Roots

Name: Roots
Brand: Roots
Rating: 4.8 (2 reviews)

Bevaya is the AI Agent platform built for insurance. (Visit bevaya.ai)

Est 2018|Valuation $92.2M|Raised $44.4M|8 Ref Customers

LinkedIn 17K|Web traffic 8K|FTEs 153|HQ New York, New York, US

Published Oct 10, 2026

01Common complaints

- If transparent self-serve pricing and rapid procurement without vendor engagement are required, consider vendors with published tiers or marketplace listings. - If the core need is generalized document extraction across many departments, a horizontal IDP vendor may be a better fit than a product positioned around insurance-specific agents. - If procurement requires abundant independent third-party review evidence (G2/Capterra/TrustRadius), this vendor currently appears to have limited public review footprint specific to the insurance product; plan reference calls and direct validation accordingly. - If the organization cannot support integration and change management (e.g., cannot allocate subject-matter experts to validate outputs, manage exceptions, and revise workflows), agentic automation initiatives often do not reach expected outcomes. - **Limited public third-party validation** - Vendor-published performance claims exist, but independent benchmarking and broad public customer reviews were limited in this research pass. - **Name collision risk** - Products and companies named "Roots", "Root", or "ROOT" exist in other domains, which can complicate searches on review platforms and community sites; verify entity details during diligence. - **Roadmap visibility** - No detailed public product roadmap was found; typical for enterprise vendors. Request roadmap commitments aligned to specific lines of business and integrations.

02Why they buy

- **Insurance-focused product positioning** - The vendor emphasizes an insurance-trained model and insurance-specific agent workflows, presented as tailored to insurance operations. - **Security and compliance signaling** - Public materials state SOC 2 Type 2 and ISO 27001 certifications and cite compliance with HIPAA/CCPA/GDPR. - **Outcome-oriented case examples (vendor-reported)** - Public case studies and customer examples report outcomes such as improved STP rates, reduced handling time, and ROI. Procurement teams should validate reproducibility and measurement methodologies for these outcomes.

03Field reports

Context: limited public third-party review presence

Roots appears to be an enterprise-focused insurance AI vendor, and in this research pass, limited reliable third-party review-platform listings specific to the insurance product were found. Enterprise vendors in niche domains often have fewer public reviews due to NDAs and a small buyer pool; public review absence is not necessarily indicative of product quality, but it increases the importance of direct diligence.

Vendor-published testimonials and claims (not independent)

The vendor's website includes customer success stories and case studies.
These materials present specific outcome metrics that are vendor-reported. Procurement teams should treat such outcomes as vendor-provided and require validation through references and audited metrics.

Community / public commentary (limited and frequently unrelated)

Searches for the vendor often return unrelated entities or products with similar names. Public community discussion specifically about the insurance product was limited in this research pass.

Recommended due diligence steps to compensate for limited public reviews

- Request reference calls with customers in similar lines of business (workers' comp, commercial auto, general liability, property). - Request a list of production deployments and time-to-value metrics, with redacted outcome reports where available. - Request examples of exception handling, accuracy reports, and typical integration patterns. - Independently validate via systems integrators that implement the platform and via outreach to insurance operations leaders who reference the vendor.

1) Insurance claims automation example — vendor-reported STP and ROI

- The vendor describes a claims letter acknowledgement automation that it reports achieved high straight-through processing, increased throughput, and a reported ROI over a measured period. - Critical evaluation: - These metrics are vendor-published; the methodology is not fully disclosed. - Key diligence questions: - Baseline process cost and volume assumptions. - How ROI was calculated (labor savings only? leakage reduction? IT cost included?). - What exception rate remained and who handled exceptions.

2) Large carrier document processing example — vendor-reported processing speed improvements

The vendor highlights a customer achieving material improvements in claims document processing speed and reports vendor-provided figures for hours saved over time.
Critical evaluation:
- Vendor-reported multiples can depend on which steps are measured (e.g., indexing time vs end-to-end cycle time). Request time-and-motion definitions and measurement methodologies.

