Embedding AI + Data to Transform Investment Workflows

For investment teams, the promise of artificial intelligence is clear: faster insights, streamlined workflows, and the ability to scale expertise without adding resources. But realizing that promise depends on one critical factor—access to high-quality, structured data. 

Akambo, a Melbourne-based investment management firm, found itself at the forefront of this evolution. With artificial intelligence already embedded across its business, the firm needed a way to connect its workflows to reliable investment data. The solution came through Morningstar’s MCP Server, enabling Akambo to unify data, analytics, and output in a single environment. Akambo associate asset consultant, Gwynn Kijkanakorn, shares their journey. 

The result is a modernized investment workflow—one that is faster, more scalable, and built for the future of advice and asset management.

Akambo was an early adopter of AI, embedding Claude across both investment and operational functions—from manager research and portfolio analysis through to client reporting and investment committee materials. 

As the firm’s use of AI matured, the focus shifted from adoption to optimisation. One of the remaining opportunities was improving the way structured investment data interacted with existing AI workflows. While Morningstar data was readily available to the team, accessing and incorporating that information into AI-driven processes still required additional manual steps. “The opportunity wasn’t access to data— it was making that data seamlessly available within the tools our team was already using every day,” explained Gwynn. “We wanted our investment professionals spending more time analysing information and generating insights, rather than moving data between systems.” 

As an investment manager focused on delivering outcomes for clients, Akambo continually evaluates where internal resources create the greatest value. Rather than allocating time and capital to building and maintaining custom data infrastructure, the firm sought a proven solution that could seamlessly integrate structured fund-level data—particularly for Australian-domiciled investments—into its existing AI-enabled investment ecosystem.

Morningstar’s MCP Server provided the missing link. 

As one of Morningstar’s first MCP clients globally, Akambo gained direct access to Morningstar data within its AI workflows– without requiring a custom build. The MCP Server’s major capabilities–entity detection, data extraction, analyst research–mapped closely to Akambo’s day-to-day processes, from fund screening and manager due diligence to portfolio construction and client reporting.

This shift allowed the firm to move from manual processes to embedded, conversational workflows.

Before adopting the MCP Server, many workflows required multiple steps: exporting data, reformatting it, and then feeding it into Claude. 

With MCP, those steps are consolidated into a single session.

As Gwynn noted, "What previously required navigating multiple screens, exporting data, and reformatting it into a usable structure now happens conversationally and flows directly into the document or presentation being prepared." 

This shift has fundamentally changed how the team works. Analysts and portfolio managers can now: 

• Run screens across thousands of funds
• Extract structures datasets instantly
• Perform calculations and modeling
• Generate charts, reports, and presentations
• Deliver client-ready outputs

And all without leaving their AI environment.

Akambo’s use of the MCP Server spans both its investment management business and Vertex, an affiliated asset consulting firm. 

Vertex supports financial advisers with model portfolios, manager selection, and investment governance. These services require consistent access to performance data, ratings, holdings, and analytics across a large universe of funds. 

The MCP Server gives Akambo access to 5,300+ Australian-domiciled funds and hundreds of datapoints per security, enabling scalable, repeatable workflows.

The most immediate impacts have been speed and efficiency–particularly in fund screening, manager research, and portfolio analytics.

Tasks that previously required navigating multiple systems now happen in minutes.

“The MCP connection makes it possible to run a screen, extract data for dozens of funds, and have it structured and ready for usage in a single session,” said Gwynn. 

For example:

• Fund screening and database building can be performed in a single query
• Manager due diligence combines qualitative and quantitative insights in one workflow
• Portfolio analytics–including tracking error, information ratios, and rolling returns–are generated using Morningstar data as the foundation 

In some cases, the firm has been able to replicate analytics typically performed by dedicated portfolio analysis platforms.

“We’re able to use the MCP as the foundational data layer and then perform calculations and generate outputs in the same session,” said Gwynn.

These productivity gains were evident early in Akambo’s evaluation process—significant enough to justify adoption even before all local data gaps were resolved.

Akambo’s relationship with Morningstar has been defined by collaboration. 

As an early adopter, the firm has played a role in shaping the MCP Server’s development—providing direct feedback on the datapoints and capabilities needed by investment professionals in the Australian market. 

As Gwynn noted, “Morningstar has been highly responsive to our feedback, including adding several managed fund datapoints we requested, which materially enhanced our workflows.” 

This two-way partnership continues to refine the product and ensure it aligns with real-world investment use cases.

For Akambo, the integration of AI and structured investment data represents more than a productivity gain—it marks a shift in how investment work is performed. 

By combining Morningstar’s data with AI-driven workflows, the firm has built an operating model that is:

• Faster, through streamlined processes 
• More scalable, without adding resources
• More accessible, reducing reliance on platform-specific expertise
• More integrated, bringing data, analysis, and output together

“Frictionless access to Morningstar data straight into our AI workflows has been the key,” said Gwynn. “It allows us to extend what we can do as a team without increasing complexity.” This approach is already shaping how the firm delivers value to clients—and offers a glimpse into the future of investment management and advice.

Learn how Morningstar’s Direct AI solutions can help your firm streamline workflows and scale investment insights. 

Gwynn Kijkanakorn and Akambo have not received any cash or non-cash compensation from Morningstar, directly or indirectly, in exchange for this client success story