With Harvey and Legora rapidly securing nine-figure funding rounds, legal tech has emerged as one of the fastest-growing and most fiercely competitive sectors for AI startups. However, while these tools cater to private practice, some startups believe a significant portion of the legal market remains underserved. Sandstone, which announced a $30 million Series A funding round on Tuesday, is zeroing in on a neglected segment of the legal industry: the complex web of overlapping tasks and systems faced by in-house legal teams.

The Series A round was led by Lightspeed Venture Partners, with participation from existing investors including Sequoia, Mantis VC, SV Angel, Operator Partners, Kearny Jackson, Daybreak Ventures, Litquidity Ventures, and others. This funding comes just six months after a $10 million seed round in January, which was led by Sequoia. As the founders explain, Sandstone’s initial user base will be the legal departments of small and mid-sized businesses. "AI helps them route and triage that work appropriately, and then they can build custom workflows on top of our platform to actually execute work, whether that’s drafting, reviewing, or providing legal analysis."

The result has little in common with legal reasoning systems like Harvey and Legora. Instead, Sandstone focuses on relationship management and workflow automation, both tailored to the unique demands of in-house legal work. According to Strydom, the emphasis on in-house legal departments allows Sandstone to deliver value where more generalized AI deployments often struggle. "One of the convictions of Lightspeed was that they really believe in highly specialized vertical AI," Strydom says, "because it takes a granular understanding of workflows to really nail down how AI can help."

Sandstone will also face intense competition from frontier AI labs, which are increasingly directing their attention to the legal sector. Anthropic has been steadily expanding its Claude for Legal offering, adding new tools in May for case law searches and deposition preparation.