About Thinking Tensors

Thinking Tensors is a small research, consulting, and education studio with a focus on safe, transparent, and useful AI—especially for healthcare and regulated environments. We help teams move beyond hype and build practical GenAI workflows that are grounded in real-world constraints: governance, clinical risk, security, and adoption by busy staff.

Our work typically falls into three tracks:

  • Education & enablement: workshops and learning products that help teams understand what GenAI can realistically do, how to evaluate it, and how to use it responsibly.
  • Design & prototyping: rapid proofs-of-concept (e.g., RAG-enabled drafting workflows, document triage, decision support) built with minimal sensitive data and strong guardrails.
  • Governance & delivery support: DPIA-aware design, evaluation plans, documentation, and implementation guidance across common cloud platforms.

We aim to make AI less magical and more measurable: clear problem statements, clear risks, clear success criteria—and systems people can trust.

What clients typically hire us for
  • GenAI workshops for clinicians, product teams, and risk/compliance stakeholders
  • Safe workflow prototypes (RAG + templating + human sign-off)
  • Evaluation plans for prompts, retrieval quality, and output reliability
  • Data governance support for UK/EU environments (healthcare-aware)
  • Technical delivery advice across AWS/Azure/GCP (IaC, containers, maintainable systems)

About the team

Ashray Shetty

Education & Applied AI

Ashray’s background spans neuroscience and translational medicine, followed by years designing and delivering data education programmes for working professionals. He focuses on building practical training, turning complex AI topics into usable workflows, and helping organisations adopt GenAI in a way that’s safe, transparent, and aligned with real operational needs.

Prak Shetty

AI/ML Research & Healthcare Systems

Prak is an AI/ML researcher and educator working at the intersection of generative AI, digital healthcare, and recommendation systems. He has experience with building proof-of-concepts for AI systems using RAG pipelines, hybrid ranking approaches, and strong prompt engineering practices—alongside hands-on delivery in healthcare technology environments and stakeholder-facing work within NHS.