Inside In-House: What It's Really Like to Be In-House Counsel for a Legal Tech Vendor

Executive Summary Jared sits down with Carly Savar, general counsel at Steno, to unpack what actually happens when a law firm signs up with an AI vendor. Carly explains why reading the fine print matters more than any feature list, and what separates a vendor you can trust from one that's just telling you what you want to hear.

Key Takeaways Read the actual data processing agreement yourself. Don't assume a vendor's security is handled just because they signed a service level agreement.

Push for a zero-day retention agreement, and ask about the LLMs your vendor is built on, not just the vendor itself.

SOC 2 Type 2 certification means a company's controls held up over a full year. SOC 2 Type 1 only proves a single snapshot in time.

Not all training is created equal. Aggregated usage data is usually fine. Your client's confidential content should never go into a model.

New billing ethics guidance says you can only charge for the time you actually spent, not the time an AI tool saved you.

About the Guest Carly Savar is general counsel at Steno, a litigation support and court reporting technology company. She spent years litigating before founding her own legal recruiting company and eventually moving in-house. Carly now negotiates AI and data agreements from both sides of the table, as counsel to a legal tech vendor and as a buyer evaluating other vendors herself.

Links and Resources Steno: steno.com

Red Cave Law Firm Consulting: redcavelegal.com

Keywords legal tech, legal technology, AI for lawyers, AI vendor vetting, legal AI vendor contracts, data security for law firms, zero-day retention agreement, SOC 2 Type 2, SOC 2 certification, ISO 27001, shadow AI, in-house counsel, legal tech general counsel, court reporting technology, Steno, AI training data, law firm AI policy, small law firm technology, technology competence rule, Red Cave Law Firm Consulting

Episode Chapters 00:00:00 Cold open and show intro

00:02:00 Meet Carly Savar and the vexing AI vendor problem