Automated Accounting System Development via OpenClaw
Budget: €250 – €750 EUR
AI-Based Zero-Touch Accounting System (OpenClaw / OpenClaude)
Please read the project carefully and submit a realistic offer.
The project is intended to be completed within a short timeframe.
1. Project Overview
The objective is to develop a fully automated ("zero-touch") accounting system using OpenClaw and OpenClaude.
The system will:
Process invoices (incoming and outgoing) automatically
Perform bookkeeping based on SKR03
Integrate bank data and perform reconciliation
Include fraud detection and notification workflows
Ensure full auditability and traceability
Operate in a secure, self-hosted Docker environment
Goal: Maximum automation with minimal manual interaction
2. System Architecture
Technology Stack
Backend: Node.js (NestJS)
AI / OCR: OpenClaude (vision-based pipeline)
Database: PostgreSQL or MySQL
Queue System: Redis with BullMQ or Celery
Storage: S3-compatible (MinIO)
Frontend: React dashboard
Deployment: Docker Compose
Integrations
Email (IMAP)
Banking (PSD2 / FinTS – future integration)
Telegram (notifications and interaction)
TAXflow App
3. Core Functionalities
3.1 Document Processing (OCR and Classification)
Automated processing of:
PDFs
Images
Email attachments
Extracted data:
Company name
IBAN
Invoice number
Invoice date
Amounts and currency
Tax information
Automatic Classification
Customer Invoice (Outgoing Invoice):
If the company name is "Hahn Fleischhandel OHG"
Supplier Invoice (Incoming Invoice):
All other cases
3.2 Document Intake
Primary Method
Email via IMAP:
Emails are not deleted
Emails are only marked as "read"
The inbox serves as a backup and archive
Secondary Method
Manual upload via dashboard (fallback)
Automation
Webhook-based triggers for processing
3.3 Banking and Reconciliation
Current Setup
Upload of bank statements (PDF)
Extracted data:
Opening balance
Closing balance
Transactions
Validation
Opening balance must match the previous closing balance
Duplicate statement detection
Future
PSD2 / FinTS API integration
Reconciliation
Automatic matching of invoices and payments
Detection of:
Mismatches
Missing payments
3.4 Accounting Logic (SKR03)
Automatic account assignment
Generation of booking records
Preparation of tax-relevant data
Self-Learning System
Trained using historical data (1–2 years)
Improves posting accuracy over time
Fallback
Standard SKR03 logic if no historical data exists
Duplicate Detection
Invoices
Payments
3.5 Workflow Automation
Invoice Lifecycle Management
Status tracking:
Open
Paid
Overdue
Reminder Logic
3 days before due date
3 days after due date
Alternative Telegram-based reminder after 5 days
Dunning Process
Automated reminders and escalation
Payment Matching
Automatic status updates upon payment detection
3.6 Telegram Integration (Central Control Layer)
Used for:
Fraud alerts
Invoice actions
Payment confirmations
Reminder notifications
Example Commands
PAID_{id}
KEEP_{id}
SEND_{id}
3.7 Fraud Detection System (Critical Feature)
Initial Check
IBAN starts with "DE" → automatically approved
Otherwise → further validation required
Four-Layer Validation
IBAN country check
Vendor history (last 6 months)
Payment history
Company registration (e.g., Handelsregister)
If unclear, manual approval is required via Telegram.
Rule
No suspicious invoice is processed automatically.
3.8 Dashboard (React)
Features
Upload invoices and bank statements
View:
Open invoices
Paid invoices
Errors and exceptions
Monitor:
Payment matching
Document processing status
Exports
CSV
Excel
PDF
Accounting reports
3.9 Reporting
Weekly
Payment overview
Outstanding invoices
Monthly
Tax reports
3.10 Compliance and Auditability
Full logging of all actions
End-to-end traceability:
Document → Payment → Booking
Audit-ready structure
4. Multi-Tenant Capability
Supports multiple companies
Reusable system architecture
Defined process for cloning environments
5. Project Phases
Phase Deliverable
1 Infrastructure, setup, Telegram integration, OCR demo
2 Email integration (IMAP), OCR pipeline, fraud detection
3 Bank integration and reconciliation
4 SKR03 logic, automation, reminders, and dunning
5 Dashboard and reporting (CSV / Excel / PDF)
6 Testing, optimization, deployment, and documentation
6. Key Requirements / Constraints
Zero-touch workflow
No email deletion
Full audit trail required
No automatic processing of suspicious invoices
Financial consistency (balance validation is mandatory)
Modular and scalable system design
7. Expected Outcome
A system that:
Automatically processes invoices
Matches payments with minimal manual input
Generates accounting entries
Detects fraud risks
Produces reports
Continuously improves through learning
Result: A highly automated, scalable, and audit-ready accounting system
Please read the project carefully and submit a realistic offer.
