AI-powered legal document drafting and review for Microsoft Word
Definely builds legal-document software delivered as a Word add-in, letting lawyers draft, review, and understand contracts without leaving their existing workflow. The tech stack reveals a modern cloud-native approach—TypeScript, React, Python, Kubernetes, Docker—paired with graph-database reasoning (Neo4j, LangGraph, RAG), suggesting the product leans heavily on semantic search and AI-assisted clause analysis. The hiring profile (security, ops, and engineering focused; 7 roles in 30 days, accelerating) and active projects (ISO 27001, SOC 2, AI certification readiness) show a compliance-first posture critical for selling into regulated legal teams.
Definely is a London-based LegalTech platform founded in 2017, serving lawyers and legal teams at mid-market and enterprise law firms. The product integrates into Microsoft Word as an add-in, enabling users to access clause definitions, cross-document references, and AI-powered contract insights without breaking context. The company employs 51–200 people and is currently scaling operations around security compliance, people processes, and platform infrastructure to support customer growth. Recent initiatives include ISO 27001 and SOC 2 audit completion, AI certification readiness, and a trust-center powered by Safebase.
TypeScript, React, Python, .NET, Azure, AWS, Kubernetes, Docker, Neo4j, LangGraph, and RAG for AI reasoning. Sales and ops tools: HubSpot, Gong, Ashby, Drata, and Zapier.
Actively working toward ISO 27001 and SOC 2 audit completion, and driving ISO/IEC 42001 AI certification readiness. Trust center powered by Safebase is live.
Definely'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.