I build automations that reduce manual work and keep teams moving.

Problem: Company inquiries coming from Gmail need to be sorted, tracked, and sent to the right department without manual handling.

Workflow: Gmail captures unread inquiries, Gemini extracts and classifies the request, then n8n routes it to the correct department, creates the ticket, updates Google Sheets, and sends the proper Slack notification.

Result: Faster inquiry handling, cleaner ticket tracking, and more consistent department routing.

Problem: Teams need a way to search internal documents without manually checking folders or giving the AI unrestricted information.

Workflow: Google Drive files are monitored for new, updated, and deleted documents. n8n processes the files, creates Gemini embeddings, stores them in Supabase, and lets a Telegram AI Agent answer using the synced knowledge base.

Result: A document-grounded chatbot with automatically updated knowledge, cleaner document management, and more reliable answers.

Problem: Leads can be missed or handled inconsistently when qualification, CRM updates, notifications, and follow-ups are done manually.

Workflow: An automated lead-handling system that qualifies incoming form responses with AI, routes them by lead potential, and manages follow-up emails automatically.

Result: Cleaner lead intake, faster routing, more consistent tracking, and fewer missed follow-ups.

Problem: Cryptocurrency news is spread across multiple sources, making it difficult to consistently monitor market sentiment and identify important developments without manual research.

Workflow: A scheduled n8n workflow retrieves recent crypto news from MarketScreener every 10 days, Gemini analyzes sentiment and generates concise summaries, then the results are stored in a structured format for historical tracking, dashboards, and reporting.

Result: Reduced manual news monitoring and transformed unstructured crypto articles into a searchable, consistent sentiment dataset for market analysis.