Consultant

Hey,

I’m a forward-deployed AI engineer who helps startups turn rough ideas into production-ready AI products.

I work at the intersection of AI engineering, data, and product, embedding closely with founders and teams to move from problem discovery to shipped software—fast. My focus is on agentic AI systems, retrieval-augmented generation (RAG), and vector search, built with the kind of reliability and traceability that real users and customers actually trust.

I specialise in designing and building end-to-end AI systems:
from scoping the problem and running early workshops, through architecture and hands-on development, all the way to deployment, monitoring, and iteration. I’m comfortable owning the whole stack—data pipelines, retrieval layers, agents, APIs, and deployment—without losing sight of business outcomes.

My technical background spans agentic workflows (LangGraph / LangChain), vector databases (TiDB, Qdrant), and metadata-aware RAG, with a strong emphasis on constrained outputs, evaluation, and hallucination control. I design systems that are explainable, auditable, and safe to operate in real production environments—not just impressive demos.

Alongside my AI work, I bring years of experience in consulting, business analysis, and data engineering, across construction, manufacturing, events/media, and agriculture. That grounding in real operations shapes how I build AI: pragmatic, value-driven, and designed to be adopted by non-technical users.

If you’re a startup looking to:

• turn customer pain into a working AI feature,
• build agentic systems that don’t fall apart in production,
• or move fast without cutting corners on reliability,

I’m happiest embedding with your team and helping you ship.