Evaluating large language models within a multi-agent system using real-world data from opioid treatment programs

Nimblemind’s evaluation reveals how a carefully trained MedGemma model can avoid the memorization traps that undermine clinical reliability.

IN-cube at Nanyang Technological University uses NimbleLabs to uncover patterns of online information exchange that shape public trust and engagement in Singapore.

How Nimblemind built a secure, compliant, and cloud-agnostic platform for clinical AI spanning AWS, GCP, Azure, and on-prem hospital environments.

A lightweight healthcare agent designed to make clinical data enrichment accessible to healthcare data scientists, researchers, and students.

How wearable devices and AI are helping providers predict pain spikes, prevent relapse, and transform care for patients with opioid use disorder.

Turning raw clinical data into explainable, privacy-safe predictions – no manual work required.

How a small minority of Telegram users spreads conspiratorial health content—undermining trust, driving costs, and reducing engagement across healthcare systems.

Nimblemind.ai announced funding to accelerate its mission to advance human health by making healthcare data accessible and useful.