Dr Gnaneshwer Jadav — AI Product & Programme Leader.

Credentials: PhD; MBA; Patent holder

— It's Gnaneshwer Jadav. I build intelligent products for complex problems.

From immunology labs to regulated digital platforms — HealthTech, EdTech, and AI systems that have to work in the real world.

Science: Pharmacy, medical biotechnology, immunology PhD.
Product: 0→1 HealthTech and EdTech platforms.
AI: Human-governed agents in regulated workflows.
Delivery: Programme leadership from roadmap to rollout.
Impact: Pilots, patents, and products that leave the lab.

Coloured-pencil illustration of Gnaneshwer kneeling beside his child, who is holding a cricket bat, with family photos and toys behind them — Off duty — family & cricketLDN

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PhD

Immunology · University of Verona, 2019

MBA

Healthcare Management · University of Kent, 2021

Patent

UK/EU healthcare management system

600+

Clinical encounters · Akeno pilot clinics

London

HealthTech · EdTech · regulated AI

Three live products

All case studies

01 / Live
Fluent Institute
EdTech · Learning
Simulation-based learning and career-readiness programmes designed around demonstrated capability, not certificates.
Read the case Visit live site
02 / Live
DeliverX
Product · Operations
Project and delivery systems for turning narrative intent into mapped, accountable execution.
Read the case Visit live site
03 / In development
Aksh Health
HealthTech · Clinical workflow
UK–India healthcare platforms: an on-premise AI layer between hospital data systems (HL7 / FHIR) and clinicians — parsing, enriching, and summarising without sending PHI to the public cloud.
Read the case Visit live site

How the work is built

All systems

01 · Operating sequence

Decide Then Build

Name the decision and the constraint before generating software. AI made execution cheap; it did not make choosing easy. The loop lives as a framework SKU on /frameworks and as a book on the shelf.

02 · Modular Orchestrated Digital Intelligence

MODI

The architecture behind Vigil-MODI: modular agents, regulation-as-code, privacy-first anonymisation, FHIR-native data, human-governed review. AI assists. It does not own the decision.

03 · Aksh Health constraint

On-prem clinical AI

Special-category health data stays on site. Ingestion (HL7 / FHIR), local inference, append-only audit. Cloud chat APIs are a non-starter for this class of problem.

Focus areas

HealthTech platforms

Regulated healthcare systems
Clinical and operational workflows
Interoperability (FHIR / HL7)
AI-assisted decision support

Research & life sciences

Research intelligence and workflow tools
Clinical trials and observational data
Responsible AI in scientific contexts

EdTech & AI product

Simulation-based learning
Career-readiness systems
LLM-assisted, human-in-the-loop workflows

If you are…

Recruiters: Scientist-operator who ships: PhD immunology, MBA healthcare, patented product work.
HealthTech & pharma: Clinical depth, FHIR / HL7, human-governed AI in regulated environments.
Founders & investors: 0→1 platforms with programme discipline — discovery through delivery.
Product & tech leaders: Decide, then build. AI as an accelerator. Humans stay in the loop.

Writing

All notes

Dr Gnaneshwer Jadav — AI Product & Programme Leader. Hello