InsurTech: what are startups building now?
In our updated market reports, you will find everything you need
SUMMARY
InsurTech startups are building the machinery of insurance: AI underwriting systems, automated claims, software-driven brokerage, specialist risk products, embedded-insurance infrastructure, and tools that help insurers price and manage risk more efficiently.
The biggest change is where startups sit in the value chain. Many of the strongest companies now sell into insurers, brokers, and MGAs or use incumbent balance sheets, rather than trying to become full-stack challengers themselves.
Funding has recovered, but the market is much more selective. Global InsurTech investment rose to $5.08 billion in 2025, while Q1 2026 deal count fell to 81 and the median deal reached $10 million, suggesting fewer companies are absorbing larger checks.
Underwriting has become one of the clearest startup targets because commercial insurance still runs on messy submissions, PDFs, spreadsheets, broker notes, and manual judgment. Companies such as Sixfold, Federato, and FurtherAI are trying to compress the work before the final risk decision.
AI agents are moving into execution. Liberate, Novella, Quandri, and others are starting to handle multi-step servicing, sales, placement, claims, and renewal workflows rather than just summarizing information for an employee.
Insurance distribution is also being rebuilt from inside. Harper, Anzen, and Novella are showing that the more interesting question is how many customers or policies one broker can handle when software performs much of the routing, follow-up, document work, and administration.
Some of the strongest InsurTech models are appearing in difficult specialist risks. Shepherd in infrastructure, Nirvana in trucking, Coalition and At-Bay in cyber, and Descartes in climate-linked parametric insurance all rely on deeper data around a narrower risk rather than broad consumer branding.
Cyber insurance may be the clearest preview of where the industry is going. Monitoring, prevention, underwriting, claims, and insurance capacity are increasingly being bundled into one continuous risk-management product instead of being handled as separate services.
The old digital-carrier thesis has not disappeared, but the survivors are being judged like insurers. Root, Hippo, Lemonade, Kin, and others increasingly have to prove loss ratios, combined ratios, expense discipline, and capital efficiency rather than just customer growth.
Incumbent insurers are validating the shift through acquisitions and deep partnerships. Munich Re bought NEXT Insurance and agreed to acquire At-Bay, while Allianz handed major cyber responsibilities to Coalition instead of simply building everything internally.
The next InsurTech cycle therefore looks more concentrated and more operational. The strongest startups are likely to win by owning a costly decision layer, a specialist risk dataset, or a high-friction workflow that insurers cannot improve quickly enough on their own.
What changed in InsurTech?
InsurTech has quietly changed from a bet on replacing insurance companies into a bet on rebuilding how insurance companies actually work. The most important startups today are less likely to pitch “insurance, but with a better app” and much more likely to automate underwriting, turn brokers into software-driven distribution businesses, prevent claims before they happen, or build specialist insurance around risks that old models struggle to price.
The funding data shows how sharp that change has become. Gallagher Re recorded $5.08 billion of global InsurTech investment in 2025, up 19.5% from the previous year and the first annual increase since 2021. But this was not a return to the indiscriminate InsurTech boom. CB Insights found only 81 deals in the first quarter of 2026, the lowest quarterly count since 2016, while the median deal reached $10 million—almost twice the $5.3 million median at the height of the 2021 boom.
Investors are backing fewer companies, but they are willing to put substantially more money behind businesses that already appear capable of changing insurer economics. Gallagher Re calculated that AI-centered companies absorbed 77.9% of all InsurTech funding in the final quarter of 2025.
Insurance startups spent the previous cycle proving that buying policies could be digitized. The current cohort is trying to prove that technology can change the cost of underwriting, claims, distribution and risk itself.
| Signal | What changed |
|---|---|
| Global InsurTech funding | $4.25B in 2024 → $5.08B in 2025 |
| Q1 deal count | 81 deals in 2026, lowest since 2016 |
| Median Q1 deal size | $10M in 2026 vs $5.3M in 2021 |
| AI share of Q4 2025 funding | 77.9% |
| Insurer/reinsurer tech investments | Record 162 investments in 2025 |
Are startups still trying to replace traditional insurance companies?
Mostly no. The most interesting InsurTech startups now increasingly sell technology to insurers, operate alongside them, or use their balance sheets rather than trying to replace them outright.
