Supporting agentic workflows with CapRelay

Why tech-first investment firms are accessing CapRelay's data with agents

CapRelay differentiates by teaching LLMs how to think like buy-side analysts, producing far better analysis than what is available through the consumer LLMs like ChatGPT.

As a result, the teams we work with are plugging CapRelay research into agents, to handle tasks like:

• Idea iteration at scale. An agent iterates through companies in a sector, pulling in CapRelay's content, like buy-side quality bull-bear debates, and flagging the names that match themes of interest.
• Pre-meeting prep. Before an IR or management call, an agent assembles the latest CapRelay research into a briefing packet, including the current buy-side debate, recent earnings context, and suggested questions, all from CapRelay, and overlaying this with the firm's internal research.
• Watchlist monitoring. Agents pull earnings reviews and risk pages for watchlist names on a schedule, surfacing the updates that matter for the current thesis.

How CapRelay supports agents

A growing number of investment teams are building research workflows around AI coding agents - tools like Cursor, Claude Code, and Codex that can read, reason over, and act on qualitative semi-structured data. Leading investment firms already use CapRelay as a core content layer inside these workflows.

What makes that possible is how CapRelay delivers research. Every CapRelay research page is built on a markdown-oriented structure. That means the content is clean, sectioned, and machine-readable without any scraping, parsing, or reformatting.

For agentic workflows, this matters. When an agent pulls a CapRelay page, it gets structured text it can reason over immediately, with no PDFs to extract, no HTML to strip, and no prompt engineering to work around messy formatting.

Unlike investment banks or equity research firms that deliver PDFs and slide decks, which are difficult for agents to access and expensive to reformat, CapRelay's architecture is built for a world where research is agent-first.

How you can do the same

Claude Code, Claude Cowork, Codex, and other agents are fantastic for many web research tasks out of the box. However, these agents lack institutional-grade context, so they resort to reading articles from consumer finance websites to piece together answers to even simple questions like, "What were key themes in Microsoft earnings through 2025?" This results in mistakes and consumer-grade analysis.

CapRelay provides the buy-side grade context your agent needs. We provide you with the Skill file and code necessary for your agent to programmatically authenticate to CapRelay, and instantly level up your agent with deep institutional-quality knowledge.

What this means for research teams

The investment teams using CapRelay through agents are giving their analysts more leverage by letting agents handle rote work in the background, so the team can spend more time on the deep research tasks that drive alpha, which no AI can do.

For teams already building agentic workflows, CapRelay is the fastest way to give those agents access to institutional-grade company research across every U.S.-listed name.