Future-Proof Your Research
Add new ML models, scale to larger studies, and stay at the cutting edge—no waiting required
Stay Ahead with Conduct Vision's Flexible Framework
As your research questions evolve, so does Conduct Vision. You’re never locked into outdated methods or stuck waiting for slow, third-party updates. Need to integrate a new ML algorithm, adapt to emerging data standards, or incorporate additional hardware?
No problem. Conduct Vision’s flexible framework lets you grow and innovate without costly retooling. By ensuring that your platform remains state-of-the-art, you protect your investment and keep your lab ahead of the curve.
How Conduct Vision Drives Research Growth and Innovation
At Conduct Vision, we empower researchers by providing scalable, modular solutions that adapt to ever-evolving scientific challenges. Our advanced architecture simplifies integration, accelerates updates, and ensures compatibility with cutting-edge machine learning (ML) technologies.
How Conduct Vision Stays at the Forefront of Innovation
Conduct Vision leverages standard data formats like JSON and a modular architecture that decouples the user interface (UI) from the analytics engine. This ensures seamless functionality and scalability.
Seamless Integration
Our machine-readable interfaces allow developers to implement advanced ML models and algorithms without altering client-side code. This simplifies workflows and reduces downtime.
Scalability for Growing Research Needs
Expand to larger cohorts, add complex behavior metrics, or adopt the latest machine learning techniques effortlessly.
Rapid Updates with Minimal Compatibility Issues
The decoupled design of Conduct Vision accelerates updates while maintaining stability, making it ideal for fast-evolving research environments.
No lock-ins. No dead ends. Your platform grows with you
Adopt emerging data standards effortlessly
Integrate new ML models seamlessly
Incorporate additional equipment without rewrites
Empowering Scalable, Adaptive, and Advanced Research
Scaling from a small pilot study to a large cohort analysis without redeveloping your tools
Quickly integrating a new ML algorithm for gait analysis or novel behavior metrics as they become available.
Adapting to new data-sharing standards or adding cutting-edge imaging data to your existing pipeline.
