Resonance Holdings
2025
AI-driven market intelligence products — data exploration, relationship mapping, and contextual insights.
Overview
Full-Stack Developer at Resonance Holdings, 2025, working on the data model, APIs, and cloud infrastructure behind the product's market-intelligence features.
Problem
Market intelligence is fundamentally about relationships — between companies, events, and signals — not just records in isolation. The data model and APIs needed to make those relationships queryable, not just stored.
Role & ownership
Designed and tuned Neo4j graph models and Cypher queries for relationship-based search, filtering, and analytics, and set up the AWS infrastructure serving them.
Architecture
Graph models and Cypher queries in Neo4j power relationship-based search, filtering, and analytics — connecting entities the way the underlying relationships actually work, rather than flattening them into rows.
Proprietary and third-party AI models feed into the data pipeline to improve recommendations.
AWS infrastructure — EKS, S3, Lambda, and API Gateway — serves the pipeline and APIs securely at scale.
Technical decisions
Decision
Neo4j graph model over a relational schema
Market intelligence is relationship-heavy — Neo4j and Cypher let relationship-based search and filtering run as native graph traversals instead of multi-table joins.
Decision
AI models integrated directly into the data pipeline
Feeding proprietary and third-party AI models into the pipeline, rather than bolting them on as a separate downstream step, let recommendations use relationship context from the graph directly.
Trade-offs
Trade-off
Graph database over relational
A graph database fits relationship-heavy queries well, but it's a less familiar operational surface than relational stores, and not every part of the product's data is naturally graph-shaped.
Outcome
- Neo4j graph models and Cypher queries live for relationship-based search, filtering, and analytics.
- Proprietary and third-party AI models integrated into the data pipeline to improve recommendations.
- AWS infrastructure (EKS, S3, Lambda, API Gateway) set up for secure, scalable deployment.