Alternatives
Bevaya alternatives
Document automation, claims decisioning, and what happens after intake.
Last updated 23 September 2026
Judged on: Insurance-trained models vs horizontal document AI, How much of the claim lifecycle is covered after intake, Whether the product decides, or only extracts and routes, Integration with the claims system of record, Fraud investigation, subrogation, and recovery coverage
Verdict
The closest alternative to Bevaya is Indico Data, which does the same intake, enrichment, and orchestration job. Hyperscience wins on handwriting and degraded scans, Five Sigma on adjuster-facing claims decisioning, and Hesper AI on what happens after intake: coverage, investigation, settlement, and recovery, with evidence behind each decision. Bevaya itself automates document-heavy intake across underwriting and claims.
Context
Bevaya is the AI agent platform from Roots Automation, Inc., launched on 28 May 2026 as the successor to the Roots platform. It ships pre-built agents for submission intake, loss runs, FNOL and FROI setup, claim indexing, legal demand and medical bill extraction, COI creation, and premium audit, all powered by InsurGPT, which the company describes as an insurance-native AI engine trained on 300M+ proprietary insurance documents. Buyers shortlist it against other insurance document AI platforms (Indico Data), horizontal document AI with an insurance vertical (Hyperscience), AI-native claims decisioning (Five Sigma), and their own build. Hesper AI is on the list for a different reason, described honestly below.
On this page
Why people look for Bevaya alternatives
Three reasons come up most. First, scope: Bevaya's public platform page describes agents that read, extract, classify, and route documents, then put a recommendation in front of a person. Teams whose bottleneck is the decision rather than the data entry go looking for something that carries the claim further. Second, the rebrand itself. Roots Automation renamed its platform Bevaya in May 2026, and buyers who evaluated Roots earlier want to know what actually changed. Third, comparison hygiene. Bevaya publishes strong numbers - 98%+ accuracy on critical work, 120+ production deployments, 3-4x capacity gains - and procurement wants two or three benchmarked options before signing. None of those are complaints about the product. They are normal reasons to build a shortlist.
Indico Data - the closest like-for-like alternative
Indico Data is the nearest direct substitute. Its public positioning is an intake and orchestration platform for insurance: extraction agents unbundle emails, attachments, statements of value, and loss runs; enrichment agents close gaps and classify; orchestration agents route validated work into downstream systems. That is the same job Bevaya does, framed almost identically, and it spans underwriting submissions, FNOL, mid-term adjustments, and broker reconciliation. Indico's own site names Allstate, Aspen, Convex, Everest, Markel, HDI, Aviva, and BHSI as customers, which is a comparable enterprise roster. It also publishes governance features insurers ask about: data lineage, confidence scoring, and explainability. If you like Bevaya's approach but want a second bid from a vendor of similar maturity, this is the one to run.
Hyperscience - best on handwriting and degraded scans
Hyperscience is a horizontal document AI platform with an insurance vertical rather than an insurance-only company, and that cuts both ways. The upside is raw extraction quality on the documents that break everyone else. Its insurance page claims 99.5% data-extraction accuracy and 98% automation, and specifically calls out cursive, sloppy handwriting, faxes, and mobile photos. It cites an IDC study showing a three-year 615% ROI and states a typical implementation of about 90 days. The trade-off is that the insurance logic sits on top of a general platform, so you get fewer opinionated, pre-built insurance agents than Bevaya ships and more configuration of your own. Pick it when your intake is genuinely dirty paper.
Five Sigma - adjuster-facing claims decisioning
Five Sigma attacks the problem from the adjuster's desk rather than the mailroom. Clive, its multi-agent AI layer, is designed to sit on top of any existing claims management system, surfacing guidance, running routine tasks, and pulling the right data into view so adjusters decide faster. Five Sigma also sells a standalone AI-native claims management system with Clive built in, so it can be an overlay or a replacement. Its site lists 11+ P&C lines including auto, homeowners, workers' compensation, cyber, general liability, and pet, names INSHUR, Resorts World, Xceedance, and Quartz Claims among its customers, and cites recognition as a Luminary in Celent's 2026 North America P&C Claims Systems Report. Choose it when adjuster throughput, not document intake, is the constraint.
Hesper AI - the lifecycle after intake, with evidence behind it
Hesper AI is not a like-for-like Bevaya replacement, and it would be dishonest to pitch it as one. Bevaya is strongest at turning inbound documents into structured, routed, downstream-ready work. Hesper is an AI claims resolution platform: it picks the claim up and carries it from first notice to final recovery, running coverage analysis with cited positions, investigation, settlement and demand review, payee checks, and subrogation and salvage screening on every file. Its differentiator is investigation-grade evidence behind each decision, sourced and timestamped so it is defensible to regulators and reinsurers. Clean claims resolve straight through; suspicious ones get a full workup in hours, not weeks. If your problem is intake accuracy, Bevaya or Indico is the better buy. If it is what happens after intake, look here.
