Akira - Agentic (AI) Personal Finance iOS App (Case Study)

Mumo Antony

Akira - Agentic (AI) Personal Finance iOS App (Case Study)

Scope

UX & visual system for an AI-first personal finance app that helps users set goals, optimise budgets, and build workflows across everyday tools (Notion, Sheets, Calendar, Slack).

Focus of Case Study

Key design decisions and the process that turned agent behaviour into a simple, motivating experience.

Problem Statement

People want control of money without manual work or judgmental interfaces. Our brief was to automate useful actions with transparent AI, make goals motivating, and connect finances into the tools people already use.

Users and Success Metrics

Primary user

Akira is designed for a 28–38, salaried or freelance professional, plans big and small expenses, uses digital tools to stay organized and avoid surprises.

Key Metrics

Time-to-first goal and budget setting
AI optimisation rate (how frequent a user approves an AI optimisation)
Workflow activation (integration per engaged user)

Budget Optimisation Metrics

Percentage % of AI suggested savings applied
Average Smart Savings by AI per user
Suggestion visibility and removal rate

Design Goals & Principles

Make AI a necessity and not an addition
Be motivating and not punitive
One primary action per surface; details in expanded view
Scannable layouts with clear numerical hierarchy
Integrate with tools users already use

Core Design Decisions

Goals copy

Goal card: Simple layout that shows goal title, progress and badges earned.
AI Insights: Single motivating sentence that sets the users expectations of achieving their goal
Goals Copy & Details
Goals Copy & Details

Goal Details

Total saved vs target
Overall progress percentage %
Projected completion date (AI insight)
Goal milestones & badges
Actionable AI suggestions (quick AI fixes)

Budget Optimisation (Smart Savings)

Decision

Continuously surface small, safe reallocations (round-ups, category trims, one-offs) based on spending/saving signals (recurring outflows, deposit patterns, upcoming bills, goal priority).

UI

Compact agent cards with recommendation, one-line “why”, estimated impact, and single CTA (Apply / Alternatives).
Smart Savings
Smart Savings

AI Agent Suggestions

AI suggestions are visible by default to accelerate value discovery. Users can remove or disable suggestions on expansion.
Many users benefit from proactive nudges; discoverable opt-out keeps control in the user’s hands. All applied changes are logged and undoable.
Agent suggestions are modular: recommendation + short reason + 1–2 CTAs.

Filters & Discovery

Two-row chips: manual filters (Urgency, Progress, Category, Status) + AI chips (At Risk, Quick Wins, Likely to Achieve, Savings Finder).
AI chips show short tooltips and a “Why?” with top signals.
AI Chip Filters & Suggestions
AI Chip Filters & Suggestions

Workflows & Agents

A workflow is an ordered chain of agents and steps that accomplishes a user goal. It defines triggers, data flow, conditions, and outcomes (e.g., “When paycheck arrives → update goals → push summary to Slack → schedule review in Calendar”).
Agents are single-purpose AI helpers that connect to tools like Plaid, Sheets, Notion, or Calendar to act on financial data.

Essential Agents

Plaid agent - fetches transactions/balances (trigger source)
AI insights agent - summarizes, scores risk/momentum, finds savings
Sheets agent - appends/updates live ledgers
Notion agent - logs journal entries or database rows
Calendar agent - creates review/bill events
Slack agent - pushes digests/alerts to a private channel
Mail/Drive agent - stores exports / sends reports
Automation (Zapier) agents - extends to niche apps

Typical Workflow Patterns

Log + Journal: Plaid → Notion (transaction rows + AI notes).
Digest + Nudge: Plaid → AI Insight → Slack (daily summary + anomaly).
Export + Analyze: Plaid → Sheets (live ledger) → Looker/Drive.
Calendar Review: Plaid → AI Insight (large txn) → Calendar (create review event).
Auto-save: Plaid events trigger Savings Agent round-ups / transfers.
Workflows and Agents
Workflows and Agents
Creating Workflow
Creating Workflow

Onboarding Flow

The onboarding process is designed to quickly build trust and excitement by focusing on clarity, personalization, and motivation. Instead of overwhelming users with setup tasks, the flow introduces the app’s core value in 3–4 screens.
Onboarding Intro
Onboarding Intro
Account Setup
Account Setup
Loading State & Set Budget and Goals
Loading State & Set Budget and Goals

Closing Note

Designing an app where agents act on users’ finances requires balancing automation with explainability. The core win here is not just having AI find savings, it’s presenting those savings in a way that feels natural, trustworthy, and easy to act on. The design choices above make the product feel less like a finance app and more like a practical, helpful friend that keeps users’ goals on track.

Roles & Responsibilities

Product Strategy & Design - Antony Mumo
Visual Brand Design - Antony Mumo
Like this project

Posted Sep 18, 2025

Our brief was to automate useful actions with transparent AI, make goals motivating, and connect finances into the tools people already use.

Likes

2

Views

36

Timeline

Jul 1, 2025 - Sep 10, 2025

Clients

Akira

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