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Weav
Founded 2021 · 19 employees on LinkedIn · 14 known investors
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Weav.ai offers an AI-native, agentic decisioning platform for insurers that unifies a company's data, guidelines, and best practices into a centralized knowledge framework, then uses AI agents to generate recommendations for underwriting, premium audit, and claims. It provides pre-configured knowledge graphs, an agentic decision engine, and an API-first, no-code architecture with human-in-the-loop review for the insurance industry.
Also known as Weav.ai
Founders & leadership
Weav was founded in 2021 by Peeyush Rai and Jeff Heine.
Investors · 14
How we know: Better Capital's portfolio page · the VCSheet dataset · Not right? Tell us
How we know: the VCSheet dataset · Not right? Tell us
How we know: NewBuild.VC's portfolio page · Not right? Tell us
How we know: Sierra Ventures's portfolio page · Not right? Tell us
How we know: techcrunch.com · Not right? Tell us
How we know: funding news · techcrunch.com · Not right? Tell us
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How we know: techcrunch.com · Not right? Tell us
How we know: funding news · Not right? Tell us
How we know: funding news · techcrunch.com · Not right? Tell us
Funding
SEC filings, press & company announcements- Undisclosed amountseed roundApr 2021
Foundation Capital (lead), Abstract Ventures, Box Group, Commerce Ventures, LocalGlobe, Operator Partners, SV Angel, Y Combinator
Source ↗
Source: company announcements and press reports — follow each round's link for the claim.
Company profile
researched Aug 2026Weav.ai provides an AI-native, agentic decisioning platform purpose-built for property and casualty (P&C) insurance. The platform is positioned to unify knowledge, decisions and actions across an insurer's organization, with agentic AI that ingests, interprets and analyzes information and generates recommendations across three functional areas: underwriting, premium audit and claims. For underwriting, the company describes leveraging experience, best practices and guidelines to support risk assessment; for premium audit, improved classification, exposure measurement and documented adherence to state regulations; and for claims, faster cycle times, prevention of unnecessary payouts, reduced litigation, early fraud detection and consistent documentation.
The product includes pre-configured Score Cards, Knowledge Graphs and Next Best Action recommendations organized by industry (for example manufacturing, construction and commercial property) and by line of business, all configurable by business users. An agentic decision engine supports insurance activities including ingestion, clearance, triage, risk, exposure and loss history analysis. The platform emphasizes an API-first architecture, no-code configuration, and human-in-the-loop review and approval of critical decisions.
The ingestion engine is described as contextually interpreting insurance documents such as ACORD forms, statements of values (SOVs), claims forms, payroll and tax reports without requiring field mapping or rigid rules, with evaluation agents that surface conflicts and low-confidence data for human review and augment data from external sources.
Business model
Weav.ai sells an AI decisioning platform to property and casualty insurance carriers. The platform is offered either as an API-first intelligence layer embedded in a customer's existing systems and workflows or through Weav.ai's own purpose-built workbenches, and can be deployed in the customer's private cloud or on-premise. Pricing terms are not disclosed in the available sources.
Traction
The website references a 'Trusted By' section but the available sources name no customers, revenue figures, funding rounds or headcount for Weav.ai.
▸Full profile — market position, technology, go-to-market, geography
Market position
Weav.ai positions itself as an AI-native decisioning platform for P&C insurance, distinct from generic automation tools, by shipping insurance-specific knowledge graphs, scorecards and workflows. The available sources contain no third-party market share, customer count or competitive benchmarking data.
Sources describe differentiation in terms of insurance-specific pre-built assets and architecture: line-of-business and industry-specific knowledge graphs and scorecards shipped pre-configured and editable by business users; AI-based document ingestion that avoids field mapping and rigid extraction rules; a rapid insurance connector framework said to allow new connectors to be built within a day; MCP client and server support for interoperating with other agentic systems; model-agnostic orchestration across commercial and open-source LLMs with optional fine-tuning for specialty lines; and deployment inside the customer's private cloud or on-premise.
Technology
The platform combines AI document ingestion, industry-specific knowledge graphs representing business entities, relationships and hierarchies, AI scorecards for quantitative evaluation against guidelines, and an agentic decision engine producing Next Best Action recommendations. It is model-agnostic, orchestrating commercial models from OpenAI (GPT family) and Anthropic (Claude family) alongside open-source models from Meta (Llama family), DeepSeek and Mistral, with optional fine-tuning for specialty lines. It supports bi-directional integration via APIs and agentic methods, ships pre-built integrations with Guidewire, Verisk, Nearmap, OSHA, HPD, Google and the Nexus audit system, and includes a Rapid Insurance Connector framework. Weav.ai agents include MCP clients that communicate with external MCP servers such as Salesforce and ServiceNow, and the company operates an MCP server allowing other agentic systems to orchestrate workflows with Weav.ai agents. Deployment options include private cloud and on-premise; the platform is described as SOC 2 Type 2 compliant and supports SSO via Okta, Azure AD, Auth0 and other SAML-compliant systems.
Go-to-market
The company's website markets directly to insurers via demo requests, positioning the platform both as an embedded intelligence layer for existing core systems and as standalone workbenches. Pre-built integrations with core insurance systems and data vendors are used to reduce implementation effort.
Property and casualty insurance carriers and their underwriting, premium audit and claims functions, including underwriters, claims adjusters and premium auditors.
Geography
Not stated in the available sources; the platform references adherence to US state insurance regulations and integrations with US-oriented data sources such as OSHA and HPD.
Compiled by commissioned research from 8 cited public sources — announcements, filings, and press listed under research sources below.
Key figures
latest reportedCompany-reported or press-reported figures, each dated to when it was claimed — not independently audited.
Related companies · 5
Companies working in the same space as Weav.
▸Research sources · 8
primary sources listed
- Weavweav.ai · web
8 public sources were cited for this profile; the first-party ones are listed here.
Frequently asked questions
- What does Weav do?
- Weav.ai sells an agentic, AI-native decisioning platform built for P&C insurance underwriting, premium audit and claims.
- Who founded Weav?
- Weav was founded by Peeyush Rai, Jeff Heine in 2021.
- Who are Weav's investors?
- Weav's investors include Better Capital, Mango Capital, NewBuild.VC, Sierra Ventures, Abstract Ventures, BoxGroup, Commerce Ventures, Foundation Capital and 6 more.