Freelancers using PandaDoc in Brașov
Freelancers using PandaDoc in Brașov
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Pavlo Demchenko
Brașov, Romania
AI Automation Expert & Systems Architect
5.0
Rating
21
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AI Automation Expert & Systems Architect
24
Just finished building a powerful automation for a client who wanted to speed up the entire post–sales call proposal process — without adding more manual work 🙌 😍 Here’s what I built: After every sales call, the client simply fills out a short 3-minute form. From there, the system takes over: AI generates clean, professional proposal copy based on the form input. A fully structured PandaDoc draft is created automatically. The lead record in ClickUp gets updated instantly. A ready-to-send email draft is created in Gmail so the client can follow up with one click. 🚀 Results: - Cut proposal creation time by 90%. - Increasing in payments by 50% (compared to every previous unpaid invoice). - Clients got lost by 30% less.
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My client wanted more booked calls and less time glued to their inbox. So we automated the entire appointment pipeline with a smart AI assistant 🙌 😍 Here’s what I built: The moment a lead sends a message, the AI takes over. It chats like a real assistant, collects all the needed info, checks availability in real time, and books the meeting automatically. It creates the event in Google Calendar, updates the CRM/Sheets, and generates instant confirmation + reminder emails. It can also reschedule, cancel, and qualify leads before booking — all without the client lifting a finger. 🚀 Results: - Reduced manual scheduling time by 95%. - Boosted completed bookings by 40%. - Zero missed messages — every lead now gets answered instantly, 24/7.
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This could be a game-changer in the UGC niche. I built this UGC content system and helped a retail store generate an extra $5K. 🚀 You can check the results in the video. What do you think?
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Just wrapped up a simple automation for an architecture firm client struggling with slow, manual document processing🙌 . 😍 Here’s what I built: This system monitors a Google Drive folder, converts PDF documents into clean text chunks with Unstructured, generates OpenAI embeddings, and upserts vectors into Pinecone. It’s a practical, production-ready starting point for Retrieval-Augmented Generation (RAG) that you can plug into a chatbot, semantic search, or internal knowledge tools. 🚀 Results: Saved 10+ hours per week in document prep. Improved document analyse speed by 80%. Improves understanding of the necessary information by 16%.
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