Intake that sorts itself
How an AI-assisted intake flow helped a small firm sign 60% more clients while spending less total time on calls.
- Company
- Frontier Law Center, an employment law firm
- Role
- Director of Growth & Operations
- Years
- 2021–2026
The problem
Inquiries more than doubled, from about 150 a month to 350, and every one got the same treatment. A warm referral and a cold web form landed in the same queue, calls averaged an hour and a half, and the best leads waited their turn.
What I built
- Automated screening that sorts each inquiry by what the lead actually needs and routes it to the right person.
- Calls recorded and transcribed automatically, so nobody takes notes by hand and nothing gets lost in the handoff.
- Intake connected to the litigation CRM, so each lead's history follows it from first contact to signed client.
- Redesigned the intake flow to separate warm transfers and high-value matters from standard inquiries, so priority leads get to the right person faster.
- Mapped the full journey from first contact to signed client, and tightened the handoff between intake and onboarding.
- Put the team on one scoreboard: signed clients and cost per acquisition.
The result
- +60%
- signed clients in six months
- 37 min
- average client call, down from 1.5 hours
- 150 → 350
- monthly inquiries, handled faster
The work made the firm a Legalweek "Best Use of AI" finalist, a boutique firm on a list with Baker McKenzie, King & Spalding, and Reed Smith.
Why it travels
The fastest way to grow is to stop treating every lead the same. That's as true for a SaaS trial funnel or an inbound sales team as it is for a law firm.
Building something that needs to grow without breaking?
I'm looking for a director-level role in marketing, growth, or operations at a company that wants AI doing real work. I'm based in Thousand Oaks and open to hybrid or on-site roles from Ventura County to Calabasas and the San Fernando Valley, or remote.
