V7 Go
AI platform purpose-built for finance — run LLMs at scale for due diligence and investment intelligence
Enterprise·All audiences·Powered by Bring-your-own LLM (Claude, GPT-4, etc. via MCP)·API available
Key strengths
Document-heavy workflow automation for private markets, insurance, and real estate280K+ documents analyzed per day280+ pre-built AI agents from industry expertsEnterprise-grade security with no training on customer data300+ integrations and MCP supportKnowledge graph connecting firm-wide data sourcesAI document generation (PDF, PPTX, editable outputs)
Enterprise pricing
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Recent changes
- Plans updated: Custom annual pricing scoped per firm, based on platform access, number of users, and document volume processed. No public price list.
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V7 Go — Technical Use Cases
V7 Go is architected for high-volume, document-centric enterprise workflows. Relevant technical deployment patterns include:
- Automated document ingestion pipelines: Ingest and extract structured data from large document volumes (the platform processes 280K+ documents/day) via API, connected to SharePoint, OneDrive, or Google Drive sources
- Private markets deal workflow automation: Integrate with PitchBook and Dealroom via native connectors to enrich deal data; deploy domain-specific AI agents for due diligence document review and extraction
- Cross-source knowledge graph queries: Leverage the firm-wide knowledge graph to run agents that reason across multiple data sources simultaneously — CRM records, data room documents, and market data feeds
- AI-generated report and deck production: Trigger document generation workflows via API to produce PDF or PPTX outputs (e.g., investment memos, insurance summaries, property reports) at scale
- Agent orchestration for insurance and real estate: Deploy pre-built agents from the 280+ library for policy document analysis, lease abstraction, or underwriting support without building custom models
- MCP-compatible agent pipelines: Use MCP support to compose V7 Go agents with external model contexts in multi-agent architectures
Alternatives
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