AI-Driven Enterprise Knowledge Extractor
Budget / Salary$4,000–8,000
TypeFreelance project
LocationRemote
Posted1 hour ago
# YARNS & COLORS | OPEN AI MISSION 002
## Meeting Intelligence Center
### Turning Enterprise Conversations into Living Knowledge
**Company:** YARNS & COLORS / 锦祥纺织科技（苏州）有限公司
**Location:** Suzhou, China
**Engagement:** Paid Project / Milestone-Based Delivery
**Open To:** Independent AI Builders, AI Workflow Architects, Knowledge Engineers, AI-Native Studios, and Small Technical Teams
---
## 1. What We Want to Build
We are not building a simple **Meeting Recorder** or **AI Meeting Summarizer**.
YARNS & COLORS wants to create an important real-time knowledge entry point for the enterprise.
Every day, valuable first-hand information is created through internal meetings, customer visits, supplier discussions, video conferences, trade shows, product development, and technical discussions.
These conversations contain information that traditional ERP systems rarely capture:
* Why was a decision made?
* What does the customer actually want?
* What market changes are emerging?
* Which products are customers becoming interested in?
* Which problems keep recurring?
* Who committed to what?
* Why did a project change direction?
Our long-term objective is:
**To transform important enterprise conversations into continuously accumulating, reusable enterprise knowledge.**
---
## 2. Long-Term Roadmap
### Phase 1 | Capture & Structure
**Meeting → Transcript → Summary → Knowledge Extraction → Human Confirmation → Knowledge Storage**
**This is the scope of the current Mission.**
### Phase 2 | Connect, Follow & Track
Future capabilities may include:
* Connecting related meetings
* Customer and project continuity
* Decision-change tracking
* Action-item and commitment follow-up
* Recurring issue detection
* Customer requirement evolution
### Phase 3 | Enterprise Intelligence
As knowledge accumulates, the system should help identify:
* Cross-customer requirements
* Emerging market signals
* Long-term unresolved issues
* Changes in customer requirements
* Repeated technical problems
* Emerging commercial opportunities
* Changes to previous decisions
The goal is to move from:
**Meeting Records → Enterprise Intelligence**
### Phase 4 | Digital Workforce Knowledge Infrastructure
Confirmed meeting knowledge should eventually become usable, under appropriate permissions, by other Digital Employees such as Executive AI, Email, Sales, Product Development, Procurement, and future AI roles.
---
## 3. Scope of This Mission
**This engagement covers Phase 1 only.**
Phases 2–4 explain the long-term direction and are **not included in the current quotation or acceptance scope**.
However, the Phase 1 data model, knowledge structure, and architecture must support future expansion **without requiring a complete rebuild**.
We do not want an oversized system on Day One, but we also do not want a disposable demo.
---
## 4. Phase 1 Core Loop
Phase 1 should establish:
**Real Meeting → Trusted Record → Knowledge Extraction → Human Confirmation → Enterprise Knowledge Storage → Retrieval**
The system should prove that information from a real enterprise meeting can become **structured, traceable, searchable, confirmable, and reusable knowledge**.
---
## 5. Capability 01 | Meeting Efficiency & Trusted Record
The system should support:
* Meeting audio capture and/or approved audio upload
* Speech-to-Text
* Speaker identification / diarization where practical
* Timestamped transcript
* Meeting-duration management and reminders
* Executive Summary
* Meeting Minutes
* Action Items
Time management should consider:
* Planned meeting duration
* Midpoint reminder
* Approximately 80% time reminder
* End-of-meeting reminder
* Important items still lacking a conclusion, owner, or deadline
We do not expect the Builder to train a proprietary ASR model. Mature technologies should be used where appropriate.
---
## 6. Capability 02 | Meeting Knowledge Extraction
The system must go beyond summarization and extract independent **Knowledge Units**, including:
1. Customer Requirements
2. Market Trends / Market Signals
3. Product Suggestions
4. Technical Issues
5. Decisions and Decision Rationale
6. Risks
7. Items Requiring Verification
8. New Opportunities
9. Competitor Information
10. Commitments and Actions
Each Knowledge Unit should:
* Be understandable independently
* Retain its source
* Be traceable to the original meeting
* Retain relevant speaker and timestamp information where practical
* Preserve supporting evidence
---
## 7. Capability 03 | Knowledge Governance
AI-generated content should not automatically become an official company fact.
