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Transcription and Meeting Analysis Platform
Expertise:
PM
Backend
Frontend
Tech Stack:
Python
LLM
Client: Large corporation
The client is a large corporation with multiple departments, including sales, HR, and project management. The company actively holds meetings and needed an effective tool for analyzing and storing information. The primary goal was to simplify the meeting analysis process and improve access to information for all employees.
About the Client
The project involved the development of a platform for meeting transcription, creation of a vector knowledge base, and customization for various company departments. The platform was designed to automate the meeting analysis process and provide personalized recommendations for each department.
Project Overview
Challenges & Objectives
- Challenges: Simplifying the meeting analysis process, improving access to information, increasing the efficiency of departmental work, and creating a unified knowledge base for all employees.
- Objectives: Developing a platform capable of automatically transcribing meetings, analyzing their content, and providing personalized recommendations for each department.
Implementation
01
Development of a meeting transcription platform supporting various languages and dialects.
02
Creation of a vector knowledge base for all communications, enabling the storage and analysis of information from all meetings.
03
Customization of the platform for different departments (sales, recruitment, etc.), allowing the analysis to be tailored to the specific needs of each department.
04
Implementation of a personal assistant for searching the knowledge base, simplifying access to information for all employees.
Platform Advantages
01
Deployment within the client's infrastructure
The platform was deployed within the client's infrastructure, ensuring a high level of security and data control.
The platform was deployed within the client's infrastructure, ensuring a high level of security and data control.
02
Support for various LLMs
The platform supports various language models (LLMs), allowing it to be adapted to the needs of different departments and tasks.
The platform supports various language models (LLMs), allowing it to be adapted to the needs of different departments and tasks.
03
Modular architecture
The flexible modular architecture of the platform makes it easy to add new features and adapt it to changing business requirements.
The flexible modular architecture of the platform makes it easy to add new features and adapt it to changing business requirements.
04
Personal assistant for knowledge base search
The implementation of a personal assistant significantly simplified the process of searching for information in the knowledge base, increasing employee efficiency
The implementation of a personal assistant significantly simplified the process of searching for information in the knowledge base, increasing employee efficiency
Outcomes & Business Impact
- A 50% reduction in the time spent searching for information, significantly improving employee efficiency.
- Improved quality of meeting analysis and decision-making, leading to more effective project management.
- A 25% increase in departmental efficiency, thanks to personalized recommendations and improved access to information.
- Simplified onboarding process for new employees, as all necessary information became available in one place.
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