Deep Research Agents
AI colleagues that run in the background to keep research updated and reliable.
The Case for Agents
The volume of primary financial content continues to grow. Analysts spend disproportionate time monitoring routine releases, maintaining trackers, and keeping notes current instead of focusing on interpretation and investment judgment.
Deep Research Agents address this directly. They run continuously in the background, process primary sources within seconds of publication, and surface only material insights. They operate with the consistency and precision expected from a trusted colleague, taking on work such as tracking guidance, maintaining primers, and synthesizing updates. Outputs are reliable every time and ready for immediate use in professional workflows.
Always-On Coverage
Agents act as persistent background processes. They capture new primary sources as soon as they are published and generate research-ready updates automatically. Analysts no longer need to check for changes manually or reassemble fragmented inputs.
This ensures analysis always starts from a complete and current foundation—whether for a single core holding or across a broader coverage universe.
Validated, Data-Backed Outputs
Every Agent output is grounded in primary sources such as earnings calls, press releases, and filings. Each statement links back to its origin, enabling analysts to verify details instantly.
The outputs are designed for immediate use in models, internal notes, and client communications, reducing the time between new information and actionable analysis.
Integrated Into the Analyst Workflow
Deep Research Agents fit naturally into existing research processes. They can be launched on demand, scheduled, or triggered by events such as earnings releases.
Analysts can choose from pre-configured agents such as earnings reviews, company primers, and data trackers, or create custom instructions to fit their specific needs. Agents can build on each other’s outputs: for example, converting an in-depth earnings review into a concise bullet-point overview for colleagues or clients, or extending a detailed primer into a recurring tracker.
This flexibility allows coverage to scale while ensuring consistency and professional standards across deliverables.
Example: An Earnings Season Workflow
During earnings season, an analyst can activate a pre-configured In-Depth Earnings Review Agent. As soon as the company publishes its earnings, the agent compiles a detailed summary note. Within minutes, the note is complete and available for use.
As additional information becomes available, for example, once the earnings call transcript is released or the 10-Q/10-K filing is published, the same note is automatically updated to reflect the new content. The analyst always works from the most current version without having to maintain it manually.
A Research Note Repurposing Agent can then be linked to this output. It adapts the detailed earnings note into a concise bullet-point overview, aligned with the instructions set by the analyst. Each time the original note is updated, the summary version refreshes as well, ensuring that what is shared with colleagues or clients is accurate and up to date.
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Frequently Asked Questions (FAQ)
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