PatSnap vs Stiltn

PatSnap provides AI-driven innovation intelligence for intellectual property, research and development, materials science and drug discovery. It is aimed at R&D leaders, IP professionals, engineers, scientists and researchers. PatSnap says its data covers more than 2 billion structured data points across patents, science, litigation and technology; its Open Platform provides more than 210 million global patent and science records. Open Platform use cases include patent search and analysis, competitive intelligence, R&D innovation and patent application support. Developers can connect through REST APIs, MCP servers, UI widgets and Agent Skills. Listed options include Python, Node.js and Java SDKs, MCP support for Claude Desktop and Cursor, React and Vue widgets, and Agent Skills for LangChain and AutoGen with more than 140 atomic tools. PatSnap states that products are available in cloud or on-premises deployments. It says it holds SOC 2 Type 1 certification and meets ISO 27001:2022 standards, and that user data is encrypted in transit and at rest using TLS 1.3 and AES-256. Its proprietary LLM does not use customer data for pretraining or retraining. Plans include a free Basic tier; the pricing note lists a starting price of $200/mo and a 14-day trial.

Stiltn is an AI platform for patent practitioners, with tools for search, drafting, competitor monitoring, and portfolio assessment. Its semantic search covers more than 150 million patents and provides explanations and claim mapping. Drafting support includes invention disclosures, patent applications, claim generation, and office action responses. Monitoring follows patent filings and application changes, then classifies alerts by relevance. Portfolio analysis considers legal defensibility, economic value, and competitor activity to make recommendations. Stiltn says it covers more than 50 patent offices, including USPTO, EPO, WIPO, JPO, KIPO, and CNIPA. Bulk imports are available from PatSnap, Anaqua, CPA Global, and standard PAIR or Espacenet exports. Deployment options are cloud, private cloud, or on-premises, with EU or US processing and storage choices and configurable retention controls. The company says customer data is not used to train models, and AI outputs link to source documents. Evaluation access costs nothing and includes full platform access, dedicated onboarding, and custom configuration; pricing beyond evaluation is on request.