Full Episodes | Insurtech Leadership Podcast

Medical malpractice is one of the most established specialty lines—and one of the hardest to modernize. In this episode of the InsurTech Leadership Podcast, Joshua Hollander sits down with Jared Kaplan, Co‑Founder & CEO of Indigo Technologies, to unpack why MedMal is finally ready for a different underwriting and distribution model.

Indigo’s bet: you can make MedMal dramatically easier for physicians and brokers without relaxing underwriting discipline—by replacing slow, form-heavy workflows with alternative data, machine learning, and tight operational execution.

Guest Bio

Jared Kaplan is the Co‑Founder and CEO of Indigo Technologies. Indigo is rethinking medical malpractice insurance with an approach that combines broker-friendly distribution, faster quoting, and underwriting models informed by large-scale claims data and alternative data signals.

Key Topics

-Why MedMal is “built to resist change”: entrenched processes, long feedback loops, and the real cost of underwriting mistakes.

-Underwriting without an application: what replaces the traditional intake and how you maintain discipline.

-Alternative data in a high-stakes line: how Indigo uses a broad feature set (beyond prior claims history) to improve risk selection.

-Risk segmentation and value creation: lowering premiums for the “overpaid” majority while avoiding the concentrated loss drivers.

-The 80/20 claims reality: the small portion of physicians that drives a disproportionate share of MedMal claims.

-Brokers as the distribution partner of the future: what modern carriers/MGAs must do to earn broker trust and share.

-Operating model over buzzwords: where the real leverage is—quote speed, workflow simplicity, and consistency.

Quotes

-Jared: “We started with the premise that you don’t need an application.”

-Jared: “I would argue Indigo is the baby of both… online distribution… and underwriting using alternative data and machine learning.”

-Jared: “There’s no one else there that can figure out the twenty percent of docs that are driving sixty percent of the claims.”

Resources

Indigo Technologies (company site): https://www.getindigo.com/

Jared Kaplan (LinkedIn): https://www.linkedin.com/in/jared-kaplan-683412/

If you work in specialty insurance, broker distribution, MGAs, or underwriting modernization, this one is a pragmatic look at where AI actually earns its keep.

Subscribe for more operator-grade conversations on insurtech, insurance innovation, and leadership—and if you found value here, leave a review to help more executives discover the show.

Introduction

Josh Hollander sits down with Vishal Sankhla, Co‑Founder & CEO of OutMarket, to get specific about what “AI in insurance” looks like when it actually changes operations. The focus is commercial insurance workflows—where work still runs through email, PDFs, spreadsheets, and agency management systems—and how to cut cycle time and errors without creating new risk.

Guest bio

Vishal Sankhla has led product teams at Uber and Meta and previously served as Head of Product at Ethos Life, helping build profitable acquisition channels, the underwriting engine, and the agency partners business. At OutMarket, he’s building an intelligence layer for commercial insurance: agent-assisted workflows that make teams faster and more consistent.

Key topics discussed

• Why AI pilots stall: fragmented data, manual handoffs, and inconsistent processes across the submission-to-bind journey.
• Data first, workflows second: where insurance data lives, how it breaks, and why workflow redesign is the unlock.
• Policy intelligence: turning policies into structure so teams can summarize coverage, surface gaps, and improve proposals.
• Servicing and renewals: reducing back-and-forth, re-keying, and avoidable errors with agent-assisted workflows.
• Integration reality: fitting into agency management systems and carrier ecosystems instead of trying to replace them.
• Measuring impact: cycle time, hit rate, and error reduction (not vanity metrics).
• Trust, privacy, isolation: what it takes to earn permission to touch sensitive client data.

Quotes

• “Because so much of this is happening manually, I think a lot of this data tends to get very, very fragmented.”
• “we built workflows that now literally allow them to drag and drop, and within a few seconds, they know exactly a quick summary”
• “We've seen a lot of use cases where people are now winning their businesses because of some AI workflows.”

