By Montrose Software team | AI & data infrastructure
In the age of big data, scientific collaboration no longer ends at the lab door - it spans continents, disciplines, and institutions. At Montrose Software, we’ve engineered a federated, secure, and scalable data platform that’s redefining how global researchers store, share, and explore multimodal datasets.
From managing terabytes of high-resolution medical recordings to enabling real-time collaboration across nearly 1,000 academic and healthcare institutions, our work empowers discovery at scale—securely, ethically, and efficiently.
A global library for research that never sleeps
Academic and healthcare researchers are generating vast and diverse datasets: patient interviews, brain imaging videos, clinical metadata, behavioral studies, and analysis scripts. But without unified systems, these datasets become digital silos - disconnected, underutilized, and hard to govern.
We partnered with a major U.S. research institution to solve this challenge head-on. The result? A federated research platform built for high-throughput, fine-grained access to over 250 TB of data- streamed, searchable, and secure by design.
Designed for discovery, built for scale
Our platform transforms the research experience through five core pillars:
1. Seamless Federated Search
Powered by Elasticsearch and GraphQL, researchers can now explore datasets across multiple institutions through a single interface—searching metadata, transcripts, and analysis scripts in milliseconds.
2. High-Throughput Streaming
Real-time video and audio streaming reduces download times by up to 80%, with adaptive HLS/DASH delivery across edge-optimized cloud infrastructure. No more waiting hours to view research data.
3. Secure by Design
We implemented a federated authentication model using Shibboleth, OpenID Connect, and role-based access controls. Institutions maintain local identity management, while researchers enjoy seamless SSO and fine-grained access.
4. AI & MLOps Enablement
Integrated with MLflow, Kubeflow, and Jupyter, the platform lets researchers experiment, annotate, and tag datasets with AI-driven insights - without compromising governance or reproducibility.
5. Cloud-Native Foundation
Built on Django REST, PostgreSQL, and React, and orchestrated via Kubernetes and Terraform on AWS, our system is both elastic and cost-effective. We’re also enabling auto-scaling PODs to meet the demands of growing academic networks.
Real impact, real science
“Montrose transformed our platform into a secure, federated ecosystem. Researchers now stream data globally and run AI workflows - without friction.”- Director of Research Data, U.S. Academic Institution
The platform now enables:
- Secure collaboration across 1,000+ institutions
- GDPR-compliant logging and governance
- Immutable archival storage with lifecycle policies
- Self-service pipelines for transcription, emotion detection,
- HIPAA compliance
What’s next?
We're actively working on:
- Federated AI collaboration through shared notebooks and model versioning
- Auto-scaling infrastructure for per - institution deployments
- Pluggable analytics modules (e.g., behavioral coding, pattern recognition)
- Zero Trust expansion for new medical and academic networks
Build your federated research ecosystem with Montrose
We understand the complex intersection of research, compliance, and cutting-edge tech. Whether you're looking to modernize legacy infrastructure, implement AI-powered insights, or scale cross-institutional access securely - we can help.
Let’s talk. Our agile, cross-functional team is ready to co-create your next-generation data platform.