Bestow illustrates the change unusually clearly. It originally sold life insurance directly to consumers and built its own underwriting and servicing operation. It eventually discovered that the underlying technology was potentially more valuable than the consumer insurer. In 2024, Bestow sold its carrier and direct-to-consumer business to Sammons Financial Group and concentrated on providing digital life-insurance infrastructure to other companies. Goldman Sachs and Smith Point Capital then led a $120 million Series D in 2025.
Federato has taken the software route from the beginning. Rather than becoming an insurer, it builds an operating platform that helps insurers manage submissions, underwriting decisions, portfolio appetite and policy workflows. Goldman Sachs Alternatives led its $100 million Series D in late 2025.
Sixfold is narrower still. It essentially builds an AI underwriting layer that carriers can insert into existing organizations. The company says its technology has processed more than 1.5 million submissions across more than 50 insurance lines and four continents.
Meanwhile, some startups remain genuine insurers. Lemonade, Root, Hippo, Kin and Ominimo all show that the carrier model has not disappeared. What has disappeared is the assumption that owning the insurance balance sheet is necessary for an InsurTech company to matter.
| Model | What startups build | Examples |
|---|---|---|
| Insurance software | Technology sold to insurers | Federato, Sixfold, Akur8 |
| AI-native brokerage | Technology plus licensed distribution | Harper, Novella |
| Specialist MGA | Underwriting technology using third-party capacity | Coalition, Shepherd |
| Insurance infrastructure | APIs and embedded distribution | Cover Genius, bolttech, Qover |
| Tech-native carrier | Technology plus insurance balance sheet | Lemonade, Root, Hippo, Kin |
If you want more recent data on this point, please see our latest InsurTech market report.
Why is underwriting attracting so many InsurTech startups?
Underwriting has become one of the biggest InsurTech opportunities because commercial insurers still spend enormous amounts of skilled human time converting unstructured information into decisions. Startups are attacking the work between receiving a submission and deciding whether, how and at what price to insure it.
Sixfold is an unusually clean example. Commercial submissions can contain emails, PDFs, spreadsheets, financial statements, broker notes and external data. Its AI extracts the relevant information, evaluates it against an insurer's appetite and produces underwriting narratives or recommendations. The company says insurers representing roughly $265 billion of gross written premium were already using its technology when it announced its $30 million Series B.
Federato is pushing further toward the operating system around that decision. Its Orchestrate product can assemble a complete quote package from a live submission for an underwriter to review. One customer case highlighted by Federato reported an 89% reduction in quote time; another said the share of bound policies fitting its preferred appetite increased 3.7 times.
FurtherAI attacks similar manual workflows from a different angle: submission intake, policy comparison and underwriting audits. The company says one MGA doubled underwriter productivity after deploying its system, while a regional insurer reduced the time required for policy comparisons by 95%.
The common target is the large amount of underwriting work that happens before the final risk decision.
Are AI agents actually starting to run insurance workflows and claims?
Yes. Insurance AI is moving beyond copilots that summarize information toward agents that execute multi-step work inside production systems, including claims.
Liberate builds AI agents for sales, customer service and claims. Its systems can quote policies, update endorsements, collect information and process claims rather than merely tell an employee what to do. The company raised $50 million at a $300 million valuation in late 2025 after reporting that one deployment reduced hurricane-claim response time from roughly 30 hours to 30 seconds.
Novella is applying the same idea to wholesale brokerage. Its agents work across placement, binding, form comparison, policy review, inspections, billing, endorsements and renewals. The company raised $21 million in 2026 to expand the model.
Quandri focuses on servicing work inside insurance agencies, while FurtherAI handles document-heavy commercial workflows. Federato and Sixfold concentrate heavily on underwriting.
Claims is becoming one of the clearest tests of whether these systems can execute rather than just assist. Sprout.ai has built insurance-specific AI that extracts claim information, evaluates coverage and helps detect fraud across health, life, motor, property and commercial insurance. Its system is designed to let straightforward claims move from first notice to decision with little or no human processing.
Lemonade provides a useful carrier-scale benchmark. In its second-quarter 2026 results, the company reported that its loss-adjustment-expense ratio had fallen to a record 5%. Lemonade attributes much of the efficiency to automation and says its claims AI now touches more than half of claims. Its gross loss ratio was also down to 60% from 67% a year earlier.
The clearest opportunity is routine work where the facts and policy rules are sufficiently structured for software to act directly.
If you want more recent data on this point, please see our latest InsurTech market report.
