Developing AI Accounting Software with Gemini Integration – Looking for Technical Insights

Hey everyone,

I’m part of a team at “Modified by moderator”, and we’re currently working on a next-gen AI-powered accounting software development that leverages Gemini (via Vertex AI/Gemini API) to automate, simplify, and enhance financial operations for small and mid-sized businesses.

We’re aiming to embed smart features such as:

  • Context-aware financial report generation
  • Real-time natural language query support for ledgers, invoices, etc.
  • Smart expense categorization using LLM understanding
  • Conversational AI assistant for tax, compliance, and reconciliation queries
  • AI-driven anomaly detection in transactions

Our tech stack:

  • Frontend: Flutter
  • Backend: Node.js + Firebase (Firestore/Auth)
  • AI/ML: Google’s Gemini API (in active prototyping)
  • Accounting Engine: Custom logic integrated with standard financial APIs

While the core functionality is coming together, we’re currently exploring and experimenting with Gemini for the intelligent layer — and running into a few challenges:

Designing effective prompts for financial domain-specific tasks
Managing Gemini’s streaming responses in chat-style financial assistants
Maintaining accuracy when parsing context-rich, ambiguous queries
Linking AI-generated output to real-time transactional and ledger data
Optimizing performance and cost when scaling across many users with dynamic queries

We’re building this from both an innovation and usability perspective, aiming to create a powerful tool that’s actually helpful in the day-to-day of accounting workflows.

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