The system should support a lifecycle such as:
**Draft → Pending Confirmation → Confirmed → Updated / Superseded → Archived**
Important numerical information, customer commitments, formal decisions, and decision rationale should support human confirmation.
AI interpretations must never silently overwrite original source material.
---
## 8. Capability 04 | Enterprise Knowledge Storage
Confirmed knowledge must be stored in an environment controlled by the company.
Phase 1 should support:
* Structured Knowledge Units
* Tags
* Customer / Project / Product / Person associations
* Version history
* Evidence traceability
* Semantic search
* Data export and migration
A vector database may support retrieval but should **not become the sole source of enterprise truth**.
The architecture should avoid unnecessary dependency on a single LLM, ASR provider, or SaaS platform.
**Enterprise knowledge must remain portable.**
---
## 9. Multilingual Requirement
YARNS & COLORS operates internationally.
Meetings may include Chinese, English, mixed Chinese-English, Japanese, Italian, French, and other languages.
Phase 1 may primarily validate:
* Chinese
* English
* Mixed Chinese-English
However, the architecture must allow additional languages to be introduced later.
Mature multilingual ASR and LLM technologies should be used where appropriate.
---
## 10. Explicitly Out of Scope for Phase 1
Phase 1 does not require:
* Complete enterprise Knowledge Graph
* Large-scale cross-meeting intelligence
* Advanced automated trend analysis
* Deep ERP / CRM / OA integration
* Company-wide high-concurrency deployment
* Full customization for every language
* Automated employee performance evaluation
* Autonomous management decisions
* Full integration with future Digital Employees
These belong to later phases.
---
## 11. What Defines Success?
The key validation question is:
**Can a real enterprise meeting be reliably transformed into trusted, confirmable, traceable, searchable, and reusable enterprise knowledge?**
If this loop works reliably in real business conditions, Phase 1 is successful.
---
## 12. Indicative Budget & Timeline
### Phase 1 Budget
**USD 4,000–8,000**
This is a general reference rather than a fixed ceiling. Proposals outside this range may be considered if they demonstrate additional value, a stronger technical approach, or a materially different delivery model.
### Target Timeline
**6–8 weeks**
Alternative timelines may be proposed with clear justification and milestone planning.
All recurring or third-party costs — including ASR, LLM usage, cloud infrastructure, databases, storage, APIs, software licenses, and other external services — must be disclosed separately from development fees.
---
## 13. Milestone-Based Payment
Indicative structure:
* **20%** — Architecture + Knowledge Model + Acceptance Plan
* **30%** — Meeting Capture + Transcript + Knowledge Extraction
* **30%** — Human Confirmation + Knowledge Storage + Search
* **20%** — Pilot Acceptance + Deployment + Documentation + Handover
Final milestones will be defined in the SOW.
---
## 14. What We Expect in Your Proposal
Please address:
1. Your understanding of the business value of this Mission
2. Your proposed Phase 1 architecture and implementation approach
3. How the design can support Phases 2–4 without a complete rebuild
4. Recommended meeting-audio capture approach
5. Recommended ASR and speaker-diarization approach
6. Multilingual handling
7. Knowledge Unit structure
8. Knowledge Storage design
9. Evidence traceability
10. Enterprise data security
11. AI models, frameworks, and components you would use
12. Who will actually perform the development
13. Relevant projects personally delivered
14. Proposed timeline
15. Fixed project quotation
16. Expected recurring third-party costs
17. Recommended maintenance model
18. The three biggest technical or delivery risks
Please begin your proposal with:
**MEETING INTELLIGENCE MISSION 002**
We are not looking for the proposal with the most features.
We are looking for:
**Builders who understand the value of enterprise knowledge and know how to turn mature AI technologies into a system that works in real business operations.**
Strong performers may be invited to participate in later YARNS & COLORS Digital Workforce Missions.
Detailed enterprise data, meeting samples, system access, internal workflows, and full acceptance criteria will only be provided to shortlisted candidates under appropriate confidentiality arrangements.