Are startups trying to automate insurance brokers out of existence?
Not exactly. A more credible InsurTech thesis today is turning brokers themselves into much higher-output businesses.
Harper is one of the clearest experiments. Rather than selling AI software to a traditional brokerage, it built an AI-native commercial insurance brokerage that connects small and midsized businesses with more than 160 carriers. The company says a conventional brokerage salesperson might handle 20 to 30 transactions in a month, whereas Harper's system allows it to serve more than 1,000 customers monthly. It had passed 5,000 customers when it disclosed $46.8 million of seed and Series A funding in early 2026.
The economic target is significant because insurance distribution remains extremely labor intensive. Applications must be assembled, insurers contacted, submissions chased, documents collected, quotes compared and renewals processed. Harper says AI performs much of the submission routing, carrier follow-up, document collection and pipeline administration.
Anzen attacks the same inefficiency while keeping independent brokers in the loop. Its platform automatically fills applications, retrieves carrier quotes and compares policies. It reported serving more than 5,000 retail agents and having quoted hundreds of millions of dollars of premium when it raised $16 million.
Novella is doing something similar in wholesale insurance, explicitly describing its objective as creating “super producers.”
The emerging contest is AI-equipped broker versus broker still doing much of this work manually.
Why is commercial insurance becoming such a big startup target?
Commercial insurance is attractive precisely because it is difficult to automate. The complexity that once protected incumbents is creating room for startups because many policies still require expensive human work before anyone can even quote them.
Shepherd shows what specialization can look like. It concentrates on commercial risks surrounding construction, energy and critical infrastructure. After raising a $42 million Series B in 2026, the company said revenue had increased more than sevenfold in two years and that it had insured more than $400 billion of project value across 1,500-plus policies for over 600 customers.
The AI data-center boom has created a particularly useful test. Enormous campuses are being built quickly, with unusual combinations of construction, equipment, power and operational risk. Shepherd has made insuring this physical infrastructure one of its specialties rather than attempting to become another general-purpose commercial carrier.
Nirvana followed a similar vertical strategy in trucking. Instead of underwriting commercial vehicles mainly through static applications, it uses telematics and says its models draw on more than 20 billion miles of driving data. Investors valued the company at $830 million when it raised $80 million in 2025.
The advantage comes from specializing deeply enough to collect better information on one difficult risk.
Is cyber insurance becoming cybersecurity with a policy attached?
Increasingly, yes. Cyber InsurTech is producing one of the clearest examples of insurance shifting from reimbursing losses toward continuously reducing the probability of a loss.
Coalition calls this Active Insurance. It combines insurance with external attack-surface monitoring, security alerts, incident response and continuous risk information. More than 100,000 policyholders were using Coalition's products when Allianz Commercial made an extraordinary strategic decision in 2026: Allianz agreed to transition its standalone commercial cyber portfolio to Coalition and make the startup its exclusive global commercial-cyber partner.
Coalition is not simply distributing Allianz policies. Under the agreement, it assumes primary responsibility for pricing, product development, risk mitigation and claims management, while Allianz contributes capital, distribution and multinational capabilities.
At-Bay has developed a closely related model for smaller companies. Its platform continuously identifies and monitors vulnerabilities while connecting those observations to insurance underwriting. Munich Re agreed to acquire the company for $575 million in August 2026. At-Bay had generated $278 million of gross written premium in 2025 and had become a top-ten U.S. cyber insurer.
These deals show cyber insurance moving toward an integrated product combining monitoring, prevention, underwriting and claims.
| Company | Current model | Recent scale signal |
|---|---|---|
| Coalition | Cyber insurance + continuous security | 100,000+ policyholders; Allianz global partnership |
| At-Bay | Cyber insurance + security platform | $278M 2025 GWP; $575M Munich Re acquisition agreement |
| Allianz–Coalition | Incumbent capacity + InsurTech risk engine | Coalition takes pricing, product, mitigation and claims responsibility |
If you want more recent data on this point, please see our latest InsurTech market report.
What are climate InsurTech startups building that traditional insurance cannot?
Climate-focused startups are increasingly building insurance around measurements rather than lengthy post-disaster loss adjustment. Parametric insurance is the clearest expression of that idea.
Descartes Underwriting uses weather data, satellite imagery, sensors and models to construct policies that pay when predefined physical conditions occur. Its flood product, for example, can use an on-site sensor to measure water depth and trigger a predetermined payout. This allows payment within days without requiring the normal process of proving every component of physical damage.