Resources mentioned

• OutMarket
• Uber
• Meta
• Ethos Life

Call to action

Subscribe for more operator-grade conversations on insurance and insurtech. On YouTube, drop a comment with the workflow you’d most like to fix—and why it’s stuck today.

Most "core modernization" programs fail for one boring reason: fragmentation. Not the tech. The contract sequencing, the
handoffs, the Excel that becomes the unofficial system of record-and the silent operational risk that follows. If you're still
running underwriting, claims, billing, and reinsurance as separate truths, you're not modernizing. You're just integrating
failure modes.

Rob Lewis, CEO of INTX Insurance Software, has built and operated carriers and a reinsurer across Africa, Europe, and now
the U.S .- and he's watched the same breakdown repeat: end-to-end change gets blocked by sunk contracts, so teams
stitch together workarounds and call it progress. His most telling data point: a material share of underwriters still rely on
Excel as the "core," even inside serious organizations.

Join live if you want to pressure-test your own replacement path-what to replace first, what not to touch, and where
"phase it in" quietly guarantees permanent manual work.

#InsurTech #InsuranceOperations 

Claims ops keeps buying “automation” that quietly adds work: more review, more disputes, more cycle time. The real villain is verification overhead—when you still have to check everything, “80% automated” is a new cost center disguised as progress.

Ralph von Grafenstein, Founder/CEO, DocuSketch, has lived the messy middle of property claims: documentation fights, estimate friction, and payout delays between restorers and carriers. His model is blunt: shrink cycle time by redesigning the workflow and centralizing quality—not by selling buzzwords.

Join us if you’re wrestling with vendor ROI, cycle-time targets, or post-cat documentation chaos.

#Insurance #Claims

Most claims “AI programs” die the same way: you buy models, bolt them onto core, and discover your data can’t support event-driven decisions. The result isn’t bad predictions—it’s diary-driven claims, slow closes, reserve noise, and a false sense of progress.

Heather Wilson (CEO) and Mubeen Rabbani (CPO) at Clara Analytics have lived this at scale: thousands of claims triaged daily, with alerts tied to measurable financial lift and operational impact. Their thesis is blunt—AI value is an operating model problem, and the hidden constraint is ingestion, normalization, and mapping across messy, multi-source claims data.

Join live if you want to review your current approach: what breaks first, what to measure, and what changes when claims becomes always-on instead of scheduled.

#InsurTech #Claims

Insurance isn’t short on “AI demos.” It’s short on AI that actually survives real workflows—submissions, audits, claims intake, policy comparison, compliance. Aman Gour (CEO, FurtherAI) breaks down what agentic AI actually means in practice, why “accuracy you can trust” is the real moat, and how teams move from one automated workflow to a platform-wide operating layer.

What you’ll hear (high-signal takeaways)

• Agentic AI, defined plainly: a loop where the system executes, checks, and self-corrects until the output is right (not just “extract text from PDFs”).

• The winning wedge in insurance AI: workflow outcomes and reliability—not model hype.

• Why “one platform” matters: insurers don’t want 10 tools; they want a workspace that expands from one workflow to many.

• Where the real leverage is: unstructured intake + decision workflows (submissions, claims/FNOL-adjacent intake, audits, policy comparison).

• The operator reality: adoption happens when humans stay in control, with review points, auditability, and explainable outputs.

• The closing theme: speed is useless without intent—“hustle with purpose.”

Chapters (timestamps)

• 00:00 — Intro + Aman’s background

• 00:36 — What FurtherAI does (where insurance ops actually bleed time)

• 02:22 — What “agentic AI” means (in the real world)

• 03:35 — The agentic loop: do → check → correct → final output

• 09:28 — “Not a ChatGPT alternative” (what a real platform is)

• 15:18 — What makes teams successful adopting AI in production

• 28:03 — One-person unicorn vs. small elite teams with leverage

• 28:56 — Closing: hustle with purpose (Margaret Mead quote)

Notable Comments 

• 03:35–04:07 — Agentic loop: execute, reflect, correct until it’s right.

