Insurance AI
S

Snapsheet

Snapsheet sells cloud based claims management software to property and casualty carriers, third party administrators, managing general agents and self insured organizations, and it reached that position from an unusual starting point. The company began under a different name and built its reputation on virtual appraisals, assessing vehicle damage from photographs submitted by claimants rather than sending an inspector, an approach it staffed in its early years with remote human appraisers reviewing images. That franchise became the foundation for a full claims platform covering first notice of loss through settlement, including digital communications with claimants, workload management for adjusters, configurable workflows, reporting, and digital payments and disbursement at the point of settlement. Appraisal coverage extends beyond passenger vehicles to boats, recreational vehicles, motorcycles, utility and exotic vehicles, and the platform handles property and commercial claims alongside auto.

Snapsheet AI is the current AI layer, and its design is explicit about where control sits. Agents are configured at the prompt level in plain language, with the carrier creating the persona, designating which context and data the agent may use, directing the actions it takes and defining the output it returns. Pre configured agents ship for summarization, scoring, intake, liability checks, communications and claim evaluation. Agents run in two modes: triggered automatically inside event based workflows, or initiated on demand by an adjuster in a side panel copilot. The company positions this against assistants that sit apart from the work, arguing that AI stranded in a side panel cannot have an effect, and that its agents operate with immediate context of the data, rules, permissions and logic already configured in the claims system.

Integration is built on open interfaces, no code automation and a partner network the company sizes at more than 140, including carriers, third party administrators, managing general agents and insurtechs. A joint platform with the core system vendor Socotra combines policy and claims stacks, and a partnership with Floatbot covers conversational agents.

Published volume figures are dated but substantial: more than 4.3 million claims managed and $15.3 billion of indemnity processed as of a 2023 report, alongside more than 25 million automated tasks executed. IAT Insurance Group is among named customers. A Trust Center and privacy policy are published on the company's own site.

Founded in 2011 by Brad Weisberg and headquartered in Chicago, Illinois, privately held, with a reported workforce above 400 as of its most recent public staffing account.

Last VerifiedAugust 26, 2026
Compare Snapsheet with other vendors
Founded
2011
Headquarters
Chicago, Illinois, United States
Categories
insurance-ai, payments-intelligence
Assessment

Capability Axes

Capability grades

15 of 15 axes rated · 3 graded A or B

AI Capability
AI Centrality
CC on AI CentralityArtificial intelligence is present but peripheral: a feature layer on a product whose value stands without it.
Vendor Published

Strip the models out and a claims system still runs from first notice of loss through settlement, which is what carriers buy it for. Virtual appraisal started with remote human appraisers reviewing photos, so automation improved a workflow that already worked.

Autonomy and Oversight Model
CC on Autonomy and Oversight ModelAutonomy is claimed and oversight is asserted without a mechanism, or full automation is presented as the entire disclosure. Human in the loop appears as a phrase rather than a described control.
Vendor Published

Agents either fire automatically inside event based workflows or wait for an adjuster in a side panel copilot, and the carrier directs their actions in plain language instructions. That makes the customer the author of the guardrails, and no approval class, referral threshold or default limit is published.

Model Risk Management and Transparency
CC on Model Risk Management and TransparencyTransparency is claimed in general terms with no mechanism a model validator could interrogate.
Vendor Published

Every plain language prompt change alters the behavior of a system making evaluation determinations, and nothing published describes version control, pre launch testing or approval for those changes. No accuracy, benchmark against adjusters or drift monitoring is published for any agent.

Operational and Outcome Evidence
BB on Operational and Outcome EvidenceVendor aggregate claims with real figures, or audited scale disclosures from a publicly listed company.
Vendor Published

More than 4.3 million claims and $15.3 billion of indemnity processed size the money moving through the platform, though both figures come from a 2023 report not restated since. IAT Insurance Group is the clearest named customer, and no accuracy, automation rate or expense saving is credited to the AI.

