Patsnap delivers AI-driven insights for IP and R&D workflows, serving over 15,000 companies globally. The stack (Python, Claude, Kafka-adjacent patterns via Kubernetes) and active adoption of RAG underscore a shift toward retrieval-augmented generation for patent and research data—a critical moat for domain-specific LLM reliability. Hiring acceleration is heavily sales-driven (21 of 33 open roles), with projects spanning partner enablement and AI-driven sales tools, indicating a transition from product-led to go-to-market expansion.
Patsnap builds an AI intelligence platform for intellectual property and R&D teams at enterprises and mid-market innovators. The core offering combines proprietary patent databases, scientific research data, and a domain-specific LLM (Hiro) to deliver insights across competitive intelligence, IP portfolio management, and M&A due diligence workflows. The company operates across life sciences, pharma, materials, and tech verticals, with 501–1,000 employees headquartered in Singapore and expanding hiring across the US, UK, China, Japan, and Canada. Current focus is accelerating sales execution and channel partnerships to drive enterprise adoption.
Core stack includes Python, Claude, Java, Spring Boot, Docker, Kubernetes, and AWS. The platform is adopting RAG (retrieval-augmented generation) to enhance data retrieval for its domain-specific LLM, Hiro.
Patsnap powers over 15,000 companies globally for IP and R&D intelligence, with claimed productivity gains of 75% in IP workflows and 25% reduction in R&D waste.
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