• 09:28–09:35 — “It’s not just a data extraction platform… It’s not a ChatGPT alternative.”

• 28:56–29:22 — “Never doubt that a small group… can change the world… Hustle with purpose.”

Guest + Company Links

• FurtherAI: https://www.furtherai.com/

• Aman Gour (LinkedIn): https://www.linkedin.com/in/amangour/

About Our Guest

Aman Gour, CEO of FurtherAI — a Y Combinator-backed startup bringing automation and AI to the most unglamorous, yet mission-critical parts of insurance. Aman’s a two-time founder, product builder, and storyteller-in-progress — who’s helping rewire how insurers handle submissions, audits, and claims intake.

#InsurTech #Insurance #AI #AgenticAI #Underwriting #Claims #WorkflowAutomation

"Best-of-breed” feels like the sophisticated choice—until you try to run a scaled brokerage platform on it. The failure isn’t theoretical: inconsistent data, fragile integrations, impossible governance, and post-close execution drift. That’s where value leaks—quietly, expensively, and usually after the deal is already signed.

I’m going live with Trevor Bunker, Chief Customer Officer, Applied Systems. Trevor sits with large agencies and broker platforms that have lived both models: system-agnostic sprawl and hard consolidation. His point is direct: if you can’t get a single view of the truth, you can’t govern performance—especially across lines, geographies, and acquisitions.

Join live if you’re making platform decisions, planning conversions, or trying to de-risk integration timelines.

#InsurTech #MergersAndAcquisitions

When fraud pressure rises, carriers tighten controls. The hidden cost: cycle time balloons, adjusters burn out, and your best customers feel like suspects. That’s how you leak value—quietly—over quarters.

In this episode of the Insurtech Leadership Podcast, host Joshua R. Hollander speaks with Clearspeed's CEO Alex Martin about how his view that the fix isn’t “better fraud analytics.” It’s a trust layer that changes routing early: accelerate clean cases, escalate exceptions.

Watch live if you’re reworking FNOL, underwriting triage, or straight-through processing.

Introduction

Every insurer receives risk submissions the same way: an email arrives, packed with documents in whatever format the broker chose to send them, and someone on the operations team has to figure out what is in there. The problem is not that carriers lack data. The problem is that nobody has built a scalable way to operationalize it. Richard Hartley spent a decade building that infrastructure at Cytora — and then sold it to the company that reaches seventy percent of US agents.

Hartley is the co-founder and CEO of Cytora, an AI-powered risk processing platform acquired by Applied Systems and now powering EPIC Autofill and EPIC Submissions Manager. The conversation was recorded live at AppliedNet, where Cytora's integration into the Applied ecosystem was being unveiled. In this conversation, Josh Hollander and Hartley dig into how Cytora's seven-agent architecture produces confident extraction from any document format, why automation is a dial not a switch, and what it took to rebuild the company from ninety people to thirty at the start of COVID before finding the right product.

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Guest Bio

Richard Hartley is the co-founder and CEO of Cytora, an AI-powered risk processing platform now operating as a division of Applied Systems. Cytora digitizes and processes risk submissions across any format — emails, PDFs, spreadsheets, images — and routes structured data into downstream systems including policy admin, underwriting platforms, and agency management systems. Before founding Cytora, Hartley studied history and political science, worked in Shanghai for a tech company building core insurance systems across Asia Pacific, and trained as a classical ballet dancer. Cytora's technology is now embedded in EPIC, Applied's core agency management system used by seventy percent of US agents.

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Key Topics

The problem was never too little data

Cytora's original thesis was that underwriters needed more data to make better risk selection decisions. That turned out to be wrong. The real problem was that carriers could not operationalize the data they already had into a workflow that functioned at scale. Recognizing that distinction forced a full company pivot — and ultimately led to the product that Applied acquired.

