o11 provides a governed data foundation that gives approved AI tools access to a firm's institutional context, including documents, email, CRM, data rooms, and market data. The platform creates a permission-aware memory layer for finance teams, enabling AI to operate within enterprise workflows like Google Workspace while maintaining security and compliance controls.
Funding
Funding not disclosed
Founders
Product
Problem
Financial services firms struggle to give AI tools access to the institutional context needed for accurate, relevant outputs. Critical information is scattered across documents, email, CRM systems, data rooms, and market data sources, making it difficult for AI to operate effectively without compromising data governance or security controls.
Solution
o11 creates a permission-aware memory layer that connects approved AI tools to a firm's institutional knowledge. The platform unifies data from documents, email, CRM, data rooms, and market context into a single governed foundation, allowing AI to operate with the full context of the firm while respecting access controls. o11 integrates directly into the enterprise applications teams already use, including Google Workspace, enabling AI to create, edit, and execute tasks within existing workflows. The system preserves evidence and permissions, ensuring that AI-generated outputs remain traceable to source records and compliant with organizational policies.
Target Audience
Primary customers are financial services firms, including private equity firms, investment banks, and other capital-markets organizations that need to deploy AI tools with proper governance and institutional context.
Features
- Unified data foundation that connects systems of record, supporting evidence, and contextual information across the enterprise
- Permission-aware memory layer that enforces access controls when AI tools retrieve and use firm data
- Native integrations with Google Workspace and other enterprise applications for in-workflow AI assistance
- Evidence preservation that distinguishes raw, normalized, curated, and generated content to maintain data provenance
- Entity resolution with matching signals and human review routing for ambiguous data relationships
- Semantic contract definitions for key business terms, formulas, and metrics with ownership and review tracking