The project is intended to be completed within a short timeframe.
1. Project Overview
The objective is to develop a fully automated ("zero-touch") accounting system using OpenClaw and OpenClaude.
The system will:
Process invoices (incoming and outgoing) automatically
Perform bookkeeping based on SKR03
Integrate bank data and perform reconciliation
Include fraud detection and notification workflows
Ensure full auditability and traceability
Operate in a secure, self-hosted Docker environment
Goal: Maximum automation with minimal manual interaction
2. System Architecture
Technology Stack
Backend: Node.js (NestJS)
AI / OCR: OpenClaude (vision-based pipeline)
Database: PostgreSQL or MySQL
Queue System: Redis with BullMQ or Celery
Storage: S3-compatible (MinIO)
Frontend: React dashboard
Deployment: Docker Compose
Integrations
Email (IMAP)
Banking (PSD2 / FinTS – future integration)
Telegram (notifications and interaction)
TAXflow App
3. Core Functionalities
3.1 Document Processing (OCR and Classification)
Automated processing of:
PDFs
Images
Email attachments
Extracted data:
Company name
IBAN
Invoice number
Invoice date
Amounts and currency
Tax information
Automatic Classification
Customer Invoice (Outgoing Invoice):
If the company name is "Hahn Fleischhandel OHG"
Supplier Invoice (Incoming Invoice):
All other cases
3.2 Document Intake
Primary Method
Email via IMAP:
Emails are not deleted
Emails are only marked as "read"
The inbox serves as a backup and archive
Secondary Method
Manual upload via dashboard (fallback)
Automation
Webhook-based triggers for processing
3.3 Banking and Reconciliation
Current Setup
Upload of bank statements (PDF)
Extracted data:
Opening balance
Closing balance
Transactions
Validation
Opening balance must match the previous closing balance
Duplicate statement detection
Future
PSD2 / FinTS API integration
Reconciliation
Automatic matching of invoices and payments
Detection of:
Mismatches
Missing payments
3.4 Accounting Logic (SKR03)
Automatic account assignment
Generation of booking records
Preparation of tax-relevant data
Self-Learning System
Trained using historical data (1–2 years)
Improves posting accuracy over time
Fallback
Standard SKR03 logic if no historical data exists
Duplicate Detection
Invoices
Payments
3.5 Workflow Automation
Invoice Lifecycle Management
Status tracking:
Open
Paid
Overdue
Reminder Logic
3 days before due date
3 days after due date
Alternative Telegram-based reminder after 5 days
Dunning Process
Automated reminders and escalation
Payment Matching
Automatic status updates upon payment detection
3.6 Telegram Integration (Central Control Layer)
Used for:
Fraud alerts
Invoice actions
Payment confirmations
Reminder notifications
Example Commands
PAID_{id}
KEEP_{id}
SEND_{id}
3.7 Fraud Detection System (Critical Feature)
Initial Check
IBAN starts with "DE" → automatically approved
Otherwise → further validation required
Four-Layer Validation
IBAN country check
Vendor history (last 6 months)
Payment history
Company registration (e.g., Handelsregister)
If unclear, manual approval is required via Telegram.
Rule
No suspicious invoice is processed automatically.
3.8 Dashboard (React)
Features
Upload invoices and bank statements
View:
Open invoices
Paid invoices
Errors and exceptions
Monitor:
Payment matching
Document processing status
Exports
CSV
Excel
Accounting reports
3.9 Reporting
Weekly
Payment overview
Outstanding invoices
Monthly
Tax reports
3.10 Compliance and Auditability
Full logging of all actions
End-to-end traceability:
Document → Payment → Booking
Audit-ready structure
4. Multi-Tenant Capability
Supports multiple companies
Reusable system architecture
Defined process for cloning environments
5. Project Phases
Phase Deliverable
1 Infrastructure, setup, Telegram integration, OCR demo
2 Email integration (IMAP), OCR pipeline, fraud detection
3 Bank integration and reconciliation
4 SKR03 logic, automation, reminders, and dunning
5 Dashboard and reporting (CSV / Excel / PDF)
6 Testing, optimization, deployment, and documentation
6. Key Requirements / Constraints
Zero-touch workflow
No email deletion
Full audit trail required
No automatic processing of suspicious invoices
Financial consistency (balance validation is mandatory)
Modular and scalable system design
7. Expected Outcome
A system that:
Automatically processes invoices
Matches payments with minimal manual input
Generates accounting entries
Detects fraud risks
Produces reports
Continuously improves through learning
Result: A highly automated, scalable, and audit-ready accounting system