completed
Audit Trail ComplianceZero-Latency ReconciliationEnterprise Role RBAC

Sahayak PFMS

Enterprise financial management system with real-time auditing, role-based access, and automated workflow pipelines

Role

System Architect

Timeline

December 2025

Infrastructure

Dockerized Microservices on AWS, Managed Kafka

01. The Problem

Government and enterprise financial systems often suffer from lack of transparency, slow manual reconciliation, and poor auditing capabilities. Sahayak was built to digitize and automate these complex financial workflows.

02. Architecture

The system uses a microservices architecture with a Go-based core engine for financial logic and a Next.js dashboard for administration. Kafka is used for asynchronous auditing and notification triggers.

03. Tech Stack

Next.js
Go
Go
PostgreSQL
Kafka
RE
Redis
DK
Docker
TypeScript
Tailwind CSS

04. Optimization

Implemented Go-routine based parallel reconciliation workers

Used Kafka topics to decouple critical payment paths from non-critical logging

Database partitioning for multi-year financial data storage

Sahayak PFMS: Financial Transparency at Scale

Sahayak is more than just a dashboard; it is a full-featured Financial Management System designed for high-stakes environments.

Core Engineering

Financial Ledger Engine

Built in Go, the ledger engine handles every transaction with strict ACID compliance. We used the Saga pattern for distributed transactions to ensure that if any step fails in a complex multi-stage payment, the entire system rolls back to a safe state.

Asynchronous Auditing

Every action in the system is published to a Kafka topic. A dedicated auditing service consumes these messages to build an immutable audit trail, ensuring 100% compliance without affecting the performance of the main transaction flow.

Product Impact

Sahayak reduced manual reconciliation time by over 80% during beta testing, proving that modern engineering can solve legacy bureaucratic bottlenecks.

Challenges

  • Handling complex role hierarchies with granular permissions

  • Ensuring data integrity across multiple microservices

  • Designing a system that remains performant with millions of ledger entries

Learnings

  • Designing for extreme data consistency

  • Implementing complex RBAC systems from scratch

  • Managing enterprise-scale Go backends

Design & Developed by Pratham Ranka
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