Top 2026 Claims Intake Solutions That Deliver Verifiable Data for Brokers

Every claim a broker handles arrives as someone else's data problem: client emails with mismatched attachments, voicemails with half the facts, carrier portals expecting a clean ACORD. Claims intake is the work of turning that into structured, verifiable records across the full lifecycle of a claim — first notice of loss (FNOL), supplemental documents, loss runs, medical records, repair estimates, and everything that follows.

The cost of getting it wrong is now measurable. In Ivans' 2026 Agency–Carrier Connectivity Trends survey of 702 independent agents, 74% named re-keying data into multiple carrier portals as their single biggest pain point, and 90% said they had reduced business with a carrier because of friction in the submission process. With U.S. insurance fraud estimated at $308.6 billion a year, carriers and regulators also expect every field a broker submits to trace back to its source.

This guide compares the claims intake platforms we would consider as a broker buying in 2026 — software that ingests messy submissions, normalizes them into verifiable records, and stands up to a carrier audit. If you need to design the intake workflow itself before choosing a vendor — pillars, controls, governance, KPIs — start with our AI claims intake framework and come back here once you know what you are buying.

Key takeaways

• Verifiable claims intake means structured, source-attributed claims data across FNOL, supplements and downstream documents, with immutable change logs that hold up under carrier and regulatory audits.
• The strongest 2026 platforms convert unstructured notes — email, voice, PDF, handwriting — into structured records with citation-level traceability.
• Broker fit varies enormously. Several of the best-known claims intake platforms are built for the adjuster, not the broker. Check whose persona the product pages are written for and which agency management systems it connects to before you shortlist.
• AI-driven intake delivers measurable ROI. A FurtherAI claims intake deployment reached ~568% annual ROI and over 90% intake automation at one specialty insurer (FurtherAI Claims Processing customer story).
• Fraud detection at intake is where the upside sits. Deloitte projects P&C insurers deploying multimodal AI across the claims lifecycle could save between $80 billion and $160 billion by 2032.

What "verifiable claims intake" actually means

Verifiable claims intake produces structured records with defined sources, change logs and immutable audit trails. Every field traces back to the document, call or system it came from. A modern intake stack runs four stages in sequence:

• Capture — collects claim details across portal, phone, email and attachments.
• Normalize — structures inputs against a standardized schema for downstream systems.
• Enrich — cross-checks identities, prior loss histories and devices against external data.
• Audit-log — timestamps every change with user attribution to produce a defensible trail.

Quick comparison: 2026 claims intake platforms for brokers

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1. FurtherAI claims intake

FurtherAI is the AI workspace we have built for brokers, MGAs and carriers running document-heavy operations. Our claims intake assistant turns unstructured FNOL notes, attachments and emails into structured, audit-ready records — with a human in the loop on every decision that needs one.

Key capabilities: document and email ingestion with citation-level traceability; configurable schemas per carrier; open API architecture; SOC 2 Type II, ISO 27001, GDPR and HIPAA compliance.

Pros: Verified broker outcomes; modular workspace extends to underwriting, policy checking and loss runs; forward-deployed engineer model speeds rollout.

Cons: Best fit for commercial and specialty brokers; less optimized for personal-lines auto intake.

Best for: Brokers and MGAs managing complex, multi-carrier portfolios.

Customer evidence: A specialty insurer using our claims intake reached over 90% intake automation, more than $360k saved annually, approximately 568% ROI and over 10× faster processing. Leavitt Group reports faster turnarounds and higher accuracy.

"Our primary focus is eliminating the immense amount of manual work involved in processing unstructured data during submission and claims intake, where people are currently keying in information by hand." — Danny O'Lenic, Insurance Product Lead at FurtherAI

2. Ivans Claims Download

Ivans Download, part of Applied Systems, is the piece most broker claims-intake comparisons leave out: the inbound pipe that carries claim data from carriers into your agency management system, so staff never log into a carrier portal to check a claim.

Key capabilities: automated exchange of claims and policy information with carrier and MGA partners across six defined message types — claim number assignment, adjuster assignment, claim reserve, payment information, claim status update and claim information — with documents filed automatically to the policy record and workflows triggered inside the AMS. Ivans reports a network of 380 insurer and MGA partners.

Integration depth is the differentiator here: 28 certified agency management systems, including Applied Epic, Vertafore AMS360, Sagitta and QQCatalyst, EZLynx, HawkSoft, Novidea, NowCerts and Veruna. No other platform in this comparison comes close on broker-system coverage. Security: ISO/IEC 27001 certified, SOC 2 Type 2 audited semi-annually, SOC 3 report available.

Pros: Unmatched agency management system coverage; removes portal-checking entirely; the natural answer to the re-keying problem Ivans' own survey measures.

Cons: This is not AI and not intake automation — it is structured data transport. It moves the claim data a carrier chooses to send; it will not take an FNOL from a client, parse a document or route unstructured email. Coverage depends on which carriers have enabled claims download for your AMS, and that varies materially, so verify carrier by carrier.

