Turn a dataset into a decision surface
Investors choose an asset, assemble signals, compare chains, and inspect models within configurable dashboards.

BRAND · PRODUCT · LAUNCH · 2023–2025
Fibonacci's data product and Gamma's next product chapter
Problem
Fibonacci needed to make institutional crypto data useful to retail investors. Gamma later needed consistent agent, portfolio, and early-access flows within its existing product.
Approach
For Fibonacci, organize data into configurable dashboards and reusable signals. For Gamma, extend the existing component library and connect campaign language to onboarding and portfolio states.
Outcome
Delivered Fibonacci's identity, dashboards, model views, and authentication. Added Gamma's next product flows and Lockbox campaign while preserving its established design foundation.
Key decisions
Investors choose an asset, assemble signals, compare chains, and inspect models within configurable dashboards.
A radial data object and restrained spectrum connect Fibonacci's brand to charts and onboarding.
Gamma's next phase extends its existing component library to preserve continuity.
Parameters, activation, performance, and next actions make autonomous agents inspectable.
Focused portfolio views retain consistent account and exposure context.
Lockbox, early access, points, and referrals share language from campaign through onboarding.
Project chronology
The chronology separates two bodies of work rather than presenting them as one redesign: Fibonacci began with a dataset and a new retail-facing product model; Gamma began with an established library that I extended into its next phase.
01 / 02
I redesigned Fibonacci's brand and built its realtime dashboard UX/UI around retail investors: asset selection, signals, model detail, and authentication. Squads Labs later announced a partial codebase acquisition in May 2024.
01
The dashboard turns realtime liquidity, risk, and market signals into inspectable models and performance history.
02
Research shaped an asset-first flow: assemble signals, preview live data, compare chains, and retain relevant history.
03
A radial mark, restrained spectrum, and orbital motion connect the API, website, dashboard, and onboarding.
04
Market, time range, sources, and confidence stay alongside the charts. The mockups proposed Matplotlib for visualizing TVL, volume, price, slippage, and pool composition.
05
Choose an asset, then select signals with explanations and previews so advanced measures are understandable before adding them.
06
The vector source preserves token discovery, market context, alerts, and navigation at inspection quality.
07
Login, social authentication, passwords, and signup carry the dashboard's orbital identity into account creation.
08
Explore the original dashboard, model, creation, and account states.
09
The brand book documents the radial mark, typography, imagery, motion, and color.