# Niramai

**Canonical:** https://apis.io/providers/niramai/  
**Website:** https://niramai.com  
**APIs profiled:** 0

NIRAMAI Health Analytix is a Bangalore, India based deep-tech healthcare company that develops AI-powered, radiation-free breast cancer screening solutions. Its core product, Thermalytix, uses machine learning and deep learning to analyze thermal images of the chest for early-stage tumor detection, complemented by the FDA-cleared SMILE-100 thermal imaging device and the Mythri mobile screening service for primary healthcare settings. The company reports 40+ patents, 55+ clinical publications, and 500,000+ women screened across 22+ countries. Backed by 500 Global. As of this enrichment pass, Niramai publishes no public API, developer portal, SDK, or documentation surface; this profile captures its company identity and domain-security posture.

## Kin Score — 10.0 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 10.0).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 4.8 |
| Commercial Clarity | 21.1 |
| Access Clarity | 21.1 |

Regulatory layer — **Health**: 17.5 (matched via tags).

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **Niramai Domain Security** — TLSv1.3 · DMARC

## Tags

Company, Healthcare, Artificial Intelligence, Machine-Learning, Medical Imaging, Breast Cancer Screening, Diagnostics, Health Tech

---

Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/niramai/). Scores are computed from the provider's own public artifacts under a published rubric.