IRD Research Lab
We study the engineering problems specific to Insurance, Healthcare, Finance, Logistics, and Retail — before we face them on a live project.
Research Areas
AI & Automation Systems
- →LLM integration patterns for document processing pipelines
- →Intelligent workflow routing and triage automation
- →AI audit trails and explainability for regulated industries
Insurance & Healthcare Engineering
- →Claims processing automation and straight-through processing
- →Patient data pipeline architecture and HL7/FHIR integration
- →Underwriting AI and risk scoring model design
Finance & Fintech Platforms
- →High-throughput transaction processing architecture
- →Regulatory compliance automation (AML, KYC, reporting)
- →Real-time risk analytics and fraud detection pipelines
Performance Engineering
- →Java / Spring Boot profiling and JVM tuning for enterprise workloads
- →Database query plan analysis and schema optimisation
- →API throughput benchmarking under sustained load
Enterprise Integration Patterns
- →Event-driven microservice orchestration with Kafka and RabbitMQ
- →Legacy system modernisation and API gateway design
- →Multi-system data synchronisation and conflict resolution
Cloud & Infrastructure Automation
- →Infrastructure-as-code templating for AWS and Azure environments
- →Zero-downtime deployment orchestration for enterprise systems
- →Cost-optimised auto-scaling models for variable workloads
Research Notes
Designing Claims Automation Pipelines
How to architect straight-through processing for insurance claims — document ingestion, AI triage, rules engine integration, and exception handling.
On Designing Systems for Longevity
Why most backend architectures fail under growth — and the structural decisions that prevent it. Covers modular service boundaries, data ownership, and interface contracts.
Practical LLM Integration in Production Pipelines
Where AI assistance genuinely accelerates enterprise workflows — and where it introduces fragility. Covers document processing, OCR post-processing, and confidence thresholding.
Java Enterprise Performance Anti-Patterns
The most common Spring Boot and JVM patterns that destroy throughput at scale — N+1 queries, connection pool exhaustion, thread contention, and lazy-loading traps.
Tools We Are Building
Select tooling developed through the IRD Research Lab — planned for public release when stable. We believe in building in public and giving back to the engineering community.
IRD Config Loader
A typed, environment-aware configuration library for Spring Boot services. Supports multiple environments, schema validation, secrets injection, and hot-reload without restarts.
Spring Audit Trail
A drop-in Spring Boot library for generating structured, tamper-evident audit logs — designed for Insurance and Healthcare compliance requirements.
PgAudit CLI
A command-line tool for analysing PostgreSQL query plans, identifying slow queries, and generating prioritised optimisation recommendations for enterprise databases.
Working on a Problem in Our Focus Areas?
We are open to research partnerships with companies and teams working on automation, AI integration, or enterprise platform challenges.
Get in Touch →