Be agnostic to the input, define the output

Most earlier attempts to digitize submissions trained models on labeled examples of prior submissions — a rigid approach that broke every time document formats changed. Cytora took the opposite position: be entirely agnostic to what comes in, whether it is a bare email, a long Excel spreadsheet, a set of images, or a stack of PDFs, and instead let the insurer define their view of risk as the output. That design principle became the foundation of a platform that works across every line of business without retraining.

Seven agents at different temperatures

Cytora's extraction engine runs seven AI agents simultaneously on the same field, each using a slightly different strategy. When all seven return the same value, confidence is high and the field is accepted automatically. When agents disagree, confidence drops and a human review task is triggered. It is the same logic as solving a math problem seven different ways — agreement across methods is the confidence signal.

Automation is a dial, not a switch

Carriers and insurers sit at different points on the automation spectrum. Some will route lower-complexity, homogeneous risks straight through without human review. Others will use Cytora to present every risk decision-ready but keep a human in the final approval seat. Hartley is deliberately non-prescriptive about which is right — the platform accommodates both, and the correct setting depends on risk complexity, organizational strategy, and appetite for accountability.

The Applied acquisition: emotionally as much as analytically

Cytora was raising its Series C when it met Applied at a conference. Both organizations had been solving the same problem from different ends of the value chain — Cytora from the insurer side, Applied from the broker and agent side. Hartley describes the acquisition decision as emotional as much as analytical: seventy percent of US agents use Applied, which made joining forces the only path to the scale of industry impact Cytora was built to achieve.

EPIC Autofill and what comes next

Post-acquisition, Cytora integrated into EPIC via API in a matter of weeks. Documents that agents previously had to read, review, and rekey manually are now digitized automatically and pre-populated in EPIC. Coming next is a feature called Transactions — a capability that unifies the multiple follow-up communications that typically accompany a single submission into one coherent, complete risk view for the insurer.

Founder lesson: be obsessed by the problem, not the solution

Cytora's hardest moment came at the start of COVID, when the team pivoted from ninety people to thirty with no certainty about what the new product would be. Hartley's advice to founders in that position: stay obsessed with the problem. The solution will come if the problem is real and you care enough about solving it. Hire people who show commitment under pressure rather than people who describe what they would do in theory.

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Notable Quotes

"The reason we exist is really to enable risk to flow in a much more frictionless way through the value chain, from the retail broker through to the insurer."

"Be agnostic to the input because you can't control it. But define the output you want. Define your view of risk."

"I view automation as a dial. You should dial it up, dial it down, really depending on what your strategy is and what you're trying to do."

"We went from eighty, ninety people to around thirty people. We had no idea what the product would be that we would build."

"Be obsessed by the problem. Don't worry about not knowing the solution, because it will take some time."

"Seventy percent of agents in the US use Applied. Being intellectually honest, that was the path."

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Resources

Guest:
Cytora: https://www.cytora.com
Applied Systems: https://www.appliedsystems.com
Richard Hartley on LinkedIn: https://www.linkedin.com/in/richard-hartley-7744b851/

Host and Organization:
Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/
Horton International (USA): https://www.horton-usa.com/
Insurtech Leadership Podcast: https://www.linkedin.com/showcase/insurtech-leadership-show

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Today on The InsurTech Leadership Podcast, we’re joined by Jane Tran, Co-founder and Chief Operating Officer of Sixfold AI—a fast-growing InsurTech that’s reimagining the underwriting process through the practical use of artificial intelligence.

Jane’s journey started on Wall Street at JP Morgan, followed by leadership roles in strategy and innovation at Marsh and MetLife. She then became part of the founding team at Unqork, where she helped scale the no-code pioneer into a global enterprise before co-founding Sixfold.

Now, Jane is helping insurers harness AI to understand risk faster, more accurately, and with greater transparency. We’ll talk about how Sixfold is transforming underwriting from an art into a science, what “responsible AI” really means in insurance, and how Jane’s leadership philosophy—rooted in precision, empathy, and mentorship—is shaping an exciting InsurTech.