Purpose-built for finance

V7 Go is an AI platform designed specifically for private markets, insurance, and real estate investment teams. It automates complex document-heavy workflows from investment diligence to underwriting.

Faster, more reliable processing of complex documents

End-to-end document automation

Build once and deploy across teams. Automate entire pipelines like CIM to PIM, dataroom to IC memo, DDQ completion, portfolio monitoring, and LBO model prep. Trigger analysis-to-document pipelines automatically when new files are uploaded.

Scale recurring processes like deal screening and compliance audits without manual intervention

Specialized AI agents for finance, insurance, and legal

V7 Go includes specialized AI agents for finance, insurance, and legal workflows. These agents break down complex tasks into reasoning steps and use Index Knowledge to query your data more accurately than a standard API call.

More accurate and robust than calling a model provider directly

Context Graph for institutional knowledge

Go beyond standalone AI with the context, integrations, and controls needed to run complex work from start to finish. The Context Graph helps build AI workflows on everything your firm knows.

AI workflows that leverage your firm's collective knowledge

Automated document generation

Generate standardized summary decks, tear sheets, and investment memos. The system can trigger an entire analysis-to-document pipeline automatically when a new document is uploaded to a designated folder.

Consistent, ready-to-use outputs for deal screening and reporting

Enterprise-grade security and controls

Your data stays yours—always. V7 is one of the few AI companies that never trains on your data. Features include end-to-end encryption, fine-grained access controls, audit logs across every workflow, and an in-house security team.

Secure, compliant AI workflows with full auditability

• Purpose-built for finance, insurance, and real estateV7 Go is an AI platform designed specifically for private markets, insurance, and real estate investment teams. It automates complex, document-heavy workflows such as deal screening, due diligence, investment memos, portfolio reporting, submission ingestion, underwriting, policy review, claims processing, lease abstraction, and deal analysis.
• Proven results with real customersCustomer testimonials on the site report significant improvements: 21x faster processing, 54% fewer errors, and the ability to screen 5x more opportunities with the same team (Star Mountain Capital, a $5B alt asset firm). Another customer replaced three separate tools and cut workflow costs by 40%. One firm went live in six weeks instead of an estimated $2M and 18 months in-house build.
• Precision AI with human-in-the-loop controlsV7 Go breaks down complex tasks into reasoning steps using Index Knowledge, enabling LLMs to query your data more accurately than a direct API call. It includes conditional logic to route high-sensitivity data to human review, building robustness into AI-powered workflows. The platform supports a variety of foundation models and allows you to connect your own API keys.
• Automated document generation and recurring workflowsThe document generation feature supports both one-off tasks and fully automated, recurring workflows. For example, when a new Confidential Information Memorandum (CIM) is uploaded to a designated folder, an AI Agent can process it and generate a standardized summary deck without manual intervention—ideal for scaling deal screening, compliance audits, or periodic portfolio reporting.

• Pricing is custom, not publicV7 Go does not list fixed prices. Pricing is custom-built based on three components: a base platform fee (with access to AI agents or data labeling tools), user-based access with customizable roles, and volume-based pricing that scales with document processing volume. You must contact them for a quote.
• V7 Go is separate from V7 DarwinV7 Go and V7 Darwin are separate products. V7 Darwin is a data labeling platform for annotating images, videos, and medical imaging to train your own models. V7 Go specializes in applying foundation models to automate document-intensive workflows. They are not the same product.
• OCR capabilities include printed and handwritten textV7 Go can recognize both printed and handwritten text using advanced optical character recognition (OCR) technologies, as well as charts, diagrams, and logos. However, the site does not specify accuracy rates or supported languages beyond this general capability.
• Integrations and MCP are mentioned but not detailedThe site lists 'Integrations & MCP' and 'Claude MCP' as platform features, but does not provide specific integration names or details on the scraped pages. No specific third-party integrations (e.g., CRM systems) are named in the content provided.

Investment Diligence Automation

V7 Go helps private markets teams turn complex deal documents into faster investment decisions. It supports deal screening, due diligence, investment memo creation, and portfolio reporting, enabling firms to process hundreds of complex deal documents per week.

Insurance Submission Ingestion & Underwriting

Insurance teams use V7 Go to automate document-heavy processes such as submission ingestion, underwriting triage, policy review, and claims processing, turning them into reliable production workflows.

Real Estate Deal Analysis & Lease Abstraction

Real estate investment teams leverage V7 Go for deal analysis, underwriting, lease abstraction, and portfolio reporting, turning acquisition and asset data into faster investment decisions.

Automated Document Generation & Workflows

V7 Go can trigger an entire analysis-to-document pipeline automatically. For example, when a new Confidential Information Memorandum (CIM) is uploaded to a designated folder, an AI Agent processes it and generates a standardized summary deck without manual intervention, ideal for scaling recurring processes like deal screening, compliance audits, or periodic portfolio reporting.

Sign up for a free V7 Lab account and create your first workspace for your project.

Upload your image or video dataset directly from your local machine or connect a cloud storage bucket (AWS S3, GCS, or Azure).

Define your annotation ontology — the classes and label types (bounding box, segmentation, keypoint) your model needs to predict.

Assign annotation tasks to your team or enable auto-annotation to let AI generate initial labels for review and correction.