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•Case study
RAG-Powered Process Automation for a Fintech Platform
A RAG-powered automation layer that enables teams to retrieve accurate information, automate internal workflows, and reduce manual processing across finance and operations.
FinTech
London, UK
3 months
$15K
•Case study
Our Approach
We approached this project as a FinTech-grade AI automation initiative, where accuracy, traceability, and security were as important as AI capability.
Our approach focused on: Designing a Retrieval-Augmented Generation (RAG) architecture to ground AI responses in verified internal data.
Automating repetitive operational workflows using AI-assisted decision support.
Ensuring the solution aligned with UK financial and compliance expectations.
Delivering incremental value through automation, rather than replacing core systems.
Instead of building a standalone AI feature, we embedded RAG directly into existing workflows to act as an intelligent operations layer.

The Problem
As the FinTech platform grew, teams faced several challenges: Key information was fragmented across databases, internal documentation, and reports.
Operations and finance teams spent significant time manually querying data and preparing summaries.
Compliance-related questions required cross-checking multiple sources.
Existing tools were powerful but not easily accessible to non-technical users.
The client needed a way to automate data retrieval and decision support without exposing sensitive systems or introducing compliance risks.
RAG-Powered Knowledge & Data Retrieval
AI-Assisted Process Automation
Secure, Controlled AI Access
RAG-BASED AUTOMATION SOLUTION
We delivered a RAG-based automation solution designed specifically for FinTech operations:
KEY FEATURES IMPLEMENTED:
- 01RAG-Powered Knowledge & Data Retrieval
We implemented a RAG pipeline that retrieves structured data from internal databases, operational documentation and policies, and process-level metadata. The AI generates responses and summaries strictly grounded in retrieved sources, ensuring accuracy and auditability.
- 02AI-Assisted Process Automation
The system supports automation of internal operational queries, finance and reconciliation checks, and compliance-related information requests. This reduced manual effort and response time for recurring internal requests.
- 03Secure, Controlled AI Access
We implemented strict controls to ensure role-based access to data, separation between AI reasoning and data execution layers, and traceable outputs suitable for regulated environments.
- 04API-First Integration
The solution was integrated into existing systems via APIs, allowing teams to access AI-powered automation without changing their core workflows.
- 05Production-Ready Architecture
The system was designed with scalability in mind, clear logging and monitoring, and readiness for future expansion into customer-facing AI features.
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