Insurance Security Solutions

Horizontal AI is great for emails. Vertical AI? That’s where the real transformation happens in finance and insurance. Horizontal AI (like Microsoft Copilot Studio) vs. Vertical AI (like Multimodal): 1. Copilot Studio tackles simpler, horizontal use cases (email automation, customer support) 2. Multimodal focuses on complex, vertical-specific processes in finance/insurance Why Vertical AI is the game-changer: • Tackles complex middle/back office processes (loan origination, claims processing) • Incorporates company-specific knowledge into AI agents • Adjusts model weights for specialized tasks • Requires deep vertical domain expertise Prediction: We'll see more vertical-specific AI platforms emerge for healthcare, government, and manufacturing. The takeaway? Use horizontal AI for simpler tasks, but for complex, industry-specific workflows, vertical AI is the future. Curious to hear your thoughts. What's your experience with AI in your industry? P.S. If you want to learn more about how vertical AI is transforming finance and insurance, let's connect. Always happy to geek out about this stuff!

Going all-in has transformed Indico from generic IDP vendor in a sea of me-too products to a fast-growing, laser-focused solutions provider. Last week I caught up with Indico's Tom Wilde (CEO) and Jeremy Stinson (SVP Marketing) and they shared some fascinating insights into how placing all their chips on the insurance industry has also transformed the product into an agentic insurance decisioning platform. The team walked me through the new Agent Studio using insurance claim submission examples. IDP is still an important piece but not the main thing anymore. Indico also added new workspace functionality for underwriters and other insurance knowledge workers after the IDP workflow ends. Doubling down on the insurance industry has paid off in spades, with higher growth, better margins, and a clear product direction for the team. * ~70% of annual recurring revenue (ARR) now comes from insurance customers. * Insurance represents ~95% of the sales pipeline. * Average contract value (ACV) has doubled. * On track to grow ARR by 50% this year. Indico’s transformation from a generalized IDP platform to a focused insurance decisioning solution is a stellar example of the strategic clarity and discipline we champion. By going all-in on the insurance vertical, the company didn’t just refine its product. It redefined its identity, aligned its technology, and changed the user experience to deliver data-driven decisioning. Read more and get the Deep Analysis in my new blog "Going All In at Indico". https://lnkd.in/eiRCddBG Indico Data

The next $300B company won’t be a general AI tool. It’ll be a vertical AI agent that understands boring better than anyone else. According to Y Combinator, vertical AI agents — laser-focused on specific domains — could be 10x bigger than SaaS. Why? Because they don’t just replace software. They replace software + labor, especially the kind that nobody wants to do. ✔️ Think of the underwriting assistant who never sleeps. ✔️ The placement coordinator who knows every carrier appetite. ✔️ The new hire who shows up on Day 1 already fluent in 750+ class codes. AI agents that target "butter-passing jobs" (read: repetitive admin tasks that drain your smartest people) are poised to dominate. In commercial insurance, we’ve got a buffet of those. That’s exactly where Linqura's AI lives. Built on our LINQ 2.0 platform, it doesn't just understand insurance — it thinks like your best commercial agent. It learns your hierarchy. It memorizes carrier appetites. And it gives every agent superpowers on Day One. We’re not building tools. We’re replacing inefficiency. And if you’re betting on vertical AI, commercial insurance isn’t just ripe — it’s overripe. Deep vertical AI is the future of insurance sales, service and underwriting. And it’s not coming someday. It’s already live. This is the way. Hanley

When discussing promising areas in insurtech with our Foundation Capital Beacons group, I spotlit 2 specialized vertical SaaS models showing particular potential: 1 - AI-enabled claims prioritization Our portfolio company EvolutionIQ exemplifies this, leveraging AI to identify and resolve high-risk long-tail disability cases. The focus is providing an intelligent "co-pilot" to augment human claims assessors. 2 - Insurance-specific payments/treasury New startups are emerging to manage payments and cash flow, powered by AI automation tailored to insurance needs. Unlike generalized software, these narrow solutions concentrate on alleviating key pressure points. And rather than whole-scale replacement, they act as assistants enhancing specific roles. 🎥 Watch for more. Which specialized AI applications do you think hold the most disruptive potential? Let me know in the comments!

