Developing AI Intellectual Property Management System
IP Management — tracking, protecting, and monetizing intellectual property objects: patents, trademarks, copyrights, trade secrets. AI automates routine: infringement monitoring, competitor analysis, registry maintenance.
IP Management System Components
IP Registry: unified database of all company IP objects with metadata, deadlines, statuses.
Infringement monitoring: automatic internet, marketplace, registry monitoring for unauthorized brand and technology use.
Patent analysis: monitor new competitor patent applications, prior art search, patentability assessment.
Automation: renewal deadlines, international applications, patent office communications.
Trademark Infringement Monitoring
class TrademarkMonitor:
def monitor_infringements(self, trademark: Trademark) -> list[InfringementAlert]:
alerts = []
# Marketplace search
for marketplace in ["major_platforms"]:
results = marketplace_api.search(trademark.name)
for item in results:
similarity = self.compute_visual_similarity(item.image, trademark.logo)
text_similarity = self.compute_text_similarity(item.title, trademark.name)
if similarity > 0.8 or text_similarity > 0.85:
alerts.append(InfringementAlert(
source=marketplace,
url=item.url,
similarity_score=max(similarity, text_similarity),
type="counterfeiting"
))
# Registry search for new similar applications
new_applications = registry_api.get_new_applications(
nice_classes=trademark.nice_classes,
date_from=self.last_check
)
for app in new_applications:
if self.compute_text_similarity(app.name, trademark.name) > 0.7:
alerts.append(InfringementAlert(
source="Registry",
url=app.url,
type="confusingly_similar_registration"
))
return alerts
Patent Landscape
Competitor patent landscape analysis:
- Monitor new patent applications (USPTO, EPO, international offices)
- Classification by technology area (CPC, IPC codes)
- Patent landscape visualization (technology × company × time)
- "White space" analysis — technology areas without competitor patents
APIs: Google Patents API, Lens.org API, EPO Open Patent Services.
Prior Art Search
When developing new technology: prior art search (existing patents and publications) before filing:
def search_prior_art(invention_description: str) -> PriorArtReport:
# Generate search queries via LLM
queries = llm.generate_patent_queries(invention_description)
# Search patent databases
patents = patent_db.semantic_search(invention_description, top_k=20)
# Assess relevance
relevant = [p for p in patents if cross_encoder.score(invention_description, p.abstract) > 0.6]
return PriorArtReport(
relevant_patents=relevant,
novelty_assessment=llm.assess_novelty(invention_description, relevant),
patentability_risks=llm.identify_risks(relevant)
)
IP Portfolio Valuation
AI model assesses patent portfolio value based on: citation count, age, breadth, licensing revenues. Used in M&A and financial reporting (IAS 38).
Implementation Timeline
Months 1–2: IP registry, basic trademark monitoring
Months 3–4: Patent monitoring, prior art search
Months 5–6: Integration with international offices, automated deadline management
Months 7–8: IP analytics and reporting, portfolio valuation