The company has moved well beyond experimental policies. Descartes reported more than $250 million of gross written premium in 2025, over 600 corporate and public-sector clients, more than 35 products and operations across over 60 countries.
Its expansion into data centers shows why the model is becoming more relevant. Descartes introduced coverage of as much as $140 million for earthquake and hurricane exposure affecting data-center projects, where an individual hyperscale campus can represent more than $10 billion of insured value.
Kin is pursuing another version of climate InsurTech by remaining a homeowners insurer but improving property-level risk selection in disaster-exposed states. It had more than $600 million of in-force premium and over $100 billion of insured property value when it raised equity at a $2 billion valuation in 2025. In 2026 it placed a $335 million catastrophe bond, its fourth and largest, to transfer major storm exposure to capital-market investors.
The objective is better measurement, faster payout design and broader access to risk capital.
Are startups still building embedded insurance?
Yes, but embedded insurance has matured from a checkout feature into infrastructure connecting global merchants, carriers and regulators.
Cover Genius works with more than 200 distribution partners and more than 50 carriers, allowing travel companies, retailers, ticketing platforms and logistics businesses to insert protection directly into transactions. It says its network reaches more than 70 million end customers. A $100 million financing announced in 2026 valued the company at $1.9 billion.
Bolttech operates an even broader marketplace. When it completed its $147 million Series C, it reported roughly 700 distribution partners, more than 230 insurers and over 6,500 insurance products. The round valued the company at $2.1 billion.
Qover has concentrated heavily on European orchestration. It works with brands including Revolut, Mastercard, BMW, Monzo and bunq and reported protecting 15 million people in more than 32 countries. Across the previous four years, it had generated more than $173 million of gross written premium and tripled revenue.
The difficult part is increasingly the infrastructure behind the purchase: insurer connections, licensing, pricing, claims and multi-country compliance.
Are startups finding a better way to price insurance—and can that actually make it cheaper?
Some are, but better pricing and cheaper operations are two different gains. Startups are attacking both: richer data can improve risk selection, while AI can reduce the labor required to underwrite, distribute and service policies.
Akur8 has built an end-to-end pricing environment covering data preparation, risk modeling, demand modeling, rate making and deployment. The company says its tools can reduce model-development time by roughly ten times while preserving transparency rather than producing an unexplained black-box rate.
Ominimo tests the same premise as an actual insurer. After launching in Hungary, it reached approximately 300,000 motor policies in roughly its first year and claimed about 7% national market share while already being profitable. Zurich subsequently invested at a valuation of about €200 million. Ominimo examines granular factors that conventional pricing models may underuse—for example, relationships between vehicle dimensions, population density and claim behavior.
Root has now produced evidence that technology-heavy pricing can coexist with strong insurer economics at scale. Its second-quarter 2026 net combined ratio was 92.1%, compared with 95.2% a year earlier, while net income reached $25.4 million. Root says proprietary data and continuously improving predictive models remain central to the business and plans another generation of pricing models.
Nirvana pushes this approach further in commercial trucking. Rather than pricing fleets mainly through static applications, it uses telematics information such as location and driving behavior against a dataset that it says exceeds 20 billion driven miles.
The same logic is spreading beyond vehicles. Coalition and At-Bay continuously observe digital infrastructure, while Descartes monitors physical conditions using sensors and external datasets.
AI also attacks expense directly. Lemonade's 5% claims-adjustment-expense ratio is one concrete indication. Harper's claimed ability to process vastly more commercial customers per sales team attacks distribution expense. Federato reports quote-time reductions approaching 90% in a customer deployment. FurtherAI says customers have doubled underwriting throughput or reduced policy-comparison time by 95%.
Technology does not remove hurricanes, car crashes, fires or liability judgments. Lower operating expense becomes structurally valuable only when the underlying risk is priced correctly.
Did the original digital-insurer model fail?
No, but it went through a much harsher economic test than early InsurTech enthusiasm implied. Several technology-native insurers are currently demonstrating much healthier underwriting economics, while others were absorbed by established insurance groups.
Root is profitable and produced a 92.1% net combined ratio in its second quarter of 2026. Hippo reported a 95.8% combined ratio for the same quarter, compared with 100.1% a year earlier, while gross written premium climbed 61% to $482 million. Lemonade reached $1.43 billion of in-force premium, up 32%, while its gross loss ratio improved to 60%; it still recorded a $43 million net loss but expects its first adjusted-EBITDA-positive quarter later in the year.
