From Risk-Averse to AI-Powered: How Responsiv Built Trust with In-House Legal Teams

Selling AI to lawyers isn’t just a technology challenge – it’s a trust challenge. In a recent Category Visionaries episode, Responsiv founder Jordan Domash revealed their strategy for winning over one of the most risk-averse professional groups.

“You don’t want to get something wrong. And their whole job is managing risk for the company,” Jordan explains, highlighting the fundamental challenge of selling to legal teams. This risk aversion shapes every aspect of the buying process, from initial engagement to final implementation.

The key was acknowledging legitimate concerns rather than dismissing them. “There’s incredible interest and it’s really easy to get a attorney to take a demo of what we’re building. But at the same time there’s a natural concern for folks that aren’t really close to the underlying tech,” Jordan notes. These concerns centered on two critical issues: AI hallucination risk and data privacy.

Rather than rushing to market, Responsiv took a measured approach. They started with design partners from Jordan’s legal tech network, people who “believed in the vision and identified the pain point that were articulating.” This careful start allowed them to build credibility through successful implementations.

Their focus on in-house counsel rather than law firms proved crucial. “Most of our peers that are building legal research tools are actually get the bulk of their spend from law firms… For us, basically we’re the anti traditional legal research tool and that we’re hyper focused on the corporate use case.” This specialization helped them build trust through deep understanding of specific needs.

The strategy worked. “Most of the new customers that we’ve signed in the past month or two have come from referrals from existing customers,” Jordan reveals. They achieved this growth without traditional marketing – their product waitlist and word-of-mouth referrals created natural demand.

Success required navigating complex budget dynamics. As Jordan explains, “There’s budget for in house people and tools. And then there’s also a separate budget that often rolls up to the general counsel in terms of outside council spend.” By positioning their solution as a way to reduce outside counsel spend, they made the ROI clear while addressing risk concerns.

Their experience building AI tools at Relativity provided crucial credibility. “I’ve been building AI enabled tools for attorneys for ten years,” Jordan notes. This track record helped them address concerns about AI adoption: “There’s been AI in this industry for a decade, but it’s been a long journey getting acceptance even in that specific vertical.”

The lesson for founders targeting risk-averse markets? Deep domain expertise matters more than technical innovation. “I don’t know if they have a appreciation for the complexity of some of these really narrow workflows. And it takes a long time to get up to speed on what you really need to deliver around the product to actually be used by a legal team or an attorney.”

By focusing on specific workflows, building trust through early adopters, and growing through product success rather than marketing spend, Responsiv created a playbook for bringing AI innovation to conservative markets. Their story shows that sometimes the best way to drive adoption isn’t to push technology harder – it’s to understand and address the fundamental concerns of your target users.