AI product engineering
Whole products, not demos. Architecture, backend, front end, payments, auth and the
deployment that keeps it up — the way we built our own two.
Node.jsMongoDB
Web appsAndroid
Data pipelines & scraping
Collection at scale that doesn't fall over. Crawlers, dedup, enrichment, scheduling,
monitoring and recovery — clean structured data landing where you need it.
CrawlersETL
EnrichmentMonitoring
LLM integration & automation
LLMs inside real workflows: extraction, classification, summarisation, RAG and agents.
Self-hosted or API — chosen on cost and latency, not hype.
RAGAgents
Self-hostedEvaluation