On this episode of FNO InsureTech, Rob Beller welcomes back returning guest Tim Attia, CEO and Co-Founder of Slice Labs, to explore how the company has evolved from early on-demand experiments into a profitable, technology-driven E&S platform serving contractors and specialty risks. Tim shares how Slice’s original vision around on-demand gig economy insurance set the foundation for a much bigger play in small commercial, E&S, and now “upper small” mid-market business, powered by a blend of AI, automation, and human judgment.​

From on-demand niche to E&S engine

Tim traces Slice’s early days building on-demand products for the gig and sharing economy, including innovative but low-premium offerings that performed well on loss but could not scale fast enough to support a large business. COVID became the forcing function to rethink whether a portfolio of small, niche on-demand policies could ever reach meaningful scale, especially as the team realized they had quietly finished building a robust, multi-jurisdiction platform for specialty and E&S lines.​

As the world shifted and specialty markets began growing rapidly, Slice leaned into its E&S capabilities and decided to move up-market, taking the same tech and experience they had refined in small gig risks and pointing it at larger, more complex business. Agents and wholesalers became the focal point, replacing the original consumer-first go-to-market with a strategy that met premium where it actually lived in the US commercial ecosystem.​

Winning over agents and wholesalers

The cornerstone of Slice’s current growth story is an AI- and automation-enabled contractors general liability product distributed through wholesalers, MGAs, and thousands of retail agents. By making it possible to quote and bind an E&S contractor GL policy in minutes, without accord forms, call centers, or long underwriting cycles, Slice removed much of the friction that small-town agents typically face when they try to place specialty business for landscapers, remodelers, electricians, and other contractors.​

Tim explains that agents naturally migrated toward Slice’s experience because it was fast, simple, and built on quality paper, with meaningful capacity and sound underwriting rather than cut-rate forms or excessive exclusions. As premiums grew from roughly 2,9002,900 average policies to cases of 20,00020,000–25,00025,000 and beyond, Slice expanded its appetite, added more mid-sized wholesalers, and layered in fee revenue alongside commission income, further improving the economics of its E&S business.​

Slice Mind, risk DNA, and AI-native underwriting

A major throughline in Tim’s story is Slice Mind, the company’s AI and machine learning layer that has quietly powered the platform for years by classifying businesses, enriching data, and supporting straight-through processing on small commercial risks. By treating each risk as part of a “constellation” with three strands—augmented data, underwriting insights, and performance metrics—Slice builds what Tim calls “risk DNA” that helps the system understand where a new submission sits relative to everything written before.​

Generative AI and modern LLMs are now supercharging this approach, allowing Slice to ingest accord forms, supplementals, and loss runs directly instead of forcing agents to re-key data, and enabling one underwriter to manage far more volume at higher premium levels. For small business, fully automated underwriting has already produced strong loss ratios and profit share performance, while the new “upper small” or “smittle” segment blends machine-driven analysis with a human underwriter in the loop to handle larger, more nuanced risks without blowing up headcount.​

The insurance problem is harder than the tech

Throughout the conversation, Tim emphasizes that while advances in AI and developer tooling are transformative, the truly hard problem is still insurance itself: predicting the future, pricing uncertainty, and capturing the messy, judgment-driven insights that experienced underwriters use every day. He notes that models can become overly rigid or conservative—at one point nearly canceling too many new-business policies—highlighting the need to blend human judgment with machine-driven pattern recognition, especially as the macro environment and risk landscape keep shifting.​

Tim also argues that the last decade of InsurTech experimentation has prepared carriers to embrace this new wave of AI, making them more open, collaborative, and eager to see real, verticalized insurance applications from major tech players like OpenAI, Anthropic, Amazon, and Microsoft. In his view, the next five years will be defined less by generic AI hype and more by specific, measurable improvements in underwriting, claims, and product performance across specialty and E&S markets.​

A bullish view on specialty, E&S, and AI-native insurance

Today, Tim is most energized by specialty and E&S conferences like WSIA and Target Markets, where real capacity, distribution, and business are being built, as opposed to noisy, generic tech events where every booth sounds the same. Slice continues to expand within contractors, add adjacent lines close to construction, and deepen its partnerships with carriers—up to and including getting carrier underwriters onto the Slice platform to see firsthand what AI-enabled underwriting can look like.​

By the end of the episode, listeners will come away with a clear sense of how Slice evolved from a pure on-demand InsurTech into an AI-forward specialty platform, why moving to higher premiums and E&S niches has been so powerful, and how risk DNA, automation, and human expertise can combine to build profitable books of business in a world where insurance remains fundamentally harder than technology.​

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