About This Session
AI applications place very different demands on inference. Coding agents reuse long context, vision-language systems process variable multimodal inputs, and generative recommendation models operate under strict latency requirements. A generic inference stack cannot maximize performance across all three. PrimaLabs delivers an application-specific inference stack engineered around each production workload. The platform jointly optimizes runtimes, kernels, caching, batching, scheduling, parallelism, and GPU infrastructure, then operates the resulting stack in an isolated environment.
Topics
- AI Models
- Agentic AI
- Infrastructure