Building the First “Siri for Insurance”

Liri Halperin Segal opened Episode 51 fresh off a talk at the UN, describing Parliament 51 — a social impact venture she co-founded with Danielle Ofek aimed at closing the gender gap in corporate leadership. While plenty of companies show healthy representation of women lower in the org chart, Liri pointed out, that pattern reliably breaks down at the C-suite. Parliament 51 works with corporates including Dell and Google, helping them apply practical tools — pay equity audits, mentoring programs, and rewritten job postings that don’t unintentionally signal “not for you” to qualified women candidates — to close that gap deliberately rather than hope it closes on its own.

LeO, her current startup, is her second company. Before it, she built Dealiri, an online-and-offline corporate gifting platform in the US. Before that, she ran one of Israel’s leading consumer recommendation websites, and before that, she worked as a journalist covering Israel’s startup scene. Her earliest leadership experience, though, came before any of it: as a soldier in an IDF intelligence field unit, where at 18 she was responsible for dozens of fellow soldiers in the field — an early, if unconventional, run at being “CEO” of a small unit, as she described it.

About Liri Halperin Segal

Liri Halperin Segal is Founder and CEO of LeO, an AI platform built specifically to automate the sales process for insurance agents and brokers, and a vocal advocate for women in tech leadership through Parliament 51, which she co-founded with Danielle Ofek.

The Problem: An Agent Sitting on Data He Couldn’t Use

LeO’s origin story is personal and specific. Liri went looking for a simple homeowners policy, worked with what she describes as a genuinely good agent, and watched him work — and saw how inefficient the process was, and how much of his own data he simply wasn’t using. That gap, not a grand theory about insurance disruption, is what pulled her into the industry. She was explicit about her framing throughout the conversation: LeO isn’t trying to reinvent insurance distribution, just make the existing wheel run better — “not to replace the wheel, but to fix it.”

LeO started in Israel, working directly with local insurance companies and agencies. Once the team recognized the US was the real target market, they built an “ambassador program,” working closely with leading US brokers and agents to get access to real data and understand their actual pain points before building anything further.

Natural Language Querying, and Why the Siri Comparison Only Goes So Far

LeO is built around what Liri called NLQ — natural language querying, a technology related to but distinct from NLP. In practice, an agent can ask LeO a question in plain language — by voice or by typing, while driving, in a client meeting, or prepping beforehand — about a specific client, a prospect, or broader market intelligence, and LeO translates that into a structured query against the underlying data and returns an answer in seconds.

She’s comfortable with the “Siri for insurance” shorthand, but drew a clear distinction: LeO is trained specifically on insurance’s own language and use cases, the kind of shorthand conversation between two agents that an outsider — or a generic assistant — likely wouldn’t follow at all.

LeO integrates with Vertafore’s AMS360, designed as roughly a five-minute onboarding process for any agency already using it, and pulls additional signal from third-party sources including Yellow Pages data, aggregators, and Reuters. One flagship feature is personalized prospecting — rather than a generic list of leads, LeO surfaces prospects that resemble an agent’s existing client base, since it already has visibility into who those clients are. A planned addition at the time of recording: news and financial intelligence tied specifically to an agent’s own clients.

Early Traction and What’s Next

Liri couldn’t share client names on the record, but confirmed one of LeO’s customers is a top-10 US insurance agency, alongside a growing base of Vertafore-connected clients and the agents and brokers in its ambassador program. One signal she watches closely: usage during weekends, which she reads as a strong indicator of how embedded the product has become in an agent’s actual workflow.

At the time of the conversation, LeO was actively hiring salespeople — ideally candidates with insurance industry or SaaS experience, though not required. Liri was also preparing to speak on a data-focused panel with BrokerTech Ventures at the upcoming ITC Vegas.

Advice: Shoe Dog

For her closing recommendation, Liri pointed to Shoe Dog, Phil Knight’s memoir about founding Nike — consumed, true to her stated preference, as an audiobook during flights and long LA drives. She called Knight one of the most interesting people she never expected to want to meet, and pointed specifically to the book’s window into 1960s startup fundraising and Nike’s early partnership history with Japanese suppliers as the details that stuck with her most.

Key Takeaways

• LeO’s founding insight came from Liri’s own experience buying a homeowners policy and watching a capable agent underuse the data he already had access to — not from an abstract thesis about insurance disruption
• LeO uses natural language querying (NLQ), a technology adjacent to but distinct from NLP, to let agents ask plain-language questions about clients, prospects, and market intelligence and get structured answers in seconds
• Integration with Vertafore’s AMS360 was a deliberate design choice to keep onboarding to about five minutes for agencies already using it, rather than requiring a heavier data migration
• Personalized prospecting — surfacing leads that resemble an agent’s existing clients, rather than generic lists — is one of LeO’s differentiated features, enabled by its direct visibility into an agency’s actual book of business
• Parliament 51, Liri’s social-impact venture co-founded with Danielle Ofek, works with corporates including Dell and Google on concrete tools — pay equity, mentoring, rewritten job postings — to close the persistent gap between women’s representation broadly and their representation at the C-suite specifically