Today's AI models can reason through complex tasks, but lack business context like identifying current fund reports or matching entities across systems. V7, founded by Rizzoli and Edwardsson in 2018, created V7 Go to teach AI systems business operations. V7 Go uses GPT-5.6 Luna to extract information from millions of files, organizing them in the Context Graph that connects entities, relationships, and evidence for MCP search and repeatable workflows spanning hundreds of steps.

The Context Graph solves the problem of agents rediscovering context on every request, which wastes time and misses key information. When data arrives, V7 Go connects to repositories like Share Point and Google Drive, scanning for entities and populating a graph that's cheaper and faster to traverse than long-context approaches. The system maintains an auditable trail and preserves cited evidence to original sources.

On the HERB benchmark, V7's retrieval system improved by 69% and reduced hallucinations by 38%. Customers report significant gains: asset managers screen deals 21x faster, reducing a full-day process to 15 minutes, while a financial services team cut review time from over 100 hours to under 10 hours, saving $12,000 in expert costs per engagement.