3) Premium audit automation example

The vendor markets premium audit automation with reported extraction accuracy and ROI metrics for example deployments.
Critical evaluation:
- Confirm whether reported accuracy and ROI are averages, best-case results, or single-customer outcomes.
- Request audited or replicable measurement methodology and clarification on whether ROI figures include platform fees.

04Best fit

- **Company size (practical target)** - Most plausible fit: mid-market to large insurers (often 500+ employees) and brokers/TPAs processing large volumes of unstructured documents. - **Industries/verticals** - Primarily Property & Casualty insurance, including workers' compensation. - **Personas** - Decision makers: COO, Head of Claims, Chief Claims Officer, Head of Underwriting Operations, CIO/CTO, Head of Automation/AI. - End users: claims adjusters, claims operations analysts, underwriting assistants, premium audit teams. - **Pain points the product addresses** - High-volume unstructured inbound documents. - Manual triage, routing, and data entry. - Slow time-to-quote and long claims cycle times. - Leakage and inconsistent handling due to missing or late data. - **Deal qualifiers** - Clear high-volume workflow candidates (submissions intake, FNOL, claims correspondence, premium audit). - Willingness to integrate with core systems. - Measurable baseline metrics (cycle times, touches per claim, leakage indicators). - **Deal disqualifiers** - Low document or transaction volumes (ROI may not justify an enterprise platform). - Highly bespoke processes with limited standardization and no appetite for process change. - Strict on-premises-only mandates without cloud options (the vendor emphasizes cloud hosting on Azure/AWS; confirm any on-prem options).

05The pitch

- **What the product does (objective value proposition)** - Roots is a B2B AI-agent platform designed for insurance operations, focused on automating and augmenting workflows in claims, underwriting, and policy servicing/operations. - The product positioning focuses on: - Automating workflows driven by unstructured insurance documents and correspondence (e.g., submissions, legal demands, medical records). - Improving straight-through processing (STP), reducing manual handling time, and increasing data extraction accuracy for downstream systems. - **Target market and positioning** - Targets property & casualty carriers, brokers, and third-party administrators (TPAs), and insurance operations teams needing document-driven automation. - Positioning: the vendor presents the product as an AI agent platform focused on insurance-specific workflows, with an insurance-specific model referred to as InsurGPT (vendor-branded). - **Company background (founding, HQ, leadership)** - **HQ:** New York, USA. - **Funding and growth (publicly stated signals)** - The company has announced growth-stage funding activity in public materials. The vendor has also reported recent revenue growth and states deployments at multiple large insurers, brokers, and TPAs; these deployment claims are vendor-provided and should be validated during procurement diligence. - **Pricing model (tiers/costs)** - Pricing is not publicly listed on roots.ai; the vendor operates a sales-led procurement model that requires vendor engagement for quotes. - Implication: buyers should expect enterprise pricing likely based on factors such as document/transaction volume, lines of business, number of workflows/agents, environments, and integration scope. - **Total cost of ownership (TCO) considerations** - Likely TCO drivers (inferred from typical enterprise automation/AI rollouts; verify with the vendor): - Implementation services (integration to claims/underwriting systems, email ingestion, document repositories). - Data security and legal review (especially if PHI/PII is included). - Change management and training for adjusters and underwriters. - Ongoing monitoring and exception handling (human-in-the-loop processes). - **Hidden/variable costs to clarify in procurement**: - Per-document or per-transaction fees. - Charges for additional environments (dev/test/prod). - Premium support, SLA tiers, dedicated customer success management. - Costs for expanding into additional lines of business. - **Key competitors / alternatives (4–6)** - Hyperscience (intelligent document processing / IDP) - Shift Technology (claims/fraud-focused AI) - Snapsheet (claims automation platform) - UiPath (RPA + document understanding) - Automation Anywhere (RPA / automation) - Cloud provider LLM ecosystems plus systems integrators (build/assemble custom insurance AI agents using LLM stacks and integration services)

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