DeepIP is an AI-native patent platform built on TypeScript, Python, React, and a multi-model LLM stack (OpenAI, Anthropic, Google Generative AI via LiteLLM and Langchain). The company is aggressively hiring across sales (6 roles) and engineering (3 roles) while operationalizing production-grade AI systems—RAG pipelines, prompt management, and an AI copilot for IP professionals. Active projects signal a shift from product depth toward go-to-market maturity: sales playbook refinement, tier-1 account-based marketing, and partner ecosystem development alongside AI feature expansion into the French market.
Notable leadership hires: Head of Marketing
DeepIP builds an AI platform for patent practitioners to reduce drafting, prosecution, and portfolio-management overhead across the patent lifecycle. The platform integrates AI-powered drafting assistance, prior-art analysis, and portfolio tools into a single workspace, targeting IP departments at mid-market and enterprise organizations globally. Founded in 2023 and based in Brooklyn, the company operates at 11–50 people with hiring accelerating across the U.S. and France. Pain points signal operational scaling: aligning marketing, sales, and growth functions; building customer success infrastructure; and reducing external recruiting dependency while achieving $12–14M revenue targets.
DeepIP integrates OpenAI, Anthropic, and Google Generative AI via LiteLLM and Langchain. The stack supports RAG pipelines and prompt-management components for production AI systems.
Yes. DeepIP has 3 active engineering roles (mix of mid, senior, and lead levels) across 15 total open positions. Hiring is accelerating in the United States and France.
Core projects include an AI copilot for IP professionals, production-ready LLM integrations, French-market expansion of AI drafting, partner ecosystem development, and sales/marketing process automation to drive growth toward $12–14M.
DeepIP's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.