Greenbox × Parsons studio class

Tempo, an AI co-pilot for wealth advisors

RoleProduct strategy & prototyping
TimelineSpring 2026 · studio course
Team4-person team · Anisha · Joannah · Jun · Yash

About Greenbox: Greenbox is an AI-native platform for wealth managers, an ecosystem that pulls the scattered tools an advisor uses into one place so they can serve more clients without drowning in software. We were asked to design a product that could live inside it.

My role

Product strategy and prototyping, as part of a 4-person team. I worked on the research and strategy, the problem framing, and building the working prototype.

Try the live prototype ↓

01 / 10

Context

An independent wealth advisor’s job is judgment: reading risk, making the call, earning trust. Without the infrastructure of a big wirehouse like Charles Schwab or Fidelity behind them, though, that’s not where their day goes. Most of it is spent stitching together a pile of tools that don’t talk to each other, eight platforms, five open tabs, and the signal that always seems to arrive after the market has already moved. So we didn’t go looking for a flashy new tool to add to the pile. We went looking for what the pile was missing.

02 / 10

The insight: it’s a workflow, not a feature

Overlapping research artifacts on a dark green field: journey maps, personas, sticky-note synthesis, and workflow frames from the studio
Research chaos — journey maps, personas, and sticky-note synthesis from the studio

Digging through the raw data from our journey maps and stakeholder calls, I noticed the same shape surfacing in every advisor’s day, an invisible loop they run from morning to night. I named it:

It sounds clean. In reality it’s a tangled scribble: drift caught too late, manual trades across platforms, compliance bolted on after the fact, reconciliation siloed so you can’t even tell what’s done versus pending. No tool owned this loop. That gap was the adjacent possible.

It sharpened into our HMW:

How might we enable RIAs to detect market anomalies and track market movements to decide and verify rebalancing strategies, and mitigate risk?

03 / 10

The product: Tempo

Not another tool in the pile, but the layer that watches, tests, and confirms, so the advisor can get back to advising. Four surfaces carry the Detect → Decide → Verify loop.

04 / 10

Morning Brief

Detect

A morning brief that ranks what needs attention before the first call: overnight drift, breaches, market shifts, cash moves. One list, not five tabs.

05 / 10

Rebalance Sandbox

Decide

Test the move before you make it. Model it against real holdings, stress it against scenarios, compare strategies side by side, then commit, only after it’s verified.

06 / 10

Meetings

Detect

Relationship memory, sentiment, and a meeting-ready snapshot, recalled automatically before every conversation.

07 / 10

AI Co-Pilot

The convergence

An always-on monitor that surfaces the next best action with its reasoning.

08 / 10

The principle we wouldn’t break

The AI proposes. You decide. Judgment stays with the advisor. Every recommendation comes with reasoning you can review and override. Tempo amplifies the advisor, it never replaces them. That single rule shaped every screen.

09 / 10

The outcome

A staged roadmap that takes an advisor from fragmented to unified, each layer feeding the next, converging into the co-pilot. The pitch in one line:

Every RIA. Every market. Always ready.
The intelligence to detect risk, the confidence to act on it, and the clarity to prove it.

Tempo is a working product, not a slide deck. Click through the morning brief, markets, rebalance sandbox, verify, and meetings — the same flow an advisor would open before their first call.

10 / 10

Designing for futures, not just today

A product strategy is only as good as the futures it survives. So we pressure-tested Tempo against four of them, a leaner competitor, the $84T generational wealth transfer, SEC regulation of AI advice, and PE consolidation of the RIA market, and found we already had leverage in each: workflow lock-in, advisor-spanning trust, advisor-in-the-loop compliance by default, and a product that scales from solo to firm without a rebuild.

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Designed and Coded by Anisha with the help of Cursor

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