Micro-Business Digital Assistant — Track Sales & Expenses with AI

Ismail Hossen — Thu, 11 Sep 2025 04:55:40 +0000

This is a submission for the Google AI Studio Multimodal Challenge

What I Built

I built a Micro-Business Digital Assistant that helps small business owners keep track of their daily sales and expenses with minimal effort.

The app provides:

Sales & Expense Tracking with manual entry and AI automation.
Persistent storage in the browser (IndexedDB) so data never disappears.
Summaries & Charts to visualize financial health
Multi-language support (English + Bengali) with local currency customization

The goal was to create a lightweight, offline-first tool that works on any modern browser without requiring sign-ups, servers, or external databases.

Demo

🔗 Live Applet on Cloud Run: https://micro-business-assistant-263910167686.us-west1.run.app/

🖼️ Screenshots:

How I Used Google AI Studio

I used Google AI Studio Build mode with Gemini 2.5 Flash to handle all multimodal inputs directly in the browser:

Image input: Photos of receipts or handwritten notes are parsed into structured JSON.
Audio input: Voice memos describing sales/expenses are transcribed and extracted into records.
Text summarization: Daily summaries are generated in English or Bengali with totals and a short narrative.

Multimodal Features

Image → Data (OCR): Upload a receipt/invoice/handwritten note → AI extracts type, item, quantity, amount, and date.
Audio → Data (Speech-to-Text + NLP): Record a quick note like “Sold 3 coffees for 150 taka today” → AI transcribes and saves it as a sale.
Summaries → Narrative: Daily totals computed locally, then AI generates a localized business summary in English or Bengali.

These multimodal features make the app accessible for business owners who may not have time to type every transaction manually. They can snap a photo or record a quick voice note.

Core Features

Sales & Expense Tracking: Log and categorize all transactions.
Persistent Storage: Records saved in IndexedDB for persistence.
Manual Data Entry: Add/edit records by hand.
AI Automation: OCR for receipts, speech-to-text for audio.
Interactive Dashboard: Summaries with charts and filters.
Data Table: Paginated, with live search.
Exports: CSV and Excel reports.
Customization: English/Bengali, custom currency.
Toast Notifications and Sample Data for smooth onboarding.

This project shows how Google AI Studio’s multimodal capabilities can be used to make business tools more natural and human-friendly — turning everyday receipts and voice notes into actionable financial data.

AI Health Companion — Making healthcare information accessible for everyone.

Ismail Hossen — Tue, 09 Sep 2025 04:43:52 +0000

This is a submission for the Google AI Studio Multimodal Challenge

What I Built

I built AI Health Companion, an accessibility-focused applet designed to support patients and caregivers with three core modes:

Visual Aid: Users upload an image, and the app describes the scene in plain language, highlighting important objects and potential hazards. In addition to the text description, users can listen to the description as an audio file, making it even more accessible for people with visual impairments.
Symptom Recorder: Users record or upload a short audio clip of their symptoms. The app transcribes the speech and summarizes the key symptoms in simple terms.
Report Simplifier: Users upload a PDF or image of a lab report, and the app provides a plain-language explanation of key information with a glossary of terms. To make the experience more helpful, users can listen to the simplified explanation and also download the simplified report as a PDF for sharing or offline use.

Together, these modes address real problems faced by patients with vision loss, elderly users who communicate better verbally, and anyone struggling with complex medical documents.

Key Features

Visual Aid with audio playback: Scene description plus text-to-speech output.
Symptom Recorder: Audio-to-text transcription and symptom summarization.
Report Simplifier with audio + PDF download: Plain-language explanations that can be listened to or saved as a PDF.
Strict input limits: 5 MB max for images and 2 MB max for PDFs to stay within the Gemini free tier.
Deployed directly from Google AI Studio to Cloud Run for a seamless build-and-deploy pipeline.

Demo

🔗 Live Applet on Cloud Run: https://ai-health-companion-390658277222.us-west1.run.app/

🖼️ Screenshots:

👁️ Visual Aid

📝 Symptom Recorder

📊 Report Simplifier

How I Used Google AI Studio

I created the applet in Google AI Studio’s Build mode, where I designed and refined the prompts for each mode.
I specified structured JSON outputs directly in the system instructions to ensure reliable parsing.
Once the applet was stable, I used AI Studio’s one-click deployment to deploy it directly to Google Cloud Run.

Models Used

Gemini 2.5 Flash was the default model, chosen for speed and efficiency.
For more complex reasoning tasks (like analyzing detailed reports), the applet optionally supports Gemini 2.5 Pro if enabled.
Both models’ multimodal capabilities were leveraged for image understanding, audio transcription, and text simplification.

Multimodal Features

Image Understanding (Visual Aid): Gemini processes uploaded images to describe content, list objects, and identify hazards. Added feature: users can listen to the description as speech.
Audio Understanding (Symptom Recorder): Gemini transcribes patient voice notes and summarizes them into key symptoms.
Document + Image Understanding (Report Simplifier): Gemini explains lab reports in everyday language with glossary terms. Added features: users can listen to the simplified explanation and download the result as a PDF.

By combining image, audio, and text processing through Gemini 2.5 Flash/Pro, the applet delivers a practical, real-world healthcare companion experience that is lightweight, privacy-friendly, and accessible.

DEV Community: Ismail Hossen

Micro-Business Digital Assistant — Track Sales & Expenses with AI

What I Built

Demo

🖼️ Screenshots:

How I Used Google AI Studio

Multimodal Features

Core Features

AI Health Companion — Making healthcare information accessible for everyone.

What I Built

Key Features

Demo

🖼️ Screenshots:

How I Used Google AI Studio

Models Used

Multimodal Features