AI Safety and Data Stewardship
CC on AI Safety and Data StewardshipGeneral assurances that do not answer the question this axis asks, which is whether one customer’s data trains models serving its competitors. Unbounded cross client learning stated with no boundary grades here too.
Vendor Published

A carrier designates which data an agent may use when writing its prompt, so the boundary around sensitive claim material sits with whoever configures it, and no default restriction is described. Whether claim data trains models is unaddressed, and a third party report that models learned from millions of past claims finds no confirmation in company material.

Regulatory and Compliance
GLBA and Data Privacy Posture
CC on GLBA and Data Privacy PostureA standard privacy policy that covers the website rather than the service, or silence on a product that touches limited consumer data.
Vendor Published

Claimant photographs, adjuster notes and disbursement instructions combine personal, evidentiary and financial data about people who are not the customer. A privacy policy is linked site wide, but its contents are not reflected here, so no retention or claimant data commitment is confirmed.

Security Certifications and Trust Center
CC on Security Certifications and Trust CenterA single footer line, or certifications asserted without being enumerated, which is weaker than naming them because it invites an assumption a buyer cannot check.
Vendor Published

A Trust Center linked from every page gives a security team a named destination, a better structure than a request queue. Its contents are not reflected here, so no SOC report, certification or penetration testing statement is confirmed.

Regulatory Status and Licensure
CC on Regulatory Status and LicensureThe regulatory position is unstated. Most vendors in this index are technology suppliers and being unlicensed is the correct posture, so this grade records silence about the posture, not a missing license.
Vendor Published

Claims handling is examined at state level for timeliness and fair settlement, and the company once employed appraisers, an activity several states license. Yet no audit trail capability, state requirement support or position on the commissioners' AI guidance is described.

AI Governance and Bias Disclosure
CC on AI Governance and Bias DisclosureResponsible artificial intelligence committed to in policy language with no evaluation behind it, on a product whose bias surface is modest.
Vendor Published

Liability check agents assess fault, which sets whether a person is paid or pursued, and fault drawn from claim narratives is where language models absorb historical handling patterns. The company publishes no fairness testing, bias evaluation or model card.

AI Liability and Recourse
DD on AI Liability and RecourseNothing published on who bears the loss when the system is wrong.
Vendor Published

Communications agents write to claimants who sit outside the contract, and nothing published tells them an agent shaped the figure they were offered or how to contest it. Because the carrier configures what the vendor built, responsibility for a defective output divides between them, and nothing allocates it.

Integration and Deployment
Model Supply Chain Disclosure
CC on Model Supply Chain DisclosureThe architecture is described and no provider is named.
Vendor Published

Writing agent personas and actions in plain language is the interface of a general purpose language model, yet no provider, family or version is named. Floatbot is disclosed as the conversational agent partner, which leaves the claims agents themselves unattributed.

Core Systems and Integration Depth
BB on Core Systems and Integration DepthNamed systems or a documented public API, with the depth or the production evidence left open.
Vendor Published

The platform runs claims through to payment disbursement, so the vendor sits inside the settlement transaction rather than handing off before it. A partner network above 140 and a joint stack with Socotra extend it, but policy administration, billing and underwriting are outside its scope.

Deployment Model and Data Residency
CC on Deployment Model and Data ResidencyCloud only with nothing stated, which is the category norm.
Vendor Published

A typical installation takes 45 days, about 30 of them spent on business rules and training, an honest breakdown from an interview several years old. Hosting provider, regions and tenancy are all unpublished, and no private deployment path appears.

Commercial
Commercial Transparency
CC on Commercial TransparencyNo price is published and engagement runs through a demo form, which is the norm in this index.
Vendor Published

The early appraisal business charged per estimate, the only known basis signal, and nothing says whether the platform kept that transaction shape or moved to a license. Whether agents cost extra, and how payment disbursement is priced, are both unaddressed.

Institution and Segment Coverage
BB on Institution and Segment CoverageNamed segments with dedicated material behind part of the coverage.
Vendor Published

Carriers, third party administrators and self insured organizations all buy it, a fit for a market where the party handling a claim often is not the one carrying the risk. Auto is where depth sits, extending through property and commercial claims, and no presence outside the United States appears despite stated expansion plans.