NEXT Insurance took another route. Munich Re's ERGO paid $2.6 billion for the company after NEXT reached roughly $548 million of 2024 topline and more than 600,000 small-business customers. Rather than proving that incumbents were obsolete, NEXT's technology ultimately became an asset inside one of the world's largest insurance groups.
The survivors increasingly look like insurers with strong technology rather than technology companies temporarily carrying insurance risk.
If you want more recent data on this point, please see our latest InsurTech market report.
Why are incumbents buying InsurTechs instead of simply copying them?
Because specialist startups can accumulate underwriting data, operating systems and teams that are difficult to recreate quickly inside a large insurer. Recent transactions suggest incumbents increasingly view proven InsurTech capabilities as strategic infrastructure rather than experimental innovation.
Munich Re provides the clearest pattern. Through ERGO it completed the $2.6 billion acquisition of NEXT Insurance in 2025, gaining a fully digital U.S. small-business underwriting platform and more than 600,000 customers.
It then agreed to buy At-Bay for $575 million in 2026, explicitly citing the movement of cyber insurance toward continuously managed combinations of security and coverage. At-Bay brought more than software: a top-ten U.S. cyber underwriting operation, $278 million of annual gross written premium and years of proprietary security information.
Allianz chose partnership rather than acquisition with Coalition but went unusually far: its standalone commercial cyber business is being transitioned onto Coalition's model.
Once a startup controls enough specialist data and workflow, buying or partnering can be faster than rebuilding it internally.
What are InsurTech startups building in life and health insurance?
Life and health InsurTech is increasingly moving toward infrastructure, automated underwriting and claims decisioning rather than simple online policy distribution.
Bestow is the clearest strategic example. After processing more than one million life-insurance applications during its direct-to-consumer years, it sold the carrier side and concentrated on technology that lets other life insurers launch and administer products digitally. Its subsequent $120 million financing suggests investors were willing to back the infrastructure business at substantial scale.
Qantev attacks health-insurance claims. Its specialized models help insurers determine whether treatment is covered, medically appropriate and potentially anomalous. Customers have included AXA and Generali.
Alan shows that a technology-native health insurer can also expand beyond the policy itself. The French company reached approximately one million members and a €5 billion valuation in 2026 while combining insurance reimbursement with digital healthcare and wellness services.
Life and health remain harder to automate because medical necessity, disability and mortality involve more contextual judgment than many routine property-and-casualty workflows.
Are startups building insurance products for completely new risks?
Increasingly, yes—and this may become more important than making existing insurance slightly more convenient. Startups are moving toward risks created or intensified by technological and economic change.
Cyber is the clearest category. Coalition and At-Bay combine security monitoring with insurance because digital risk changes continuously and conventional annual underwriting snapshots are inadequate.
AI infrastructure is creating another category. Shepherd insures construction and operation around data centers, energy assets and other critical projects. Descartes has designed parametric catastrophe protection specifically for hyperscale data centers, with limits reaching $140 million for some perils.
Climate change is expanding demand for wildfire, flood, hurricane and extreme-temperature products. Meanwhile trucking startups such as Nirvana can construct products around telemetry that traditional commercial-auto underwriting did not historically possess.
The innovation is increasingly starting with a new or poorly measured risk rather than a new way to sell an old policy.
Will AI replace old insurance core systems?
Partly, but replacing the entire insurance technology stack at once is unlikely. The nearer-term battle is over which layer becomes the insurer's system of intelligence.
Legacy policy-administration systems remain deeply embedded because they contain years of policies, accounting rules, regulatory logic and integrations. Replacing them is expensive and operationally dangerous.
Startups such as Federato are therefore trying to surround or supersede the decision-making layer rather than merely reproduce another database. Federato's thesis is that underwriting strategy, appetite, submissions, external data and AI should exist in the same operating environment. Its $100 million Series D indicates substantial investor confidence in that approach.
Sixfold can sit more narrowly inside the underwriting process. Liberate's agents interact with existing systems to execute workflows. FurtherAI automates tasks across whichever systems an insurer already uses.
The prize is becoming the operating layer through which insurance work gets done.
If you want more recent data on this point, please see our latest InsurTech market report.
What does the funding market say startups will build next?