If you niche down correctly, your agency might not get acquired by another brokerage. It'll get acquired by a SaaS company. Most agency owners don't even realize this is happening. They're so locked into the old playbook that they miss the bigger opportunity. A vertical-specific agency doesn't just sell insurance. It controls distribution, data, and trust inside one industry. And that is exactly what SaaS companies want more than anything else. Think about it. If you build a niche contractor insurance agency, who has more to gain from owning your book of business? Another generalist agency… or a software company like ServiceTitan that already sells to the same contractors every day? ServiceTitan has the audience. You have the trust. Together, they own the entire customer relationship. Same thing in restaurants. If you run a niche restaurant insurance agency, Toast could buy you tomorrow and instantly bolt insurance into their ecosystem. This is the part agency owners miss. When you niche, you're not just building an insurance agency. You're building: • A distribution channel • A data engine • A retention machine • A customer relationship SaaS companies would kill for SaaS companies have churn problems. Insurance agencies don't. SaaS companies struggle with distribution. Insurance agencies don't. And if you own a niche with 500, 800, 1,200 clients who all look the same, think the same, buy the same policies, and operate with the same risks, your agency becomes insanely attractive. Not because of commissions. Because of the data. Who else has payroll, revenue, fleet size, job types, safety practices, experience mods, loss history, and employee count for thousands of contractors? You do. The future winners aren't generalists. It's the vertical-specific agencies. The ones that become so embedded in a single industry that SaaS companies start circling them the way private equity used to. If you want an exit in the next 5 to 10 years, niche agencies will have options generalists simply won't. The whole game is shifting. And most agency owners haven't noticed yet.

Horizontal AI solutions are appealing because the market seems massive. But we learned early on that this is a tough way to win, so we did the opposite instead. To be fair, companies like Slack and Dropbox proved horizontal solutions can work at scale. That unlimited TAM is attractive but if you’re building a startup you have limited resources and very little time. You need to pick one thing you can solve really well. That's way easier when you go vertical and become an expert in one industry. The foundation can be the same - integrations, workflows, and AI agents. But the specifics are what actually matter. With horizontal, you're giving customers an empty canvas. They can build an AI agent that picks up the phone and answers questions, but they have to figure out everything from scratch. With vertical, you're giving them a platform optimized out of the box. For a carrier, we can say "here's an agent that handles first notice of loss, and it's already integrated to your claims management system so it can fully complete the task." That’s not a “voice AI agent”, that’s an end to end system. The difference is saving months of configuration work and hitting 80% automation rates instead of 20%. One requires a lot of investment and internal resources. The other is ready to go, works better, and is purpose-built for insurance workflows. For insurance companies evaluating AI vendors right now, this matters. Ask if they're giving you a blank canvas or a solution that already understands your workflows, your integrations, and your industry terminology. Your odds of success are completely different.

E&S carriers compete on speed and specialization, but the data stack most of them rely on isn't built for either. Rate filings don't exist the way they do in admitted lines, so pricing a risk means selecting the right admitted comparators and adjusting from there. That selection is the expert work, not a preprocessing step. And the legacy data subscriptions the industry runs on deliver raw information without a native analytics layer, so an analyst still spends weeks stitching, normalizing, and pivoting before an underwriter can act on it. At Effective AI, we've built that middle layer. The agent pulls exposure characteristics, selects comparators aligned to the specific risk, and delivers the analytical view in the format the underwriter already reasons in. FutureProof, an AI-native MGA, uses it in production to support four E&S programs across Florida, California, and Texas, with expansion into eight additional states underway on the platform. What used to take 6 weeks is now a 3-day pass, and their underwriters are deciding from a richer, more current view of the market than a manual process could produce. Read the case study: https://lnkd.in/gsm7SJq3