Lawgeex is a technology company.
Lawgeex has raised $35.0M across 3 funding rounds.
Lawgeex has raised $35.0M in total across 3 funding rounds.
Lawgeex is a legal tech company that builds an AI-powered platform for automating contract review, redlining, and negotiation. It serves in-house legal teams at enterprises, solving the bottleneck of manual contract reviews for routine agreements like NDAs and vendor contracts by flagging issues, applying company playbooks, and accelerating approvals—saving up to 80% time, 90% costs, and delivering 209% ROI per Forrester analysis.[1][4][5] Customers include GE Power Conversion and pharmaceutical suppliers, with proven efficiency gains like 85% faster turnaround and 94% AI accuracy outperforming lawyers' 84% in studies.[2][5][6]
The platform combines machine learning, NLP, and contextual intelligence with human Legal QA for precision, reviewing millions of contracts to match experienced attorneys while enabling strategic focus.[1][4][5]
Lawgeex was founded in 2014 by Noory Bechor, a corporate lawyer with 8 years of experience who identified contract review as a major friction point for legal departments, and Ilan Admon, his school friend and an AI expert serving as CTO.[1][2] Bechor's insight came during his legal career, recognizing AI's potential to understand legalese despite its early adoption stage, leading them to pioneer Contract Review Automation (CRA) as a new category.[1]
Early traction included a landmark study where their AI reviewed NDAs in 26 seconds versus lawyers' 92 minutes, gaining attention as a disruptor despite skepticism.[2][6] By 2022, it pivoted successfully to enterprises, achieving profitability in that division with a mature product and large customer base.[2]
Lawgeex rides the legal AI wave, transforming "legal tech" into a vertical by automating routine tasks amid rising AI adoption in enterprise software.[1][2] Timing aligns with post-2014 NLP advances and demand for efficiency in fast deal cycles, especially in regulated sectors where manual reviews slow sales.[2][4]
Market forces like high contract volumes, cost pressures, and AI maturity favor it—enterprises embrace hybrid human-AI models for 75-85% turnaround cuts, influencing ecosystems by standardizing CRA and freeing lawyers for strategy.[2][5] It sets benchmarks, as seen in studies outperforming humans, pushing competitors toward contextual intelligence over basic flagging.[6]
Lawgeex's enterprise profitability and maturing AI position it for expansion into more contract types and global markets, leveraging ongoing training for even higher accuracy.[2][5] Trends like generative AI integration and regulatory pushes for efficiency will amplify its edge, potentially evolving influence through deeper analytics and playbook standardization across industries. As a pioneer proving AI's legal ROI, it exemplifies how tech unlocks business speed, circling back to Bechor's vision of legal powering innovation.[1][4]
Lawgeex has raised $35.0M in total across 3 funding rounds.
Lawgeex's investors include Aleph VC, Angelic Ventures, Founder Collective, LAUNCH, Redline Capital, Samsung NEXT Ventures, Uncork Capital, 14W, lool ventures, Eilon Tirosh, Rami Lipman, Yossi Matias.
Lawgeex has raised $35.0M across 3 funding rounds. Most recently, it raised $20.0M Series C in May 2020.
| Date | Round | Lead Investors | Other Investors |
|---|---|---|---|
| May 1, 2020 | $20.0M Series C | Aleph VC, Angelic Ventures, Founder Collective, LAUNCH, Redline Capital, Samsung NEXT Ventures, Uncork Capital | |
| Apr 1, 2018 | $12.0M Series B | Aleph VC, Redline Capital, Samsung NEXT Ventures | |
| Nov 1, 2016 | $3.0M Series A | 14W, Aleph VC, Angelic Ventures, lool ventures, Eilon Tirosh, Rami Lipman, Yossi Matias |