The funding market is signaling concentration around AI-heavy businesses that can demonstrate measurable insurance economics rather than another broad wave of experimentation.
Gallagher Re found that annual InsurTech funding rebounded to $5.08 billion in 2025, but CB Insights' first-quarter 2026 data shows only 81 deals. A shrinking deal count alongside a $10 million median round means capital is clustering rather than spreading.
The companies receiving large checks reinforce the point. Federato raised $100 million for AI-native insurer infrastructure. Bestow raised $120 million for life-insurance technology. Cover Genius secured $100 million to extend embedded-insurance infrastructure. Shepherd raised $42 million around specialist commercial underwriting. Harper raised nearly $47 million around an AI-native brokerage. Sixfold raised $30 million around underwriting AI.
Meanwhile insurers themselves made a record 162 venture investments in technology companies during 2025 according to Gallagher Re, even as CB Insights subsequently found insurer corporate-venture participation weakening at the beginning of 2026.
The pattern points toward fewer generic InsurTech companies and more concentrated bets on expensive workflows and specialist risks.
So what are InsurTech startups actually building now?
InsurTech startups are now building the machinery of insurance more than the storefront. The strongest evidence points toward AI underwriting systems, autonomous brokerage operations, automated claims, embedded-insurance infrastructure, continuously monitored cyber coverage, climate-risk products and highly specialized commercial insurers.
The distinction from the previous InsurTech cycle is important. The earlier thesis was largely that insurance distribution was outdated: digitize the purchase experience, acquire customers online and eventually displace slow incumbents. That produced meaningful companies, but it underestimated how much of insurance economics comes from correctly selecting, pricing and managing risk.
The new generation is attacking those functions directly.
Sixfold and Federato want to change what an underwriter can process. Harper, Anzen and Novella want to change what one broker can sell. Sprout.ai and Liberate want to change how much claims work requires a person. Coalition and At-Bay are combining insurance with continuous cybersecurity. Descartes and Kin are finding different ways to manage catastrophe exposure. Shepherd and Nirvana are building around industries whose risk can be better understood with specialized data. Cover Genius, bolttech and Qover are turning insurance distribution into infrastructure.
The boundary between an insurer and an InsurTech is also becoming less useful. Munich Re can own NEXT and At-Bay. Allianz can supply capacity while Coalition runs cyber underwriting and risk management. A carrier can retain its regulated balance sheet while a startup becomes the layer through which its employees make decisions.
Startups are decomposing insurance into underwriting, pricing, distribution, claims, prevention, capital and risk data—and competing for whichever layer can be made radically more productive.
For now, the most important InsurTech product is no longer the digital policy. It is the system deciding what should be insured, how it should be priced, who should sell it and how the risk should be managed.
OUR METHODOLOGY
This analysis asks what InsurTech startups are actually building now by breaking the market into the main places where technology is changing insurance: underwriting, claims, brokerage, specialist commercial insurance, cyber, climate risk, embedded distribution, pricing, life and health, core systems, and the carrier model itself.
We prioritized recent evidence that showed real operating movement rather than broad positioning. That includes funding decisions, premium and customer scale, underwriting and claims outcomes, acquisitions, strategic insurer partnerships, and reported financial performance. Company-specific claims were treated as evidence about that company, while broader conclusions were based on patterns that appeared across several businesses or parts of the insurance value chain.
Market-level funding comparisons rely mainly on Gallagher Re's Global InsurTech Report Q4 2025 and CB Insights' State of Insurtech Q1'26. These sources support the article's figures on total funding, deal count, median deal size, AI's share of capital, and insurer or reinsurer technology investment.
For underwriting and workflow automation, key sources include Federato, Sixfold, Liberate, Harper, and Shepherd. We used these mainly for company scale, product scope, funding, and reported customer outcomes.
For strategic validation from established insurers, we relied on Allianz Commercial's Coalition partnership announcement, Munich Re's At-Bay acquisition announcement, and Munich Re Ventures' NEXT Insurance case study. For public-carrier economics, we used Root's SEC material, Lemonade's investor results, and Hippo's Q2 2026 results.
Other key company sources include Descartes Underwriting for parametric data-center coverage, Cover Genius, bolttech, and Qover for embedded-insurance infrastructure, and Akur8 for insurance pricing technology. The final conclusions come from aggregating these independent company, insurer, filing, and market-level sources rather than allowing one funding round or one startup narrative to define the category.
