev, CEO of encorp.ai, demonstrates in this video. Facing a conference with 4,000 attendees and only two days, he gives ChatGPT Work browser access to the conference platform and lets it analyze participants instead of scrolling through the app himself. In the demo, using the Bits & Pretzels platform, he asks ChatGPT to find potential clients suitable for Encorp.ai, then requests an Excel file with company, person, position, likelihood of needing the services, why they are a good prospect, two AI use cases and a conversation opener. The result is a shortlist of 18 priority contacts, each with priority, name, company, use cases and an outreach angle. Martin notes the same approach works for sales prospecting, company research, lead qualification, partnerships, market research and recruitment, and reminds viewers to follow corporate policies and access rules when using such tools with company accounts. Aimed at sales, business development and founders who attend conferences.