## Meeting Intelligence Center
### Turning Enterprise Conversations into Living Knowledge
**Company:** YARNS & COLORS / 锦祥纺织科技（苏州）有限公司
**Location:** Suzhou, China
**Engagement:** Paid Project / Milestone-Based Delivery
**Open To:** Independent AI Builders, AI Workflow Architects, Knowledge Engineers, AI-Native Studios, and Small Technical Teams
---
## 1. What We Want to Build
We are not building a simple **Meeting Recorder** or **AI Meeting Summarizer**.
YARNS & COLORS wants to create an important real-time knowledge entry point for the enterprise.
Every day, valuable first-hand information is created through internal meetings, customer visits, supplier discussions, video conferences, trade shows, product development, and technical discussions.
These conversations contain information that traditional ERP systems rarely capture:
* Why was a decision made?
* What does the customer actually want?
* What market changes are emerging?
* Which products are customers becoming interested in?
* Which problems keep recurring?
* Who committed to what?
* Why did a project change direction?
Our long-term objective is:
**To transform important enterprise conversations into continuously accumulating, reusable enterprise knowledge.**
---
## 2. Long-Term Roadmap
### Phase 1 | Capture & Structure
**Meeting → Transcript → Summary → Knowledge Extraction → Human Confirmation → Knowledge Storage**
**This is the scope of the current Mission.**
### Phase 2 | Connect, Follow & Track
Future capabilities may include:
* Connecting related meetings
* Customer and project continuity
* Decision-change tracking
* Action-item and commitment follow-up
* Recurring issue detection
* Customer requirement evolution
### Phase 3 | Enterprise Intelligence
As knowledge accumulates, the system should help identify:
* Cross-customer requirements
* Emerging market signals
* Long-term unresolved issues
* Changes in customer requirements
* Repeated technical problems
* Emerging commercial opportunities
* Changes to previous decisions
The goal is to move from:
**Meeting Records → Enterprise Intelligence**
### Phase 4 | Digital Workforce Knowledge Infrastructure
Confirmed meeting knowledge should eventually become usable, under appropriate permissions, by other Digital Employees such as Executive AI, Email, Sales, Product Development, Procurement, and future AI roles.
---
## 3. Scope of This Mission
**This engagement covers Phase 1 only.**
Phases 2–4 explain the long-term direction and are **not included in the current quotation or acceptance scope**.
However, the Phase 1 data model, knowledge structure, and architecture must support future expansion **without requiring a complete rebuild**.
We do not want an oversized system on Day One, but we also do not want a disposable demo.
---
## 4. Phase 1 Core Loop
Phase 1 should establish:
**Real Meeting → Trusted Record → Knowledge Extraction → Human Confirmation → Enterprise Knowledge Storage → Retrieval**
The system should prove that information from a real enterprise meeting can become **structured, traceable, searchable, confirmable, and reusable knowledge**.
---
## 5. Capability 01 | Meeting Efficiency & Trusted Record
The system should support:
* Meeting audio capture and/or approved audio upload
* Speech-to-Text
* Speaker identification / diarization where practical
* Timestamped transcript
* Meeting-duration management and reminders
* Executive Summary
* Meeting Minutes
* Action Items
Time management should consider:
* Planned meeting duration
* Midpoint reminder
* Approximately 80% time reminder
* End-of-meeting reminder
* Important items still lacking a conclusion, owner, or deadline
We do not expect the Builder to train a proprietary ASR model. Mature technologies should be used where appropriate.
---
## 6. Capability 02 | Meeting Knowledge Extraction
The system must go beyond summarization and extract independent **Knowledge Units**, including:
1. Customer Requirements
2. Market Trends / Market Signals
3. Product Suggestions
4. Technical Issues
5. Decisions and Decision Rationale
6. Risks
7. Items Requiring Verification
8. New Opportunities
9. Competitor Information
10. Commitments and Actions
Each Knowledge Unit should:
* Be understandable independently
* Retain its source
* Be traceable to the original meeting
* Retain relevant speaker and timestamp information where practical
* Preserve supporting evidence
---
## 7. Capability 03 | Knowledge Governance
AI-generated content should not automatically become an official company fact.
