How to De-Risk Model Performance in High Stakes Deployment

Join Encord and Mantyx for a deep-dive into de-risking AI model performance in the highest-stakes deployments: surgical robotics, autonomous systems, and defence.

In these fields, a bad model isn't a bug report. It's a catastrophe.

Data quality, annotation rigor, and human oversight aren't nice-to-haves. They're the product.

What you will leave with:

• A framework for evaluating data quality risk before models reach production
• Real annotation workflow patterns from surgical AI that translate across domains
• A cross-domain playbook for data drift, rare events, and annotation governance
• How to scale with foundation models without sacrificing traceability

Register to participate in the session live or to get a recording.