Google selected 20 AI-driven companies for its AI First Accelerator 2025 in India. Hand-picked them from over a thousand applications. And out of that entire cohort, only two startups come from healthtech.
Small in number, but big in ambition.
Meet Aignosis and Aisteth, two very different teams working on one shared goal: making early detection and frontline care faster, smarter and more accessible.
First, what exactly is Google’s AI First Accelerator?
The AI First accelerator is an initiative from Google for Startups that helps early-stage startups (typically seed to Series A) build and scale core AI/ML-powered products.
The goal is to give AI-first companies the resources, technical rigor, and ecosystem access they need to evolve from prototype to product.
It is a three-month, equity-free program that runs in multiple regions. Google has already hosted AI First cohorts in Europe & Israel, Africa, Korea, and other APAC markets.
The structure stays mostly the same everywhere: deep technical mentoring, product sprints, cloud architecture reviews, and access to Google’s AI stack.
Healthtech startups in Google’s AI First 2025 India Batch
Aignosis: Screening autism with your webcam
Founders: Raksheet Jain and Divyansh Mangal
Year: 2024
Aignosis is tackling one of medicine’s hardest and most sensitive gaps: early autism detection.
Using short video interactions, Aignosis applies AI to detect behavioural cues—gaze, expressions, subtler signals clinicians usually watch for—and flags children who may benefit from a formal neurodevelopmental assessment.
The tool lowers the barriers to an initial autism screening in regions where paediatric specialists are scarce or where waitlists are long. It does not replace a full clinical diagnosis; rather, it helps surface at‑risk children earlier so they can be referred into formal assessment and support pathways sooner.
With Aignosis, early-stage screening becomes scalable, and potentially affordable and accessible beyond big cities.
What Aignosis gets from Google
Inside the accelerator, Aignosis gets access to Google’s AI teams, cloud infra, and hands-on support to sharpen its models for accuracy, fairness and reliability.
It’ll also get guidance on data governance and regulatory readiness, absolutely essential when you’re dealing with children’s behavioural data.
This kind of support puts Aignosis in a strong position to expand beyond pilots, build clinical partnerships, and eventually explore other neurodevelopmental screenings built on multimodal AI.
Aisteth: Building AI-powered smart stethoscopes
Founders: Satish Jeevannavar and Radhakrishna Jamadagni
Year: 2018
Aisteth fuses traditional auscultation (listening through a stethoscope) with AI-powered analysis. It helps clinicians pick up subtle heart or lung sound patterns that might be missed in noisy wards, busy clinics or in settings lacking specialists.
For patients, this means earlier detection of murmurs, early-stage heart failure, respiratory issues and conditions that often go unnoticed until they worsen.
For healthcare providers, Aisteth promises a powerful safety net: a “smart stethoscope” that helps catch red flags before they escalate.
Over time, as the platform collects longitudinal data, it could also offer richer insights. Like tracking changes in heart and lung sounds over months or years, rather than relying on single snapshots.
How Google helps Aisteth scale
AI First gives Aisteth the space to refine and stress-test their deep-learning models across different environments, hardware setups and patient profiles.
Heart and lung sounds vary widely, and the model has to perform reliably everywhere, not just in perfect conditions.
With the accelerator’s network and guidance, Aisteth is also well-positioned to integrate their insights into EHRs, risk scores and telemedicine platforms, taking their tool beyond point-of-care listening into full diagnostic support.
What these startups gain from Google’s AI First accelerator
For healthtech startups like Aignosis and Aisteth, building trustworthy AI isn’t easy. Clinical data, sensitive populations (kids, patients), varied environments, regulatory scrutiny. The barrier to entry is high.
That’s where Google’s AI First programme adds real value:
- Equity-free participation
- Cloud & compute credits (often up to US$350,000 worth)
- Access to Google’s AI, ML, Cloud, and product experts: 1:1 mentoring, architecture reviews, infrastructure guidance, UX/product input, performance tuning.
- Responsible-AI & governance support
- Technical deep-dives & scaling guidance: From optimising inference cost and latency, to stress-testing models across different hardware/devices/environments.
- Go-to-market, business strategy, and investor / enterprise introductions: Connecting startups with healthcare providers, payers, regulators, investors and partners.
- Global exposure and network access: The accelerator draws participants and attention worldwide. Some startups from past cohorts have gone on to raise significant follow-on funding, scale internationally or deploy inside enterprises, showing that AI First can be a genuine springboard.
For healthtech companies, this kind of support—technical, regulatory, financial and ecosystem—can make the difference between a promising prototype and a clinically viable tool.
Wrapping up
Google, via AI First, is backing real, high-potential solutions that could transform access, affordability, early detection and frontline care in India and beyond.
With the structural, technical, and network support from Google, these tools stand a chance to be adopted, trusted, and scaled.
In a world where AI hype often outpaces impact, Aignosis and Aisteth give a glimpse of what meaningful, responsible, clinically relevant AI in healthcare can look like.
