AI-Powered Market Intelligence
Mobile UX/UI DesignProduct Manager & Designer

AI-Powered Market Intelligence

Mobile-First Enterprise App Design

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Project Type

Mobile UX/UI Design

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Timeline

In Progress

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Key Features

Conversational AI, Real-time Alerts, Streaming UX

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My Role

Product Manager & Designer

Designing the future of market research—a mobile application delivering conversational AI search, source-grounded summaries, and personalized intelligence for enterprise users.

1

Overview

The Challenge

Enterprise users need rapid, trustworthy, and actionable insights from dense financial content like earnings calls, filings, and research while on the move, but traditional apps struggle to provide meaningful summaries on small screens.

Our Solution

A mobile-first application combining the power of an AI assistant with the rigor of enterprise data, offering source-grounded summaries and natural conversational search that builds trust over time.

Core Objectives

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1

Design an intuitive conversational AI search experience

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2

Ensure absolute trust via source-grounded outputs

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3

Deliver personalized, real-time intelligence feeds

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Optimize rendering of dense financial data for mobile

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5

Enforce enterprise-grade security and compliance

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Strategic Design Rationale

Translating high-density desktop financial data into a low-friction, high-trust mobile experience.

PHASE 01

Conversational AI vs. Traditional Filters

Drastically reduces time-to-insight. Users can simply ask natural language questions rather than navigating complex menus or sifting through search results on a small screen.

PHASE 02

Strict Source-Grounded Outputs

Prioritizes trust mechanisms over raw AI generation. Every response includes inline citations and source previews, allowing users to instantly verify the exact earnings call or filing.

PHASE 03

Proactive 'Smart Event' Alerts

Moves from a 'pull' to a 'push' model using OS-native features. Synthesized, actionable insights are pushed to the lock screen the moment market-moving events occur.

PHASE 04

Automated Audio & Text Briefings

Personalized daily briefings can be consumed as short text snippets or generated audio, enabling hands-free consumption during commutes.

PHASE 05

Streaming Latency & Native Patterns

Streaming token rendering combined with platform-native components ensures the AI generation feels incredibly fast and premium on both iOS and Android.

3

Interactive Prototypes

Core App Functionality

A powerful suite of tools designed to provide actionable intelligence at your fingertips, anytime, anywhere.

Conversational AI Search

Ask complex market questions in natural language and receive detailed, source-grounded answers instantly.

Show AAPL Q3 earnings highlights
Revenue grew 8% YoY to $94.9B...[1]
Apple 10-Q ↗

Real-Time Sentiment Analysis

Monitor market sentiment with AI-driven analysis of news, earnings calls, and financial reports as they happen.

Bullish
72%
Neutral
18%
Bearish
10%

Updated just now

Smart Event Alerts

Set custom triggers for portfolio-relevant events and receive push notifications before the market reacts.

MSFT earnings beat — +4.2%

2 min ago · High priority

Fed holds rates at 4.5%

18 min ago

Automated Briefings

Start your day with generated audio and text summaries covering the most impactful events tailored to your watchlists

Morning Briefing — Mar 29, 2026

3:42
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UX & Platform Patterns

iOS 26 Best Practices

Leveraging large titles, native bottom sheets, context-aware toolbars, advanced haptics, and Dynamic Type support.

Android 16 Features

Incorporating Material dynamic color, predictive back navigation, modal bottom sheets, edge-to-edge layouts, and foldable layouts.

Core User Flows

AI Search & Conversational Query

AI Summary Card & Transcripts

Personalized Intelligence Feed

Company Deep Dive Dashboard

Alerts & Notification System

5

Design System & Trust

Native iOS & Android Architecture

Built using native iOS (SwiftUI) and Android (Jetpack Compose) frameworks to ensure rapid, highly customizable styling while sharing a core component architecture and design tokens.

Latency Strategy

Addressing AI wait times with streaming token rendering, progressive skeleton UI, and informative status indicators.

AI Interaction Patterns

Focusing on streaming responses, inline citation references, confidence indicators, and clear boundaries between AI and original source text.

Trust Mechanisms

Mandatory citation layer, source preview drawers, timestamping, and expandable reasoning to mitigate AI hallucination.

6

Implementation Plan

% of users making first query

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Citation click-through rate

0%

Daily Queries & Alert interactions

0%

Weekly Active Users

0%