Genie AI

Genie AI is a legal technology company that provides an AI-powered platform for drafting, reviewing, and negotiating legal documents. Founded in 2017 by Rafie Faruq (CEO) and Nitish Mutha (CTO), the London-based startup aims to make legal services more accessible and efficient. The founders, who both hold MSc degrees in Machine Learning from University College London (UCL), were inspired to apply generative AI to the legal field, recognizing that legal contracts are highly structured documents.

Rafie Faruq has a background in philosophy, economics, and was a former derivatives trader before co-founding Genie AI. Nitish Mutha worked as a software engineer for five years prior to pursuing his master's at UCL, where he was taught by creators of Deepmind. Their combined expertise in AI and Faruq's interest in creating social impact led to the development of Genie AI. The company initially focused on serving large law firms but pivoted to a self-serve model to directly empower end-users.

The platform's core offering is an agentic legal AI that automates tasks such as contract drafting, risk analysis, and negotiation support. It features a proprietary editor that is compatible with DOCX formats and handles track changes. Users can generate personalized agreements from scratch by describing their needs in plain language, review documents for potential risks which are flagged in a color-coded system, and access an open-source library of legal templates. The AI assistant can also suggest alternative language to mitigate risks. The platform serves a wide range of clients, from startups and small to medium-sized enterprises to large corporations, including FTSE 100 companies and Global 200 law firms. The business model is primarily based on annual subscription fees determined by usage, with a freemium option available.

Genie AI has secured significant funding, including a Series A round of approximately $17.8 million (£13.3 million) led by GV (Google Ventures) and joined by Khosla Ventures, bringing its total funding to over $20 million. This investment is intended to fuel further product development and expansion into the U.S. market. The company emphasizes data privacy and security, stating that user data is not used to train its AI models and is protected by 256-bit encryption.

Keywords: AI legal assistant, contract automation, legal document drafting, legal document review, AI contract negotiation, generative AI, legal tech, contract lifecycle management, risk analysis, legal templates, proprietary editor, self-serve legal, agentic AI, legal software, contract management, document automation, AI-powered editor, legal clause library, legal risk mitigation, contract analysis