Best for: Any brokerage whose staff currently check claim status in carrier portals. Treat it as the plumbing beneath an AI intake layer rather than a substitute for one.

3. Inaza

Inaza is an AI automation and data platform built exclusively for insurance, and one of the few with an explicit brokers and agents solution covering claims rather than only quoting.

Key capabilities: multimodal extraction across ACORD forms, FNOL emails, loss runs in Excel, SOVs, broker voice notes, PDFs, images and malformed files; AI email, phone and browser agents; FNOL automation described as capturing, classifying and actioning every first notice. Security: SOC 2 Type 1 and ISO/IEC 27001:2022.

Broker evidence: BCMG Insurance Brokers is published as automating 100% of FNOL across its book — the clearest broker-side claims reference of any vendor in this comparison.

Pros: Broker-aware out of the box; strong multi-format ingestion reduces follow-ups; a genuine named broker case study on claims.

Cons: Still newer to enterprise rollouts, with few named customers published. No agency management system integrations are named, so confirm how data reaches your AMS. No published pricing.

Best for: Mid-market brokers and MGAs wanting broker-specific intake without a bespoke build.

4. Liberate

Liberate builds insurance-native AI agents across voice, SMS, email and digital that resolve service and claims workflows inside core systems. On claims it handles voice FNOL end-to-end on calls of up to 20 minutes and writes back to the claims core, and it ships a Voice FNOL Accelerator on the Guidewire Marketplace for ClaimCenter.

Key capabilities: multi-channel FNOL capture with identity verification, policy lookup and vendor dispatch; pre-built connectors for Guidewire, Duck Creek, Snapsheet and Applied Epic; partner integrations with Zywave, Eberl, Insuresoft and Covenir. Liberate states SOC 2, HIPAA and PCI DSS. It raised a $50M Series B in October 2025 led by Battery Ventures.

Pros: Genuinely conversational intake rather than form-filling; Applied Epic is a named connector, which is rare among AI-native vendors; strong evidence of production deployment at carrier scale.

Cons: Its documented claims proof points are carrier-side, while its agencies-and-brokers page is mostly sales and service — quotes, certificates, endorsements, renewals — and does not foreground FNOL. Applied Epic is the only broker management system named. Ask for a broker-side FNOL reference customer before committing.

Best for: Retail brokers whose clients report claims by phone and who want that call captured as structured data rather than a callback note.

5. Indico Data

Indico Data positions itself as the intake and orchestration platform for insurance, ingesting unstructured claims and broker submissions from FNOL through resolution. Its agentic AI pulls structured data from email bodies, PDFs, tables, Excel sheets, ACORD forms, loss runs, SOVs, images, zip files and handwriting, then routes it into downstream systems.

Key capabilities: ingestion from a shared inbox or document repository, with connectors for Box, ImageRight, Azure and Documentum, plus a Guidewire Cloud integration. Indico publishes outcome figures of under 30 seconds for SOV and loss run processing, a 90% faster cycle time at Convex Insurance and an 85% reduction in submission processing time. Security: SOC 2 Type II. Aviva Ventures completed a strategic minority investment in October 2025; the company remains independent.

Pros: Genuinely strong on the messiest unstructured inputs; shared-mailbox ingestion maps well to how broker claims actually arrive.

Cons: Heavier platform-level deployment than overlay tools. Note that the shared-mailbox and broker-submission capability sits on Indico's intake pages, while its claims pages are written for carriers — so confirm the broker claims workflow specifically. SOC 2 Type II is the only certification listed.

Best for: Mid-market to large brokers handling high volumes of mixed-format broker-to-carrier submissions.

6. Bevaya (formerly Roots Automation)

Bevaya launched on 28 May 2026, replacing the company's earlier Roots platform and becoming its go-forward brand. The naming matters if you are drafting contracts: the legal entity remains Roots Automation, Inc., trading as Bevaya. The "Digital Coworkers" term you may remember has been retired in favour of "AI agents."

Key capabilities: named agents including FNOL/FROI Setup, Claim Indexing, ACORD Form Extraction, Loss Run Processing and Claim-to-Policy Comparison. Its InsurGPT engine is now described as an ensemble of specialised models trained on 300M+ proprietary insurance documents, with 98%+ accuracy claimed. Security: SOC 2 Type 2, HIPAA, GDPR, CCPA and 23 NYCRR 500 — the strongest stated posture in this comparison.

Pros: Excellent unstructured-document accuracy; buy specific automations rather than a platform commitment; publishes a per-agent rate card, which almost no one else here does.

Cons: Carrier and TPA oriented. Its broker substantiation is "3 of the Top 10 brokers" — global brokerages, not retail — and there is no brokers solution page, no named agency management system integrations, and every claims page is written to the adjuster persona.

Best for: National and global brokerages with in-house claims operations. Retail brokers should look elsewhere first.

