Epo Patent Intelligence

EPO Patent Intelligence monitors EPO patents, analyzes competitor threats, identifies tech trends, and generates strategic HTML reports for informed business...

EPO Patent Intelligence System

Intelligent patent monitoring and competitive analysis using the European Patent Office (EPO) Open Patent Services (OPS) API.

Quick Start

1. Ensure EPO credentials are configured in .env file:

   • EPO_CONSUMER_KEY - Your EPO API consumer key
   • EPO_SECRET_KEY - Your EPO API secret key

2. Run patent intelligence collection for a company:

   bash

   cd /path/to/skill
   source .env
   python3 scripts/epo_data_mapper.py "pa=IBM" 1 10
   

3. Generate strategic analysis using OpenClaw LLM:

   • Load collected patents from database
   • Use LLM to analyze patent relevance and strategic importance
   • Generate HTML report with competitive intelligence

Architecture

This skill uses a hybrid approach:

Deterministic Layer (Scripts)

• scripts/epo_data_mapper.py - EPO API authentication and data fetching
• scripts/weekly_report.sh - Automated weekly execution
• scripts/database_manager.py - Database operations

LLM-Powered Layer (OpenClaw Agents)

• Patent analysis - Use LLM to understand why patents matter to the client
• Strategic categorization - Identify technology categories and competitive threats
• Report generation - Create professional HTML with business insights
• Pattern identification - Detect trends across patent collections

Workflow

Phase 1: Data Collection (Deterministic)

Step 1: Configure EPO API credentials

bash

# Ensure .env file exists with EPO credentials
cat .env
EPO_CONSUMER_KEY=your_key_here
EPO_SECRET_KEY=your_secret_here

Step 2: Fetch patents from EPO API

bash

source .env
python3 scripts/epo_data_mapper.py "pa=IBM" 1 5

This script:

1. Authenticates with EPO using OAuth2
2. Queries EPO OPS API for patents
3. Parses XML response into structured data
4. Saves to SQLite database

Phase 2: Analysis (LLM-Powered)

Step 3: Analyze collected patents with LLM

Load patents from database and use OpenClaw's reasoning capabilities to:

1. Identify technology categories - Match patents to business-relevant categories
2. Assess competitive threat - Determine if competitor is encroaching on client's territory
3. Evaluate strategic importance - High, Medium, Low, Critical
4. Generate recommendations - Immediate action, weekly review, monthly review, monitor

Example analysis prompt:

text

Analyze these patents collected from EPO API for DMG Mori:
- Patent: "Spindle Lubricator System" by Mazak
- Abstract: [patent abstract text]
- Technology: CNC Machining

Questions:
1. Why does this patent matter to DMG Mori specifically?
2. What is the competitive threat level? (None/Low/Medium/High/Critical)
3. What strategic action should DMG Mori take?
4. Which DMG business area is affected? (CNC/Additive/Automation/Digital)

Phase 3: Report Generation (LLM-Powered)

Step 4: Generate professional HTML report

Use LLM to create structured HTML with modern enterprise dashboard design:

• Executive summary with KPI cards and key metrics
• Interactive Chart.js visualizations
• Individual patent cards with threat scoring and strategic analysis
• Activity timeline with competitor events
• Export to PDF functionality
• Mobile-responsive design

Modern Framework Stack (CDN-based, no build step):

• Tailwind CSS - Professional utility-first styling
• Chart.js - Interactive data visualizations
• Font Awesome - Enterprise iconography
• Inter font (Google Fonts) - Modern typography

Report structure:

html

<!-- Modern enterprise dashboard template -->
<nav class="gradient-bg text-white sticky top-0">
  <h1>Patent Intelligence - Week 14, 2026</h1>
  <span class="bg-white/20 px-4 py-2 rounded-full">
    <i class="fas fa-sync-alt mr-2"></i>Live Updates
  </span>
</nav>

<!-- Executive Summary Cards -->
<div class="grid grid-cols-1 md:grid-cols-4 gap-6">
  <div class="bg-gradient-to-br from-blue-500 to-blue-600 rounded-xl p-6 text-white">
    <p class="text-blue-100">Total Patents</p>
    <p class="text-3xl font-bold">47</p>
  </div>
  <!-- More KPI cards... -->
</div>

<!-- Charts Section -->
<div class="grid grid-cols-1 lg:grid-cols-2 gap-8">
  <canvas id="competitorChart"></canvas>
  <canvas id="techChart"></canvas>
</div>

<!-- Patent Cards with Priority Styling -->
<div class="card-hover priority-high threat-critical rounded-xl p-6">
  <span class="bg-red-500 text-white px-3 py-1 rounded-full">CRITICAL</span>
  <span class="bg-gray-800 text-white px-3 py-1 rounded-full">CNC Machining</span>
  <h4>Intelligent Spindle Control System</h4>
  <p><strong>⚠️ Competitive Threat:</strong> [Analysis text]</p>
  <div class="text-3xl font-bold text-red-600">85</div>
</div>

Weekly Report Deployment:

• Week 14: https://hermes.sqncr.ai/Patent_report_kw14
• Week 15: https://hermes.sqncr.ai/Patent_report_kw15
• Each week gets a new subdomain with fresh reports

Key Scripts

scripts/epo_data_mapper.py

Purpose: EPO API authentication and data fetching Deterministic - Same input always produces same output Parameters:

• Query (e.g., "pa=IBM", "ti=CNC")
• Range start (1-100)
• Range end (1-100)

Usage:

bash

python3 scripts/epo_data_mapper.py "pa=Trumpf" 1 5

Output: Saves patents to SQLite database

scripts/weekly_report.sh

Purpose: Automated weekly patent intelligence generation Deterministic - Runs on schedule (Monday 9:00 AM via cron) Workflow:

