V7Labs

AI workflows for document-heavy finance, insurance and real estate operations

Intermediate API
Screenshot of V7Labs, AI workflows for document-heavy finance, insurance and real estate operations

What is V7Labs?

V7Labs is an AI search tool. V7 Go builds AI agents and workflows for document-heavy operations in private markets, insurance and real estate, backed by connected knowledge graphs, hundreds of prebuilt agents, spreadsheet and slide generation, and enterprise integrations. Sold through demos and solutions engineering rather than self-serve plans.

V7 (marketed as V7 Go) is a platform for automating document-heavy workflows in private markets, insurance and real estate investment. Instead of a single chatbot, it packages work into named agents and multi-step workflows: deal screening, due diligence, investment memos, submission ingestion, underwriting triage, policy review, claims processing, lease abstraction and portfolio reporting. The pitch is reliability on complex material where errors carry real cost, and the company reports outcomes such as faster processing and fewer errors at customer firms. The product rests on a context layer the vendor calls knowledge graphs. Portfolio databases, filings and earnings transcripts, data rooms, financial models, market and pricing data, decks and news feeds are connected and made searchable, so agents work against a firm's own material rather than a bare model prompt. More than 280 prebuilt agents cover narrow job titles (zoning consultants, surety bond processors, treasury management sales officers, reserving actuaries), and teams can build their own. Outputs can be exported to PDF, PPTX, Google Drive or SharePoint, which matters for investor-ready tables, slides and documents that still need editing. Day to day, a diligence or underwriting team loads a batch of documents, selects or configures an agent, and reviews the extracted fields and generated analysis. Excel capability is a stated strength: the site claims fourth place globally on SpreadsheetBench, which points to spreadsheet generation and manipulation as a first-class feature rather than an afterthought. Integrations run over 300 connectors plus MCP, with API access for custom links. The tool suits mid-size and large firms in finance, insurance and property that already have defined processes and want them automated end to end, not solo knowledge workers experimenting with prompts. Compared with general-purpose AI assistants, V7 trades breadth for vertical depth and governance. Buyers should expect a demo-led sales process and a solutions engineering relationship rather than self-serve signup.

How do you use V7Labs?

  1. 1Book a demo and scope your workflow
    Start by requesting a walkthrough. Come with one concrete process, such as underwriting triage or lease abstraction, and the documents it consumes.
  2. 2Pick an industry starting point
    Review the finance, insurance or real estate pages to see which prebuilt workflows map to your process before evaluating build options.
  3. 3Browse the agent library
    Scan the agent catalogue for a close match to your use case, such as contract audit, and note which inputs and outputs it expects.
  4. 4Connect your data sources
    Link the repositories your team already uses, from data rooms and filings to spreadsheets and market data, so agents can retrieve firm context.
  5. 5Build and test the agent inside V7
    Configure prompts, fields and output formats, then run a batch of sample documents and check extraction accuracy before wider rollout.
  6. 6Export outputs and document the workflow
    Once results hold up, send generated tables, slides and memos to PDF, PPTX, Drive or SharePoint and record the steps for the team.

Pros and cons

Pros

  • Purpose-built agents for named finance, insurance and real estate tasks rather than generic promptsAI
  • Knowledge graphs connect internal data rooms, filings, models and news into a searchable context layerAI
  • Document generation exports to PDF, PPTX, Drive and SharePoint, keeping output editableAI
  • Over 280 prebuilt agents plus custom agent building and API or MCP accessAI
  • Reported customer results include faster processing and measurable error reductionAI

Cons

  • No public pricing, so budgeting requires a sales conversation before any commitmentAI
  • Focus is narrow: teams outside finance, insurance and real estate will find little hereAI
  • Effectiveness depends on connecting clean internal data, which is real setup workAI
  • Demo-led onboarding and solutions engineering may not suit buyers wanting instant self-serve accessAI

How much does V7Labs cost?

Support

Sales is demo-led, with a dedicated Solutions Engineering team that customers credit for turning data challenges into working solutions quickly. No public help centre details are given on the homepage.

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Integrations

Over 300 integrations and MCP connections are advertised, including SharePoint, Box, Azure, S&P Market Intelligence, SEC filings and news sources, with API access and support for custom integrations.

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Features

Agent library of more than 280 prebuilt agents, custom agent building, connected knowledge graphs spanning data rooms, filings, financial models and market data, document and slide generation with PDF, PPTX, Drive and SharePoint export, spreadsheet capability ranked fourth globally on SpreadsheetBench, and enterprise security controls.

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Frequently asked questions about V7Labs

  • Does V7Labs have an API?
    Yes, V7Labs offers an API.
  • How do you use V7Labs?
    The walkthrough on this page covers 6 steps: 1. Book a demo and scope your workflow 2. Pick an industry starting point 3. Browse the agent library 4. Connect your data sources 5. Build and test the agent inside V7 6. Export outputs and document the workflow.
  • What platforms does V7Labs support?
    V7Labs is available on Web App.
  • What does V7Labs integrate with?
    Over 300 integrations and MCP connections are advertised, including SharePoint, Box, Azure, S&P Market Intelligence, SEC filings and news sources, with API access and support for custom integrations.
  • What are the limitations of V7Labs?
    No public pricing, so budgeting requires a sales conversation before any commitment. Focus is narrow: teams outside finance, insurance and real estate will find little here. Effectiveness depends on connecting clean internal data, which is real setup work.

Status

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Added10/21/2026

Platforms

Web App

Pricing

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