AI Agent Applications – Intelligent Meeting Minutes System (Part 1)

“ Intelligent meeting minutes systems have many mature online applications. Why develop a self-researched meeting minutes system? Self-researched private deployment has its practical significance and market demand; this series of articles will analyze application scenarios, product definitions, and technical implementations step by step.”

As a general efficiency tool, intelligent meeting minutes systems have very mature application systems in large companies. The current market meeting minutes systems can be divided into three categories:

Integrated office ecosystem built-in tools: Feishu Miaojì, DingTalk Shanjì, Tencent Meeting Minutes;

Professional AI meeting assistants: Tingnao AI, iFlytek Tingjian, Tongyi Tingwu;

Internationally universal tools: Otter.ai, Microsoft Teams transcription;

01

—

Why develop self-researched private deployment?

1. Confidentiality needs: Many corporate meeting contents cannot be disclosed, such as shareholder meetings, marketing meetings, etc. Cloud services cannot be used due to concerns about leakage risks;

2. Industry/internal terminology: Many meeting contents contain industry or company-specific jargon, commonly referred to as “industry jargon,” which cloud-based general meeting minutes AI cannot accurately understand;

3. Association of previous and subsequent meeting contents: When meeting contents refer to previous meeting contents, cloud-based meeting minutes AI has no memory and cannot understand this meeting through the previous meeting contents, leading to a loss of relevance in the minutes; key information may be missed;

4. Action plans and execution: Meetings generate action plans that need to be followed up on, including follow-up results, etc.; cloud-based meeting minutes AI can only provide minutes without subsequent follow-up, which cannot form a closed loop;

5. Implementation of meeting resolutions: After meeting resolutions, specific tasks need to be implemented, such as sending notifications/documents, forming rules and regulations, checking work, etc.; it is necessary to connect with other systems to form an information chain and close the loop to improve overall efficiency and quality;

6. Meeting quality and efficiency: Whether meetings are of quality, whether decisions are made, the role of meetings in the entire project or a larger scope; the work assessment of meeting participants, etc., cannot be analyzed by cloud AI;

02

—

Core competitive differences

Competitive Dimension	Cloud-based General Tools	Self-researched Private Solutions
Data Security	Data stored on third-party servers, with leakage risks	Local storage + end-to-end encryption, zero data outflow
Terminology Adaptation	General terminology recognition, low accuracy for specialized terms	Supports custom terminology libraries, strong industry adaptability
Process Closure	Only provides basic minutes, cannot link to business systems	Full process management, deeply integrated with OA/ERP systems
Quality Analysis	No deep analysis capability, only provides basic statistics	Multi-dimensional quality indicators, supporting assessment and optimization

03

—

Target Customer Groups

(1) Core Customer Group: High-Sensitivity Industry Enterprises

Including financial institutions (banks, securities firms), medical enterprises, military units, government departments, etc., whose core needs are data security and compliance, with extremely high confidentiality requirements for meeting contents. These enterprises have sufficient budgets and are usually willing to invest 1 million to 10 million yuan/year for private deployment and custom development, with rigid demands for terminology adaptation and system integration capabilities.

(2) Key Customer Group: Medium to Large Group Enterprises

Such as manufacturing groups, chain enterprises, technology companies, etc., these enterprises have high meeting frequencies and cross-departmental collaboration, with core needs for full-process closed-loop management of meetings and association of previous and subsequent contents, requiring private solutions to connect with existing internal systems to improve meeting efficiency and decision-making effectiveness. Their needs focus on task follow-up, assessment correlation, and other functional modules, with budgets typically ranging from 100,000 to 1 million yuan/year.

(3) Potential Customer Group: Small and Medium Enterprises in Niche Fields

Such as specialized law firms, accounting firms, and technology startups in niche industries, these enterprises may be small in scale but have clear needs for privacy protection due to meeting contents involving client confidentiality or core technologies. With the popularity of lightweight private solutions (such as Docker container deployment), the demand from these enterprises is gradually being released, leaning towards a “basic functions free + advanced functions subscription” model, with budgets typically ranging from 10,000 to 100,000 yuan/year.

04

—

Summary

Today, we have considered the “AI Meeting Minutes Self-Research Private Deployment Solution” from a market perspective. Next, we will cover:

• Business Architecture

• Technical Architecture

• Product Design

• Key Technical Implementations