We have been backing seed-stage InsurTech companies since 2020. The category has changed substantially in six years — not just in the technologies available to founders, but in what problems are available to be solved and which problems are already occupied by companies from earlier cohorts. Writing about what 2026 seed-stage InsurTech looks like is, in part, writing about what 2020–2022 seed-stage InsurTech accomplished well enough that it is no longer available as a greenfield opportunity.
What Is No Longer Greenfield
Motor telematics-based pricing for personal lines is not a seed-stage opportunity in 2026. The companies that solved this problem at scale — usage-based motor pricing, real-time fleet telematics for commercial motor — exist and are growing. A founder proposing to build this in 2026 is proposing to compete with established market participants who have accumulated years of loss data, carrier relationships, and pricing model accuracy that cannot be replicated from a standing start at seed stage.
Straightforward FNOL automation — digitising the first notice of loss intake process, routing simple claims to automated pathways — is similarly competitive. The first generation of claims automation companies, including in our own portfolio, have established production deployments at tier-1 carriers. The incumbent FNOL automation market has enough credible providers that a new entrant is competing on execution and pricing rather than on a genuinely novel approach to the problem.
Direct-to-consumer digital InsurTech in personal lines is almost entirely occupied at seed stage. The companies that successfully digitised personal motor, home, and travel insurance consumer experience in the 2018–2022 wave have either grown significantly or failed; the ones that survived have defensible positions. Building another direct consumer insurance brand in 2026 without a structural advantage in risk selection or distribution cost is competing on marketing, which is not where seed-stage capital should be going.
Where the 2026 Greenfield Is
The seed-stage opportunities that we find genuinely open in 2026 share a pattern: they exist at the intersection of insurance domain complexity and recent shifts in adjacent technology that have made previously unsolvable problems newly tractable.
Real-time reinsurance pricing infrastructure. The primary market has built digital distribution and AI underwriting. The reinsurance layer has not moved. Treaty pricing, facultative reinsurance placement, catastrophe model integration, and bordereaux management remain heavily manual and relationship-based at the operational level. The founders building tools that give cedants and reinsurers better real-time visibility into portfolio aggregation and treaty pricing are solving a problem that was not practically addressable before the combination of cloud-scale data infrastructure and modern LLM-based document intelligence made structured data extraction from reinsurance documents economically feasible.
Continuous underwriting policy administration. The regulatory and actuarial case for continuous underwriting has strengthened substantially. The policy administration infrastructure that enables it — event-driven policy engines that manage mid-term repricing, variable premium collection mechanics, regulatory disclosure at repricing events — is still being built. The founders who solve the administration infrastructure problem are enabling a product category that multiple carriers want to deploy but cannot, because their legacy policy administration systems are not designed for it.
EU AI Act compliance infrastructure for insurance models. The transition period for the EU AI Act's provisions on high-risk AI systems in insurance has created a category of compliance infrastructure need that did not exist two years ago. Carriers and InsurTechs that have deployed AI underwriting models are now managing the compliance obligation: technical documentation of model architecture and training data, fairness testing across protected characteristics, ongoing monitoring of model performance and distribution shift, audit trail for individual decisions subject to regulatory review. The tooling to manage this compliance obligation at scale does not exist as a packaged solution. Founders building the compliance infrastructure layer for insurance ML are solving a problem with a known and growing addressable market.
Climate risk model calibration services. The parametric insurance market for climate risk has grown significantly, and with it the demand for climate risk models that can price novel parametric triggers accurately. The challenge is that historical climate data is an increasingly poor predictor of forward-looking climate risk — the model calibration problem is harder now than it was when the parametric market was built, and the solutions are more urgent. Founders combining physical climate science with ML-based model recalibration, in a form accessible to underwriters rather than climate scientists, are addressing a problem that is commercially acute and technically demanding.
The Founder Profile That Succeeds in 2026
The founder profile for successful 2026 seed-stage InsurTech is more specific than it was in 2020. In 2020, a strong ML engineer with a general understanding of insurance and a credible go-to-market thesis could raise a seed round and build something real. The unsolved problems in InsurTech were broad enough that technical capability plus domain awareness was sufficient.
In 2026, the remaining greenfield problems are at the edges of domain complexity — the parts of insurance that require genuine deep knowledge of reinsurance structures, regulatory compliance architecture, actuarial model methodology, or climate science to solve. The founders succeeding at seed in this environment have either built that domain knowledge through direct practitioner experience in insurance, or have structured their founding teams so that domain depth is present from day one through co-founders or early hires, not outsourced to advisors.
The other shift is in the speed of carrier relationship development. The carriers who were most amenable to early-stage partnership experiments in 2020–2022 have now developed vendor preferences and evaluation frameworks that filter more aggressively. A cold approach to carrier business development in 2026 requires stronger evidence of technical differentiation earlier in the process. Founders who come with existing carrier relationships — from prior roles in insurance, from portfolio company networks, from advisory positions — compress the sales cycle meaningfully. This is not impossible without existing relationships, but it requires more time and more patient capital than some founders plan for.
Our Outlook for the Rest of Fund II Deployment
We are actively deploying the remaining Fund II capital into the categories described above. The companies we back will be solving problems that require genuine insurance domain depth, that are technically demanding enough to create durable differentiation, and that have a clear path to carrier deployment within 18 months of seed close. The seed market in European InsurTech is healthy — the quality of founding teams we are meeting in 2026 is the strongest we have seen across our history, driven by the talent that came through the 2022–2024 market correction and emerged with hard-won operational experience. The problems that remain unsolved are the right problems for this stage of the industry's development.