Where Bevaya is still the right answer
For a large carrier, broker, or TPA drowning in inbound paper, Bevaya is a strong default and often the correct choice. Its models are insurance-specific rather than general-purpose, which matters on ACORD forms, loss runs, exposure schedules, and medical bills. It ships working agents rather than a toolkit: submission intake, FNOL and FROI setup, claim-to-policy comparison, claim indexing, legal demand extraction, invoice payment processing, COI creation, premium audit. It is validated on the Guidewire Marketplace for ClaimCenter with a published document-indexing accelerator, and writes to Salesforce Industries and Duck Creek Claims. Its compliance posture is deep - SOC 2, HIPAA, GDPR, CCPA, and 23 NYCRR 500 - with immutable audit logs, role-based access, and human-in-the-loop review. The company has been operating since 2018 and was founded by former AIG operators. That combination of insurance depth, enterprise references, and governance is hard to beat if intake is your real problem.
Building in-house on a foundation model
Cheap frontier models and good document APIs make a build look attractive, and for a narrow, high-volume document type it sometimes is. You keep full control of prompts, thresholds, and data residency, and nothing leaves your tenancy. The costs land later. Insurance documents are adversarial: poor scans, handwriting, inconsistent carrier formats, and forms that change without notice. Bevaya's own September 2026 benchmark argues that insurance-trained models beat general frontier models on loss runs, which is self-interested but directionally consistent with what teams report. Add human review tooling, audit logging, confidence calibration, drift monitoring, and integration into the claims system, and the scope reliably outruns the original estimate, with permanent maintenance attached once it ships. Best suited to large carriers with a standing ML team and genuinely unusual requirements.
How we compared
- Insurance-trained models vs horizontal document AI
- How much of the claim lifecycle is covered after intake
- Whether the product decides, or only extracts and routes
- Integration with the claims system of record
- Fraud investigation, subrogation, and recovery coverage
Comparison table
| Dimension | Hesper AI | Indico Data | Hyperscience | Five Sigma | In-house build |
|---|---|---|---|---|---|
| Primary capability | Claims resolution across the lifecycle | Document intake and orchestration | Document AI (horizontal, insurance vertical) | Claims decisioning and claims management | Whatever you scope |
| Insurance-specific | Yes - P&C claims only | Yes | No - multi-industry platform | Yes - P&C claims | By construction |
| Covers the claim after intake | Yes - coverage, settlement, payment, recovery | Routes validated work downstream | Extraction output into your systems | Yes - adjuster workflow and decisions | Scope-dependent |
| Fraud investigation | Yes - built-in, 15+ phases in parallel | Not described on their public pages | Fraud detection workflow, incl. document forgery | Not described as an investigation module | Rare in practice |
| Subrogation and recovery | Yes - every file screened | Not described on their public pages | Not described on their public pages | Not described on their public pages | Rare in practice |
| Strongest document edge case | Forensic analysis of altered documents | Emails, SOVs, loss runs | Handwriting, faxes, degraded scans | Adjuster file content | Depends on the model you pick |
| Claims system of record | Works inside it - no rip and replace | Routes into it | Feeds it | Overlay, or replaces it | You integrate it |
| Time to production | Scoped per line of business, no core replacement | Not published | About 90 days, per their site | Not published | Outruns the original estimate |
| Best for | Resolving claims end to end | A like-for-like Bevaya bid | Dirty paper and handwriting | Adjuster throughput | Unusual requirements |
Who should use what
Indico Data
You want a second bid that does what Bevaya does
- Same intake, enrichment, and orchestration model
- Comparable enterprise carrier references on its own site
- Publishes data lineage, confidence scoring, and explainability
- Spans underwriting submissions as well as claims
Hyperscience
Your intake is handwriting, faxes, and bad scans
- Claims 99.5% data-extraction accuracy on its insurance page
- Explicitly handles cursive, faxes, and mobile photos
- States a typical implementation of about 90 days
- Useful outside insurance if other departments need it too
Five Sigma
Adjuster capacity is the constraint, not document intake
- Clive layers onto an existing claims management system
- Also available as a standalone AI-native claims platform
- Covers 11+ P&C lines on its public site
- Carries Luminary status in Celent's 2026 North America P&C claims report
Hesper AI
Your problem starts after the documents are clean
- Carries the claim from first notice to final recovery
- Investigation-grade evidence behind coverage and settlement decisions
- Built-in fraud investigation and subrogation screening
- Wrong choice if you only need better document extraction
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