Alternatives to Snapsheet

Vendors in the same categories as Snapsheet whose profiles look most alike, each with a line on what the product does. Similar is not the same: check that each one does the job you need. No vendor pays for placement.

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FINEOS sells core insurance software to life, accident and health insurers and the employee benefits market.

FRISS screens the whole policy lifecycle for property and casualty insurers and calls the result trust automation, which is a deliberate inversion of how this category usually talks.

The index publishes no overall score or ranking. See what we assess and the methodology.

Commercial

Pricing

Vendor-published figures are labeled as such. Figures labeled “Estimated” are derived from third-party sources and have not been confirmed by the vendor.

Entry Price Pricing Basis Data Protection Terms Implementation Source
Not published. No price, unit of billing, tier or contract term appears on any vendor surface for the claims platform, the appraisal product or the configurable artificial intelligence agents
Not published on any vendor surface. The platform spans first notice of loss through settlement with appraisal, workflow, communications, reporting and payment disbursement, and nothing published indicates whether charging follows claims handled, estimates produced, adjuster seats, transaction volume, payments disbursed or a platform subscription. The early business charged per estimate, and a claims platform serving carriers, third party administrators and managing general agents with very different volumes would plausibly retain a volume based element, without anything published confirming it. The configurable agents introduce a second undisclosed variable, since a capability a customer can point at many use cases consumes value in a way a per agent or per invocation basis would price quite differently from inclusion in the platform fee. No tiered data protection terms are published. A Trust Center and a privacy policy are both published and linked site wide, which gives a buyer a structured route rather than an ad hoc request. Their contents are not reflected here, so no retention schedule, data processing agreement, subprocessor list or claimant data commitment is confirmed. The open commitments concern three distinct data classes the platform holds together: photographic and documentary evidence of loss submitted by claimants, adjuster narrative and liability assessments about named individuals, and payment instructions including disbursement details. The configurable agents raise a fourth question: which data classes a carrier may point an agent at, whether any are restricted by default, and whether prompts and claim content reach a third party model provider during inference. No implementation or professional services fee is published. The company has published a useful duration breakdown, though it dates from an interview several years old. A typical installation was stated at 45 days, of which roughly 30 go to configuring business rules and training staff rather than to technical integration, with clients able to build interfaces and integrations alongside. Naming the split between technical work and business configuration is candid, because business rule definition is where claims implementations usually overrun and where the customer's own effort dominates the cost. Configuration is positioned as a customer capability rather than a services engagement, through no code automation, configurable workflows and agents written in plain language. That shifts effort toward the buyer's team rather than a professional services bill. Nothing published states a services rate, a migration path from an incumbent claims system, or how long agent configuration takes. Vendor Published

The company's site, product pages and news archive publish no price, unit or tier, third party coverage adds none, and a demo request is the only route. One historical detail is the only known basis signal: in its early virtual appraisal business the company charged for each estimate it produced, a transaction model rather than a license. Nothing published indicates whether that shape survived the move to a full claims platform.

The company is privately held, founded in 2011 in Chicago under a different name. Its most recently reported financing was a small round in mid 2023, following a larger raise in 2017, so no financial reporting fills the gap. The open commercial questions are whether the configurable agents are included with the platform or licensed separately, how payment disbursement is charged given that money movement usually carries its own economics, and whether appraisal remains priced per estimate alongside the platform.

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AI FinTech Index

The AI FinTech Index is an independent index that tracks changes to AI vendors in financial services. It holds 610 vendors across banking, lending, insurance, wealth, capital markets and financial crime compliance, each graded on the same 15 capability axes from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
October 20, 2026
The AI FinTech Index is an editorial reference, not a regulatory body. Vendor data is verified against published sources and public regulatory filings. Figures labeled “Estimated” have not been confirmed by the vendor. See the Methodology page for evaluation standards and limitations.
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