AI Research & Advisory

The tools are here.
The workflows aren’t.

Marteno diagnoses, designs, and prototypes AI workflows for institutional investment teams — starting with one research bottleneck at a time.

Working with

Engagements

Three ways we work.

A workflow is not a prompt. We move from problem to embedded routine — not tool demo to hype cycle.

  1. Diagnostic

    We map how your analysts and PMs actually work today, identify leverage points, and surface what’s safe to automate — grounded in your research process, not generic tooling.

  2. Prototype

    We design and build AI-augmented workflows that fit your process, governance, and compliance standards. Specific routines, not chatbots.

  3. Embed

    Rollout, enablement, and measurement. We help the workflow stick — inside your existing research cadence, inside your existing tools.

Research happens in workflows, not tools.

Thinking

Writing on AI in institutional investing.

Practical writing on where AI is actually helping buy-side teams — and where it isn’t.

  1. AI Might Be Wrong · April 2026

    Can AI Pick Stocks?

    A PM’s take on what the evidence actually shows.

  2. AI Might Be Wrong · March 2026

    2031: AI and the Asset Management Crisis

    A structural view of where AI lands in the industry over the next five years.

  3. AI Might Be Wrong · February 2026

    I Built an Investment Committee That Debates Stocks

    A working multi-agent system, and what it reveals about research workflows.

More from AI Might Be Wrong →

Current Deck · March 2026

AI Investing for
Investment Teams.

A practical deck on where AI is actually helping buy-side teams today — and where it isn’t. Written for analysts, portfolio managers, and heads of research.

Download PDF

PDF, March 2026 edition.

Background

Built by a buy-side operator.

Marteno is led by Jeremy Leung — formerly at UBS, with close to two decades in institutional investment management. We exist because AI capability has outpaced the workflows investors actually use. Our job is to close that gap from inside the process, not from the outside in.

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One bottleneck at a time.

We work with institutional investment teams considering, piloting, or scaling AI inside fundamental research.