Martyns Nwaokocha

Background

The engineer behind Nodeworks

I specialise in knowledge graph engineering: designing graph data models, building ingestion pipelines, writing Cypher and Gremlin queries, and delivering complete implementations from raw data to production graph database to API to dashboard.

My day-to-day work has involved Neo4j, Amazon Neptune and Memgraph in production settings: performance tuning, entity resolution, taxonomy graphs, search infrastructure, and LLM-backed applications on top of graph context.

On the data side: Apache Airflow and AWS MWAA for pipelines, OpenSearch and Elasticsearch for search (including dense vector search), Power BI and Grafana for dashboards, and AWS Lambda, S3 and Bedrock for cloud infrastructure.

On the web side: hand-written static sites, Next.js, FastAPI backends, and native Android. Streamlit for data applications. SEO bundled or standalone.

Why Nodeworks

The graph database consultancy market in the Czech Republic changed in August 2026 when the leading independent Czech Neo4j specialist was acquired by Neo4j, Inc. That created a gap for vendor-neutral, independent knowledge graph work. Nodeworks fills it.

Vendor-neutral matters in this space. Neo4j is the dominant database, but Amazon Neptune, Memgraph and other graph platforms have real production strengths. Advice that is not tied to a vendor reseller arrangement is worth something.

How I work

Everything starts with understanding the actual problem. I do not recommend a graph database, a RAG pipeline or a custom web build without first establishing that it is the right solution. If it is not, I will say so.

Projects are scoped in writing before any work starts. The proposal includes deliverables, timeline and a fixed fee. Changes to scope are handled as separate written agreements, not verbal adjustments.

I work in English and Czech. Most collaboration is remote, but in-person meetings are available in Brno and Prague.