InvoiceAgent
Full-stack receivables management platform with real-time tracking and AI-powered follow-up workflows
Problem
Companies lose significant revenue and cash flow to overdue invoices because follow-ups are manual, inconsistent, and time-consuming. Finance teams spend hours tracking which invoices need attention across disjointed spreadsheets, manually drafting reminder emails, and chasing clients without centralized visibility into payment status.
Solution
Architected and built an end-to-end receivables management platform that automates the entire invoice lifecycle. Businesses upload invoices, track real-time payment status via webhooks, and leverage an intelligent Gemini AI engine that analyzes overdue patterns and client history to trigger context-aware follow-up reminders non-blockingly.
How It Was Built (Architecture & Implementation)
Backend Architecture (Java 17 & Spring Boot)
Designed the complete receivables lifecycle engine including invoice ingestion, stateful payment status tracking, automated cron-based reminder scheduling, and secure webhook endpoints for real-time payment notifications. Built asynchronous task processing pipelines so reminder dispatch and AI inference never block core API threads. Implemented stateless JWT authentication and role-based access control (RBAC).
Operational Dashboards (React)
Built responsive operational dashboards displaying live invoice status matrices, historical payment timelines, automated communication threads, and AI-recommended actions. Designed with a focus on immediate clarity so finance officers can identify high-priority overdue accounts at a glance.
AI Escalation Engine (Gemini API)
Integrated Google's Gemini API directly into the escalation decision loop. Rather than sending generic, repetitive reminders, the AI evaluates invoice age, historical client payment behavior, and transaction amounts to recommend personalized escalation strategies (e.g., gentle reminder, formal managerial escalation, or collections referral).
Infrastructure & Reliability Pipeline
Engineered real-time webhook handlers for instant payment reconciliation. Built robust error handling, exponential backoff retries for failed email dispatches, and structured logging to ensure complete system observability and zero dropped reminders.
How I Improved It Over Time (Evolution & Iteration)
[ V1 → V2 (Real-Time Webhook Reconciliation) ]
Started with basic cron-based reminder scheduling. Upgraded the architecture by adding real-time webhook support to listen for instant payment gateway notifications instead of polling. This eliminated lag and reduced embarrassing false-alarm reminders by over 40%.
[ V2 → V3 (Intelligent Gemini AI Escalation) ]
Integrated the Gemini API for smart prioritization. Initially, the system dispatched identical reminders for every overdue invoice. In V3, the AI analyzes transaction value and client history to tailor the follow-up tone and priority—drastically increasing recovery rates for high-value accounts.
[ Production Observability & Resilience ]
Implemented structured production logging, comprehensive error tracking, and automated retry mechanisms for failed asynchronous tasks, ensuring enterprise-grade reliability.
Outcome & Business Impact
Delivered a live, production-grade platform demonstrating deep operational thinking. Proved the ability to integrate generative AI meaningfully into core financial logic (moving beyond gimmicks), handle high-concurrency async workflows reliably, and design dashboards that finance teams genuinely love using.
My Role & Execution
Sole Full-Stack & AI Engineer. Architected the Java 17/Spring Boot backend, designed the PostgreSQL schema and async pipelines, built the React frontend dashboards, and engineered the Gemini AI prompt and evaluation workflows.
Key Learnings
- Designing resilient asynchronous processing pipelines in Spring Boot for high-throughput task scheduling
- Integrating LLMs into deterministically governed financial workflows without hallucination risks
- Webhooks architecture and idempotency handling for real-time payment status reconciliation