The system should support a lifecycle such as:
**Draft → Pending Confirmation → Confirmed → Updated / Superseded → Archived**
Important numerical information, customer commitments, formal decisions, and decision rationale should support human confirmation.
AI interpretations must never silently overwrite original source material.
---
## 8. Capability 04 | Enterprise Knowledge Storage
Confirmed knowledge must be stored in an environment controlled by the company.
Phase 1 should support:
* Structured Knowledge Units
* Tags
* Customer / Project / Product / Person associations
* Version history
* Evidence traceability
* Semantic search
* Data export and migration
A vector database may support retrieval but should **not become the sole source of enterprise truth**.
The architecture should avoid unnecessary dependency on a single LLM, ASR provider, or SaaS platform.
**Enterprise knowledge must remain portable.**
---
## 9. Multilingual Requirement
YARNS & COLORS operates internationally.
Meetings may include Chinese, English, mixed Chinese-English, Japanese, Italian, French, and other languages.
Phase 1 may primarily validate:
* Chinese
* English
* Mixed Chinese-English
However, the architecture must allow additional languages to be introduced later.
Mature multilingual ASR and LLM technologies should be used where appropriate.
---
## 10. Explicitly Out of Scope for Phase 1
Phase 1 does not require:
* Complete enterprise Knowledge Graph
* Large-scale cross-meeting intelligence
* Advanced automated trend analysis
* Deep ERP / CRM / OA integration
* Company-wide high-concurrency deployment
* Full customization for every language
* Automated employee performance evaluation
* Autonomous management decisions
* Full integration with future Digital Employees
These belong to later phases.
---
## 11. What Defines Success?
The key validation question is:
**Can a real enterprise meeting be reliably transformed into trusted, confirmable, traceable, searchable, and reusable enterprise knowledge?**
If this loop works reliably in real business conditions, Phase 1 is successful.
---
## 12. Indicative Budget & Timeline
### Phase 1 Budget
**USD 4,000–8,000**
This is a general reference rather than a fixed ceiling. Proposals outside this range may be considered if they demonstrate additional value, a stronger technical approach, or a materially different delivery model.
### Target Timeline
**6–8 weeks**
Alternative timelines may be proposed with clear justification and milestone planning.
All recurring or third-party costs — including ASR, LLM usage, cloud infrastructure, databases, storage, APIs, software licenses, and other external services — must be disclosed separately from development fees.
---
## 13. Milestone-Based Payment
Indicative structure:
* **20%** — Architecture + Knowledge Model + Acceptance Plan
* **30%** — Meeting Capture + Transcript + Knowledge Extraction
* **30%** — Human Confirmation + Knowledge Storage + Search
* **20%** — Pilot Acceptance + Deployment + Documentation + Handover
Final milestones will be defined in the SOW.
---
## 14. What We Expect in Your Proposal
Please address:
1. Your understanding of the business value of this Mission
2. Your proposed Phase 1 architecture and implementation approach
3. How the design can support Phases 2–4 without a complete rebuild
4. Recommended meeting-audio capture approach
5. Recommended ASR and speaker-diarization approach
6. Multilingual handling
7. Knowledge Unit structure
8. Knowledge Storage design
9. Evidence traceability
10. Enterprise data security
11. AI models, frameworks, and components you would use
12. Who will actually perform the development
13. Relevant projects personally delivered
14. Proposed timeline
15. Fixed project quotation
16. Expected recurring third-party costs
17. Recommended maintenance model
18. The three biggest technical or delivery risks
Please begin your proposal with:
**MEETING INTELLIGENCE MISSION 002**
We are not looking for the proposal with the most features.
We are looking for:
**Builders who understand the value of enterprise knowledge and know how to turn mature AI technologies into a system that works in real business operations.**
Strong performers may be invited to participate in later YARNS & COLORS Digital Workforce Missions.
Detailed enterprise data, meeting samples, system access, internal workflows, and full acceptance criteria will only be provided to shortlisted candidates under appropriate confidentiality arrangements.
Apply on Freelancer →
Project sourced from Freelancer.com. Applications happen directly on the original platform — we never collect your data.