7. Five Sigma

Five Sigma is an AI-native claims management platform whose agent, Clive, automates FNOL, triage, coverage, liability, fraud detection and documentation. It can be deployed on an existing claims system or used with Five Sigma's own AI-native claims management system. Recent deployments include Starr, Loadsure and Fast Cover. (Note the company's site is now at fivesigmalabs.com, though it still brands as Five Sigma.)

Pros: AI-native architecture rather than bolted-on; quick proof-of-value cycles; the deepest coverage of the downstream claims lifecycle here.

Cons: Five Sigma states its audience as insurers, MGAs, TPAs, self-insureds, reinsurers and mutuals — brokers are not mentioned anywhere on its homepage or Clive product page. There is no stated broker proposition.

Best for: Wholesale brokers and MGAs running claims operations end to end, and TPAs. Retail brokers are not the buyer.

Key features to evaluate

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What brokers should ask vendors

Most claims intake platforms are built for carriers and adjusted afterwards for brokers. These questions surface that quickly, and every one of them came out of comparing the seven platforms above.

On broker fit

• Who is your product written for? Ask them to walk you through the persona on their claims pages. If every screenshot shows an adjuster queue, you are buying a carrier tool.
• Name three broker reference customers on the claims side. Not submissions, not underwriting — claims. Several vendors here have strong broker stories on submissions and none on claims.
• Which agency management systems do you connect to natively? If the answer is none, ask exactly how structured data reaches your AMS, and who builds that.

On verifiability

• How does a field trace back to its source? Ask to see the citation on a real extracted document, not a slide.
• What does your audit log actually record? Timestamp, user attribution and prior value, or just the change?
• Can you produce a full claim lifecycle record on demand in a format a carrier auditor will accept?

On the AI itself

• What is your accuracy figure, and on whose documents? Vendor accuracy is measured on vendor test sets. Ask them to run your own document mix.
• What happens at low confidence? A platform without a defined escalation path is one that will silently guess.
• Which model, and does it train on our data? Get the contractual answer, not the sales answer.

On compliance and commercials

• Which SOC 2 type? Type I is a point-in-time design assessment; Type II tests operating effectiveness over months. Not every vendor in this market specifies which they hold.
• Is pricing per seat, per document, per agent or per claim? These are not comparable, and the unit tells you what the product really is.
• What does implementation actually require from us, in named roles and weeks?

Selecting the right claims intake platform for brokers

Align technology choices with operational scale — volume, lines of business and integration dependencies. The best-fit solutions mirror existing broker workflows across carriers, offer configurable rule libraries for fraud and validation, integrate securely via standardized APIs, and maintain real-time auditability and change history.

Most brokerages will end up with two things rather than one: a data pipe that removes portal-checking, and an AI layer that turns unstructured client input into structured records. They solve different halves of the problem, and neither substitutes for the other.

"We had a producer spend hours trying to extract and format a loss run using general AI tools, and it just wasn't working. When they ran the same file through FurtherAI, it produced exactly what they needed in minutes. That's when it really clicked for us." — Laurie Flanagan, Chief Project Officer at Leavitt Group

For a broader read on AI ROI in commercial insurance, see our breakdown of where AI is delivering measurable returns. For a vendor-level view of the FNOL layer specifically, see our first notice of loss (FNOL) automation comparison.

Ready to see verifiable claims intake in your own workflow? Schedule a demo.

Frequently asked questions

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REFERENCES

^{Applied Systems. "Ivans Download for Agents." ivans.com}

^{Applied Systems. "Security." ivans.com}

^{Bevaya. "AI Agents for Claims Automation." bevaya.ai}

^{Coalition Against Insurance Fraud. "The Impact of Insurance Fraud on the U.S. Economy." (2022) insurancefraud.org}

^{Deloitte. "Property and Casualty Carriers Can Win the Fight Against Insurance Fraud." (April 2025) deloitte.com}

^{Five Sigma. "Clive." fivesigmalabs.com}

^{FurtherAI. "Claims Processing Case Study." furtherai.com}

^{Inaza. "AI Solutions for Brokers and Agents." inaza.com}

^{Indico Data. "Intake." indicodata.ai}

^{Ivans. "2026 Insurance Agency-Carrier Connectivity Trends Survey Report." (August 2026) ivans.com}

^{Liberate. "Platform." liberate.ai}

^{McKinsey & Company. "Can Agentic AI (Finally) Modernize Core Technologies in Insurance?" (April 2026) mckinsey.com}

^{PR Newswire. "Roots Automation, Inc. Launches Bevaya, Its New Flagship AI Agent Platform for Insurance." (May 2026) prnewswire.com}

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DISCLAIMER 

This article is for general informational purposes only and does not constitute legal, regulatory, compliance, underwriting, or other professional advice. The content reflects information available as of the date of publication, and FurtherAI undertakes no obligation to update it as laws, regulations, or AI technologies evolve. 

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