Introducing Point Self-Service

Point Self-Service gives clients direct access to trusted investment intelligence, enabling bespoke analysis, deeper exploration and faster answers while maintaining a single, governed source of analysed investment data truth.

Direct access to trusted investment intelligence

Through APIs, Power BI semantic models, MCP and LLM integrations, clients can interact with their data in the way that best suits their business. This flexible, increasingly headless approach separates trusted investment intelligence from any single interface, allowing it to support reporting, analytics, business intelligence and emerging AI initiatives while maintaining governance, consistency and control.

Client expectations continue to evolve

Firms are increasingly looking beyond reports and dashboards towards more flexible ways of working with data. At the same time, analytics and AI initiatives are placing greater demands on data quality, governance and consistency.

To meet these demands, we've been developing the latest version of Point Self-Service, extending Point's long-standing mission of transforming complex investment data into a managed, trusted and usable business asset.

Point Self-Service enables users across a client’s organisation to access and analyse investment intelligence through the tools, applications and interfaces that best suit their needs, without creating different versions of the underlying business information.

Accessing trusted investment intelligence

At the heart of Point Self-Service is Point's investment intelligence foundation.

Rather than simply exposing raw underlying data, Point provides access to governed information that already incorporates business logic, calculations, reconciliations, definitions and investment context. This allows users, reports, analytics platforms and AI systems to work from a common understanding of the business.

Clients can create bespoke queries, perform period-on-period analysis and explore information at both granular and enterprise levels while remaining aligned with operational reporting and oversight processes.

The result is greater self-sufficiency for business users, faster access to answers and increased confidence in the consistency of information being used across the organisation.

Enabling modern analytics and AI

Modern data strategies require more than access to governed datasets. Organisations need a trusted intelligence layer that can be consumed consistently across reporting, analytics and AI applications.

Point Self-Service extends access to that intelligence layer through APIs, Power BI semantic models and emerging AI integration patterns such as MCP and LLM-enabled workflows. This allows firms to incorporate trusted investment intelligence directly into their own analytical environments while maintaining control, oversight and governance.

Throughout testing, we focused on usability, performance and real-world self-service use cases, enabling clients to independently answer increasingly sophisticated business questions without relying on predefined reports or specialist support.

A foundation for the future

Point Self-Service represents an important milestone in our vision to make trusted investment intelligence more accessible.

By extending direct access to the intelligence that underpins the wider Point platform, clients can accelerate analysis, support AI initiatives, adapt how information is consumed across the business and derive greater value from the data they already own, while maintaining consistency, governance and trust.