
Client Success Story
RAG-Powered Process Automation for a UK Fintech Platform

Project Overview
Transforming Financial Operations with Intelligent Automation
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
Strategy & Execution
RAG Architecture & UK Financial Compliance Implementation
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.

Manual Overload & Fragmented Data Challenges
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-Based Automation Solution
We delivered a RAG-based automation solution designed specifically for FinTech operations:
KEY FEATURES IMPLEMENTED:
- 01
RAG-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.
- 02
AI-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.
- 03
Secure, 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.
- 04
API-First Integration
The solution was integrated into existing systems via APIs, allowing teams to access AI-powered automation without changing their core workflows.
- 05
Production-Ready Architecture
The system was designed with scalability in mind, clear logging and monitoring, and readiness for future expansion into customer-facing AI features.
Project Interface Showcase
Client Testimonials
What Our Clients Say
Feedback on how our innovative solutions help achieve business results.

Xedrum delivered a production-ready AI-powered application within the agreed timeline and budget, including a working release on Apple TestFlight. The team was highly proactive in resolving issues, adapting to evolving requirements, and ensuring the AI functionality aligned with real user needs. Throughout the engagement, Xedrum consistently treated the project as a priority and demonstrated a strong understanding of both technical and business concerns.
Celine LeibfriedCEO at Unscripted
Xedrum successfully implemented a robust system that allows users to upload data, execute automated jobs, and retrieve results efficiently. The team delivered all components on schedule, maintained clear communication through weekly and ad-hoc meetings, and demonstrated professionalism throughout. The final solution met both technical and operational expectations.
Tomer PeretzCTO at Osirix
Xedrum's engineers worked closely with the client's project manager, integrating seamlessly into the existing workflow. The team consistently delivered planned milestones, maintained strong communication through regular online meetings, and brought a personal, collaborative approach that made them feel like an in-house AI team rather than an external vendor.
FredericCTO at Touch2Seen
Xedrum operated as an extension of the client's internal team, taking ownership of both delivery and day-to-day execution. Their engineers quickly understood the product context, collaborated across time zones, and proactively contributed ideas to improve the solution. The team maintained consistent velocity, adapted to changing priorities, and helped move the product forward without adding management overhead.
Arnon ZamirCTO at Aristo
Xedrum successfully implemented a robust system that allows users to upload data, execute automated jobs, and retrieve results efficiently. The team delivered all components on schedule, maintained clear communication through weekly and ad-hoc meetings, and demonstrated professionalism throughout. The final solution met both technical and operational expectations.
Richard BatesCEO at Acumen Data
Xedrum delivered a production-ready AI-powered application within the agreed timeline and budget, including a working release on Apple TestFlight. The team was highly proactive in resolving issues, adapting to evolving requirements, and ensuring the AI functionality aligned with real user needs. Throughout the engagement, Xedrum consistently treated the project as a priority and demonstrated a strong understanding of both technical and business concerns.
Celine LeibfriedCEO at Unscripted
Xedrum successfully implemented a robust system that allows users to upload data, execute automated jobs, and retrieve results efficiently. The team delivered all components on schedule, maintained clear communication through weekly and ad-hoc meetings, and demonstrated professionalism throughout. The final solution met both technical and operational expectations.
Tomer PeretzCTO at Osirix
Xedrum's engineers worked closely with the client's project manager, integrating seamlessly into the existing workflow. The team consistently delivered planned milestones, maintained strong communication through regular online meetings, and brought a personal, collaborative approach that made them feel like an in-house AI team rather than an external vendor.
FredericCTO at Touch2Seen
Xedrum operated as an extension of the client's internal team, taking ownership of both delivery and day-to-day execution. Their engineers quickly understood the product context, collaborated across time zones, and proactively contributed ideas to improve the solution. The team maintained consistent velocity, adapted to changing priorities, and helped move the product forward without adding management overhead.
Arnon ZamirCTO at Aristo
Xedrum successfully implemented a robust system that allows users to upload data, execute automated jobs, and retrieve results efficiently. The team delivered all components on schedule, maintained clear communication through weekly and ad-hoc meetings, and demonstrated professionalism throughout. The final solution met both technical and operational expectations.
Richard BatesCEO at Acumen Data
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Hi, I'm Danylo Melnychuk
CEO at Xedrum
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