AI-Controlled Document Management System Development
Budget: €30 – €250 EUR
Development Specification: AI-Based Document & Correspondence Management System
1. System Objective
The goal is to develop an AI-powered system that manages, analyzes, and processes correspondence and documents from multiple sources (folder structures, email, Telegram, web uploads).
The AI should be able to:
* Understand and structure documents
* Answer questions based on correspondence
* Analyze and review legal/official documents
* Perform task-based processing of documents
* Maintain context across multiple documents
* Integrate external research (web, internal knowledge base, document history)
⸻
2. Core Structure (Multi-Folder System)
2.1 Folder Logic
Each folder represents:
* A company OR
* A topic OR
* A case/client file
2.2 Folder Attributes
Each folder contains:
* Document base (PDF, DOCX, email, text, images)
* Metadata:
* Company / project
* Timestamp
* Document type (letter, notice, contract, etc.)
* Dedicated AI context database per folder
⸻
3. Data Sources / Input System
The system must support ingestion from:
3.1 Upload
* Web-based upload (drag & drop)
* Bulk folder import
3.2 Email Integration
* Automatic ingestion from email inboxes
* Extraction and storage of attachments
3.3 Telegram Integration
* Forwarding of messages/documents to a bot
* Automatic classification into folders
3.4 API Integration
* Direct upload API for external systems
⸻
4. AI Functionalities
4.1 Document Analysis
* Document summarization
* Extraction of:
* Deadlines
* Claims / demands
* Legal risks
* Relevant entities (people, authorities, companies)
* Document classification (e.g. notice, invoice, contract, complaint)
⸻
4.2 Document Q&A System
Users can ask questions such as:
* “What is the other party requesting?”
* “What deadlines are mentioned?”
* “What risks are identified?”
* “What does document X say?”
The AI must:
* Answer strictly based on available documents
* Provide references (document + section)
⸻
4.3 Cross-Document Analysis
* Compare multiple documents
* Detect patterns (e.g. repeated fees, inspections, actions)
* Reconstruct timelines of events
⸻
4.4 Drafting & Legal Writing Assistance
The AI can:
* Draft responses, objections, and statements
* Structure legal or formal documents
* Suggest argumentation strategies
* Generate formal correspondence
⸻
4.5 Web & Knowledge Research
* Automatic research when required:
* Laws and regulations
* Court decisions
* Technical/legal background knowledge
* Combined reasoning from:
* Internal documents
* External knowledge sources
* Historical case data
⸻
5. Storage & Index Architecture
5.1 Vector Database
* Semantic search across all documents
* Chunk-based document embedding storage
5.2 Metadata Database
* Document classification
* Folder assignment
* Chronological indexing
5.3 Context Engine
* Separate context per folder
* Global cross-folder search capability
⸻
6. User Interface (Web Application)
Features:
* Folder overview dashboard
* Document viewer
* AI chat per folder
* Global AI search
* Upload center
* Document timeline view
⸻
7. Roles & Permissions
* Admin (full access)
* User (restricted folder access)
* External viewer (optional read-only access)
⸻
8. Security Requirements
* Full encryption of stored documents
* Role-based access control per folder
* Logging of all AI outputs and actions
* GDPR-compliant data handling
⸻
9. Integration with OpenClaw
Since OpenClaw already exists:
* Used as:
* AI orchestration layer
* Tool-calling framework
Required integrations:
* Document retrieval module
* Web research module
* Telegram/email connectors
* Retrieval-Augmented Generation (RAG) pipeline
⸻
10. Optional Extensions
* Automated deadline tracking
* Escalation system for legal deadlines
* Auto-generated email responses
* “Critical case” dashboard
⸻
11. Final Outcome
The system should function as:
An intelligent document and correspondence management platform with AI-based legal and analytical assistance capabilities.
End of Specification
:::
1. System Objective
The goal is to develop an AI-powered system that manages, analyzes, and processes correspondence and documents from multiple sources (folder structures, email, Telegram, web uploads).
The AI should be able to:
* Understand and structure documents
* Answer questions based on correspondence
* Analyze and review legal/official documents
* Perform task-based processing of documents
* Maintain context across multiple documents
* Integrate external research (web, internal knowledge base, document history)
⸻
2. Core Structure (Multi-Folder System)
2.1 Folder Logic
Each folder represents:
* A company OR
* A topic OR
* A case/client file
2.2 Folder Attributes
Each folder contains:
* Document base (PDF, DOCX, email, text, images)
* Metadata:
* Company / project
* Timestamp
* Document type (letter, notice, contract, etc.)
* Dedicated AI context database per folder
⸻
3. Data Sources / Input System
The system must support ingestion from:
3.1 Upload
* Web-based upload (drag & drop)
* Bulk folder import
3.2 Email Integration
* Automatic ingestion from email inboxes
* Extraction and storage of attachments
3.3 Telegram Integration
* Forwarding of messages/documents to a bot
* Automatic classification into folders
3.4 API Integration
* Direct upload API for external systems
⸻
4. AI Functionalities
4.1 Document Analysis
* Document summarization
* Extraction of:
* Deadlines
* Claims / demands
* Legal risks
* Relevant entities (people, authorities, companies)
* Document classification (e.g. notice, invoice, contract, complaint)
⸻
4.2 Document Q&A System
Users can ask questions such as:
* “What is the other party requesting?”
* “What deadlines are mentioned?”
* “What risks are identified?”
* “What does document X say?”
The AI must:
* Answer strictly based on available documents
* Provide references (document + section)
⸻
4.3 Cross-Document Analysis
* Compare multiple documents
* Detect patterns (e.g. repeated fees, inspections, actions)
* Reconstruct timelines of events
⸻
4.4 Drafting & Legal Writing Assistance
The AI can:
* Draft responses, objections, and statements
* Structure legal or formal documents
* Suggest argumentation strategies
* Generate formal correspondence
⸻
4.5 Web & Knowledge Research
* Automatic research when required:
* Laws and regulations
* Court decisions
* Technical/legal background knowledge
* Combined reasoning from:
* Internal documents
* External knowledge sources
* Historical case data
⸻
5. Storage & Index Architecture
5.1 Vector Database
* Semantic search across all documents
* Chunk-based document embedding storage
5.2 Metadata Database
* Document classification
* Folder assignment
* Chronological indexing
5.3 Context Engine
* Separate context per folder
* Global cross-folder search capability
⸻
6. User Interface (Web Application)
Features:
* Folder overview dashboard
* Document viewer
* AI chat per folder
* Global AI search
* Upload center
* Document timeline view
⸻
7. Roles & Permissions
* Admin (full access)
* User (restricted folder access)
* External viewer (optional read-only access)
⸻
8. Security Requirements
* Full encryption of stored documents
* Role-based access control per folder
* Logging of all AI outputs and actions
* GDPR-compliant data handling
⸻
9. Integration with OpenClaw
Since OpenClaw already exists:
* Used as:
* AI orchestration layer
* Tool-calling framework
Required integrations:
* Document retrieval module
* Web research module
* Telegram/email connectors
* Retrieval-Augmented Generation (RAG) pipeline
⸻
10. Optional Extensions
* Automated deadline tracking
* Escalation system for legal deadlines
* Auto-generated email responses
* “Critical case” dashboard
⸻
11. Final Outcome
The system should function as:
An intelligent document and correspondence management platform with AI-based legal and analytical assistance capabilities.
End of Specification
:::