Home / Team / Diya R.

Diya builds applied AI systems end-to-end, from data foundations through to user-facing agents. She is completing an MSc in Financial Data Science at University College Dublin, following a BA in Economics.

At an AI-native startup in London, she developed reasoning-driven multi-agent pipelines that combine semantic retrieval, topic modelling and prompt-flow orchestration to interpret founder requirements and produce structured, explainable insights. She built a voice-AI culture interviewer from scratch, integrating speech models, embeddings, and sentiment and behavioural analysis into a system designed for human-centric decision intelligence, and engineered the semantic tailoring layers that improved matching relevance and interpretability across the platform. Alongside the build itself, she standardised experimentation and documentation practices so AI deployments could be evaluated and scaled rather than shipped ad hoc.

Her work also covers the layer beneath the models. At a blockchain data intelligence platform in Dublin, she architects the data infrastructure and ontology layers that turn raw market, token and on-chain data into structured intelligence ready for downstream AI and ML use, including schema standards, validation protocols and metadata architecture. Earlier, as a thesis research assistant at UCD Smurfit Graduate Business School, she applied NLP, web scraping, and text and sentiment analysis to build a novel dataset for model testing and publication.

Sector experience

AI-native startups, blockchain and tokenised-asset data platforms, academic research, cross-functional startup execution spanning ops, engineering and R&D.

AI systems work

Multi-agent pipelines, semantic retrieval and RAG, voice-AI systems, sentiment and behavioural analysis, data ontology and metadata architecture for AI-ready datasets.

Technical skills

Education

MSc Financial Data Science, University College Dublin · BA Economics, Flame University