ainmayHealthcare AI

AI that healthcare
can trust.

AI advisory and delivery for healthtech, wellness, hospitals, labs and life sciences.

Book a consultationHow we work
ComplianceDesigned to meet
  • HIPAAUS health privacy
  • DPDP ActIndia data protection
  • GDPREU data protection
  • ABDMIndia digital health
  • ISO 27001Information security
  • SOC 2Security controls

We work with hospitals and labs, health and wellness apps, healthtech platforms, life sciences and insurers: anyone putting AI in front of patients, users or health data. Then we build what the evidence supports.

What we build

Products people actually use.

We don't stop at strategy. These are the kinds of systems we design and ship, with review, explanation and monitoring built into the interface itself.

Encounter · 14:32Awaiting clinician review
Transcript“Tightness in my chest since Monday. It's worse on the stairs.”
Chief complaintExertional chest tightness, 3 days
PlanECG, troponin, cardiology review
Every line linked to sourceApprove note
Clinical documentationDrafts that clinicians approve, with nothing written that can't be traced back to the conversation.
Health assistantGuardrails on
I've had a headache for three days and I feel dizzy.I can help you decide on next steps. Is the headache sudden and severe, or do you have any vision changes?
Red-flag symptoms checkedAnswers grounded in approved content
Escalates to a clinician when unsureBook a doctor
Health assistants and chatbotsConversational AI with guardrails, escalation paths and every answer grounded in approved content.
Recommendation model · v2.3Within threshold
0.91AUROC · last 30 days
Data driftLow
Fairness checkPassed · 6 groups
Next governance review12 Oct
Recommendations and monitoringRecommendation engines watched after launch, with drift, fairness and review dates in one place.

Illustrative interfaces. Client work is shared under NDA.

What we do

Four practices. One accountable partner.

Where AI will create measurable value in your organisation, what it will take, and the order to do it in.

  • Opportunity and readiness assessment
  • Prioritised use-case portfolio with business cases
  • Board-ready roadmap and investment plan
Explore this practice
Our approach

Evidence first. Enthusiasm second.

  1. 01

    Assess

    Understand your goals, data, systems and constraints, and where AI can genuinely help.

  2. 02

    Prioritise

    Rank opportunities by value, feasibility and risk. Agree success measures up front.

  3. 03

    Validate

    Prove performance and safety on your data, with clinicians, users and operators in the loop.

  4. 04

    Deploy & govern

    Put it into production, monitor it, and keep it compliant as models and rules change.

“In healthcare, AI has to be as trustworthy as the people who use it. That is the standard Ainmay is built to.”
AinmayAbout Ainmay →

Building or buying AI for health?

Book a confidential 30-minute consultation. We'll tell you where AI fits, what it will take, and what we'd advise against.

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