Project: AI assistant for analyzing team meetings
Goal:
Create a comprehensive AI system for the automatic processing of audio recordings from team meetings. Key requirements include transforming unstructured conversations into structured, analysis-ready data; creating multi-level summaries for different roles (Owner, Team Lead, BizDev); and developing an interactive AI assistant for instant access to the corporate knowledge base via Telegram.
My Contribution:
The project started with a challenge: key company information — decisions, problems, and tasks — was "locked" inside hour-long audio files. This made searching and analyzing it practically impossible, forcing employees to waste time re-listening.
My contribution involved designing and developing "from scratch" a cohesive, multi-component architecture on self-hosted n8n, which transformed passive audio recordings into an active and intelligent resource.
I strategically chose the stack PostgreSQL + Supabase, which allowed combining the reliability of a relational database for structured reports with the power of a vector store for semantic AI search.
The system consists of three interconnected workflows that ensure the complete data lifecycle:
Workflow #1 ("Data Factory"): This process serves as the foundation of the entire system. It automatically accepts audio recordings, integrates with a transcription service, and then uses OpenAI to generate unique, customized summaries for each role. The final data is structured and stored simultaneously in PostgreSQL and vectorized for Supabase.
Workflow #2 ("Analytics Synthesizer"): Operating on a schedule, this workflow aggregates daily summaries from PostgreSQL, reuses AI to create a concentrated strategic report for the week for the owner, and automatically sends personalized briefings to key employees (Team Lead, BizDev) via Telegram.
Workflow #3 ("Interactive AI Assistant"): The pinnacle of the system — a Telegram bot that serves as a single access point to the knowledge base. I implemented:
Access control: The bot identifies the user and their role through the database, unlocking relevant features.
Admin commands: The ability to generate reports on demand by triggering Workflow #2.
RAG pipeline (Retrieval-Augmented Generation): A full-fledged question-answering mechanism. The bot converts the user's query into a vector, finds relevant information in Supabase, prepares context, and generates an accurate response using OpenAI.
Result:
Successfully developed and implemented an autonomous corporate "second brain" that operates 24/7. The client received a system that transforms conversations into structured assets, saving dozens of hours of work time and enabling data-driven decision-making rather than relying on memory.
The architecture is fully scalable: adding new roles, report types, or data sources does not require a system overhaul. The solution provides instant and secure access to information, ensuring that each employee sees only the data assigned to them.
#n8n #PostgreSQL #Supabase #pgvector #OpenAI #Telegram #TelegramBot #Automation #NoCode #API #APIIntegration #RAG #LLM #AIassistant #WorkflowAutomation #BusinessAutomation #Automation #ChatBot
Create a comprehensive AI system for the automatic processing of audio recordings from team meetings. Key requirements include transforming unstructured conversations into structured, analysis-ready data; creating multi-level summaries for different roles (Owner, Team Lead, BizDev); and developing an interactive AI assistant for instant access to the corporate knowledge base via Telegram.
My Contribution:
The project started with a challenge: key company information — decisions, problems, and tasks — was "locked" inside hour-long audio files. This made searching and analyzing it practically impossible, forcing employees to waste time re-listening.
My contribution involved designing and developing "from scratch" a cohesive, multi-component architecture on self-hosted n8n, which transformed passive audio recordings into an active and intelligent resource.
I strategically chose the stack PostgreSQL + Supabase, which allowed combining the reliability of a relational database for structured reports with the power of a vector store for semantic AI search.
The system consists of three interconnected workflows that ensure the complete data lifecycle:
Workflow #1 ("Data Factory"): This process serves as the foundation of the entire system. It automatically accepts audio recordings, integrates with a transcription service, and then uses OpenAI to generate unique, customized summaries for each role. The final data is structured and stored simultaneously in PostgreSQL and vectorized for Supabase.
Workflow #2 ("Analytics Synthesizer"): Operating on a schedule, this workflow aggregates daily summaries from PostgreSQL, reuses AI to create a concentrated strategic report for the week for the owner, and automatically sends personalized briefings to key employees (Team Lead, BizDev) via Telegram.
Workflow #3 ("Interactive AI Assistant"): The pinnacle of the system — a Telegram bot that serves as a single access point to the knowledge base. I implemented:
Access control: The bot identifies the user and their role through the database, unlocking relevant features.
Admin commands: The ability to generate reports on demand by triggering Workflow #2.
RAG pipeline (Retrieval-Augmented Generation): A full-fledged question-answering mechanism. The bot converts the user's query into a vector, finds relevant information in Supabase, prepares context, and generates an accurate response using OpenAI.
Result:
Successfully developed and implemented an autonomous corporate "second brain" that operates 24/7. The client received a system that transforms conversations into structured assets, saving dozens of hours of work time and enabling data-driven decision-making rather than relying on memory.
The architecture is fully scalable: adding new roles, report types, or data sources does not require a system overhaul. The solution provides instant and secure access to information, ensuring that each employee sees only the data assigned to them.
#n8n #PostgreSQL #Supabase #pgvector #OpenAI #Telegram #TelegramBot #Automation #NoCode #API #APIIntegration #RAG #LLM #AIassistant #WorkflowAutomation #BusinessAutomation #Automation #ChatBot
Kyiv 
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