1. Source .env credentials
2. Fetch patents for all monitored competitors
3. Trigger LLM analysis
4. Generate HTML report
5. Send email notification

Usage:

bash

# Manual run
./scripts/weekly_report.sh

# Cron setup (every Monday 9:00 AM)
crontab -e
0 9 * * 1 /path/to/skill/scripts/weekly_report.sh

scripts/database_manager.py

Purpose: Database operations for patent storage Deterministic - Reliable data persistence Functions:

• save_patent() - Store patent with deduplication
• get_patents_by_company() - Retrieve patents by competitor
• get_patents_by_date() - Time-based queries
• get_recent_patents() - Last N days

Usage:

python

from scripts.database_manager import DatabaseManager
db = DatabaseManager()
patents = db.get_recent_patents(days=7)

LLM Analysis Guidelines

When to Use LLM vs Scripts

Use Scripts (Deterministic):

• EPO API authentication
• Data fetching from EPO
• Database storage/retrieval
• Scheduled execution
• File operations

Use LLM (Intelligent):

• Patent relevance assessment
• Strategic importance scoring
• Competitive threat analysis
• Natural language report generation
• Pattern/trend identification
• Business impact evaluation

Analysis Template

For each patent, analyze:

1. Competitive Threat

   • None: Unrelated to client's business
   • Low: Adjacent technology, low impact
   • Medium: Overlapping technology, potential threat
   • High: Direct competitor, core technology
   • Critical: Threatens key business area

2. Technology Alignment

   • CNC_Machining: Turning, milling, machining centers
   • Additive_Manufacturing: 3D printing, laser metal deposition
   • Automation: Robotic loading, Industry 4.0
   • Digital_Manufacturing: IoT, predictive maintenance
   • Other: Specify based on patent content

3. Strategic Action

   • Immediate_review: Patent requires urgent R&D attention
   • Weekly_review: Include in weekly technology meeting
   • Monthly_review: Standard monitoring, monthly assessment
   • Monitor: Track but no immediate action needed

4. Business Impact

   • Describe in 2-3 sentences why this patent matters
   • Connect to client's business strategy
   • Highlight risks and opportunities

Example Analysis Output

text

Patent: "Spindle Lubricator System"
Company: YAMAZAKI MAZAK CORP

⚠️ COMPETITIVE THREAT: Mazak is patenting spindle lubrication technology that 
directly competes with DMG Mori's CNC machining center offerings. This indicates 
Mazak is investing in core CNC technology improvements that could erode DMG's 
competitive advantage in high-precision machining.

📊 TECHNOLOGY ALIGNMENT: CNC_Machining - This is DMG Mori's core business. The 
patent covers spindle lubrication systems which are critical for maintaining 
precision in high-speed machining operations.

⚡ ACTION: Weekly R&D review recommended. DMG Mori should evaluate if this 
technology represents a threat requiring defensive patenting, or if it's 
an opportunity for licensing or collaboration.

🎯 IMPACT: HIGH - Core technology area, direct competitor, potential to 
affect DMG's market position in CNC machining centers.

Database Schema

Table: patents

• id (INTEGER PRIMARY KEY)
• patent_id (TEXT) - EPO patent ID
• title (TEXT) - Patent title
• inventor (TEXT) - Inventor names
• company (TEXT) - Patent assignee
• filing_date (DATE) - Filing date
• publication_date (DATE) - Publication date
• abstract (TEXT) - Patent abstract
• category (TEXT) - Technology category (assigned by LLM)
• technology_area (TEXT) - Specific technology area
• secondary_effects (TEXT) - Side effects/benefits
• image_url (TEXT) - Link to patent document images
• created_at (TIMESTAMP) - When stored

Competitive Monitoring Setup

Step 1: Define Competitors

For a manufacturing client like DMG Mori:

• Trumpf (laser, additive manufacturing)
• Mazak (CNC machining)
• Okuma (machine tools)
• Haas (CNC systems)

Step 2: Define Technology Categories

Match to client's business:

• CNC_Machining
• Additive_Manufacturing
• Automation
• Digital_Manufacturing
• Laser_Technology
• Tooling_Systems

Step 3: Configure Weekly Monitoring

Edit scripts/weekly_report.sh:

bash

COMPETITORS="Trumpf Mazak Okuma Haas"
TECH_CATEGORIES="CNC Additive Automation Digital"

Step 4: Set Up Cron

bash

crontab -e
# Add: 0 9 * * 1 /path/to/skill/scripts/weekly_report.sh

Security & Credentials

EPO API Credentials:

• Store in .env file (not in version control)
• Format: EPO_CONSUMER_KEY=xxx, EPO_SECRET_KEY=xxx
• Script loads via source .env before execution
• Never commit credentials to git

Data Security:

• Database stored locally: data/patents.db
• Reports generated locally: reports/*.html
• No data sent to external services (except EPO API)
• Logs kept locally: logs/*.log

Troubleshooting

EPO API Authentication Failed

Check: .env file exists and contains valid credentials Action: Verify keys at https://developers.epo.org/

No Patents Fetched

Check: Query syntax (e.g., pa=IBM works, pn=EP* may not) Action: Test with simple query first: pa=IBM

Report Not Generated

Check: Database has patents, LLM analysis completed Action: Run weekly_report.sh with debug logging

Cron Job Not Running

Check: Script permissions, cron syntax, paths Action: Test script manually before adding to cron

References

For detailed information, see:

• references/EPO_API.md - EPO OPS API documentation
• references/ANALYSIS_PATTERNS.md - LLM analysis templates
• references/REPORT_TEMPLATES.md - HTML report structure examples
• references/COMPETITOR_SETUP.md - Setting up competitor monitoring