YC Root AccessThis AI Startup Is Taking Over Phone Sales
CHAPTERS
- 0:05 – 0:54
Simple AI: an AI voice agent that completes sales calls end-to-end
Cat explains Simple AI’s core product: a natural-sounding voice agent that answers inbound calls and can complete the entire sales flow without human involvement. The agent can explain products, answer questions, collect shipping and billing details, and place orders.
- 0:54 – 1:44
Iconic customer proof: Omaha Steaks runs its main phone line on Simple AI
Jared probes for real customer examples, and Cat highlights Omaha Steaks—an established, large U.S. brand. If you call the number on their website, Simple AI answers and can take orders.
- 1:44 – 3:39
Founders’ origin story: meeting and building software inside Y Combinator
Cat and Zach recount meeting while working at YC on internal products. They describe YC’s software infrastructure (e.g., Bookface) and why software is a “secret weapon” enabling YC to operate at scale.
- 3:39 – 4:47
Catching the startup bug: deciding to build after years around founders
The conversation shifts from background to motivation: working at YC made it hard not to start a company. They cite exposure to alumni stories and early breakthroughs (including OpenAI’s YC Research roots) as a catalyst.
- 4:47 – 5:49
Idea #1: building a “better Siri” (and why it confused users)
Cat explains their initial consumer push: a general assistant that could do many actions like ordering food or calling an Uber. They learned that wide capability sets made the product hard to understand and set expectations for.
- 5:49 – 8:26
Idea #2 goes viral: AI that makes outbound calls for consumers
They discovered that users loved the voice calling feature: having the AI place phone calls on their behalf for tasks like reservations or appointments. Viral stories emerged, including negotiating car purchases across dealerships and long hold-time refund calls.
- 8:26 – 9:30
Why the viral consumer product didn’t monetize: novelty vs repeat usage
Zach explains the retention problem: people thought it was amazing but used it infrequently. Customer interviews revealed users liked it but wouldn’t pay for something they only needed a few times per year.
- 9:30 – 11:27
The pivot trigger: inbound business demand—and a prank call that landed Omaha Steaks
Inbound requests from consumer users asked to deploy the voice technology for business phone lines. The Omaha Steaks CEO tried the consumer app, prank-called their COO, and immediately saw the call-center implications—becoming a major early customer.
- 11:27 – 14:01
Phone sales is mission-critical: Omaha Steaks’ holiday surge and staffing crisis
Cat describes why inbound phone sales matters for Omaha Steaks and similar DTC brands—especially during holidays. Omaha Steaks must scale headcount 15x with temporary workers, creating training/attendance issues and lost revenue from mishandled calls.
- 14:01 – 16:31
Deploying in the real world: integrating with 1990s-era systems and on-prem constraints
They share what it took to implement Simple AI at Omaha Steaks: two weeks on-site, understanding workflows, and integrating with legacy AS/400 terminal systems and slow-change IT processes. The integration effort became part of the company’s operational playbook.
- 16:31 – 20:26
From product catalogs to SKUs: teaching the agent to sell complex inventories
The agent must navigate messy, real-world product complexity: variants, bundles, promos, regional offers, and source-code driven campaigns. The founders describe translating this operational knowledge into an AI system that can confidently complete orders.
- 20:26 – 23:54
Performance edge: 30% better upsell than trained reps + personalization experiments
Cat claims the AI outperforms trained, full-time agents on upsells—key to unit economics in phone sales. They also describe new levers: changing voice/accent, tailoring to demographics and customer history, and rapid A/B testing via prompt updates.
- 23:54 – 26:56
Beyond labor replacement: better customer experience through memory and conversation
They argue the AI can improve—not just cheapen—customer interactions by removing handle-time pressure and remembering personal preferences. Examples include customers sharing life stories and the system retaining preferences like not offering chicken again.
- 26:56 – 29:00
Company momentum: launch timing, funding, hiring, and building premium-quality voice AI
Cat and Zach share milestones: launching the current product about a year prior, growing from 2 to 10 people recently, opening a San Francisco office, and raising $14M. They emphasize a premium strategy—spending on latency and quality rather than racing to the bottom on cost.
- 29:00 – 35:18
Technical moat: latency, custom models, evaluation, and guardrails for reliability
Zach outlines the hardest engineering problems: responding in under ~600ms, building evaluation suites, fine-tuning models per customer, and solving long-tail issues like address transcription. They also stress orchestration/guardrails to prevent hallucinations and ensure correct order placement.
- 35:18 – 37:13
Founder lessons: don’t over-plan—talk to users early and follow demand
In closing, they reflect on iterating through three ideas and leaning heavily on user feedback. Their advice: start building, talk to users even when you only have a handful, and trust you can learn new domains if the problem is real.
