Point

Most wealth and asset managers carry a structural data problem that gets worse as the business grows: investment data sits fragmented across custodians, portfolio management systems, spreadsheets, and third-party managers, with no single reconciled source. Point was founded in 2017 by investment management practitioners to address exactly this, building an Investment Data Intelligence (IDI) platform that sits between existing books of record and the systems where teams actually consume intelligence.

The platform’s core component is an Independent Investment Book of Record (IIBOR), which aggregates data across all asset classes, custodians, and managers into a proprietary, reconciled data warehouse using a bi-temporal architecture. From there, Point’s Intelligence Engine runs both persistent and on-demand analytics, and its Reporting Engine generates custom client PDF reports automatically. A dedicated AI layer, Point AI, generates role-specific briefing notes for relationship managers, investment teams, and operations staff directly from the underlying analytics.

Point is explicit about what it is not: it does not replace a PMS, CRM, or client portal, and does not offer an end-client digital experience. It is designed to sit alongside these systems and feed them clean, reconciled data. Clients include single family offices managing complex multi-custodian portfolios, as well as discretionary managers and fiduciary advisors.

Key capabilities include:

• Independent IBOR with automated data collection and reconciliation across custodians and managers
• Deterministic analytics engine with both persistent and on-demand calculation modes
• AI-generated meeting briefs and portfolio summaries with role-specific outputs
• Pixel-perfect automated client PDF reporting with custom template support
• Open data sharing interface for integration with third-party CRM, portal, and analytics tools

Pricing is not publicly disclosed. Firms that already have a PMS they are satisfied with and want a data orchestration layer above it are the natural fit; firms expecting a front-to-back operational system are not.