Kernel

Semantic Kernel is a lightweight, open-source development kit that lets you easily build AI agents and integrate the latest AI models into your C#, Python, or Java codebase. It serves as an efficient middleware that enables rapid delivery of enterprise-grade solutions. Microsoft and other Fortune 500 companies are already leveraging Semantic Kernel because it’s flexible, modular, and observable. Backed with security-enhancing capabilities like telemetry support, hooks, and filters you’ll feel confident you’re delivering responsible AI solutions at scale. Version 1.0+ support across C#, Python, and Java means it’s reliable, and committed to nonbreaking changes. Any existing chat-based APIs are easily expanded to support additional modalities like voice and video. Semantic Kernel was designed to be future-proof, easily connecting your code to the latest AI models evolving with the technology as it advances.

Wafer delivers the fastest open source LLMs for enterprise through serverless and dedicated inference built for production AI workloads. Its serverless inference gives teams access to top open models with no infrastructure, no deployment overhead, and fast APIs, including GLM-5.2-Fast for low-latency inference with EAGLE speculative decoding and a per-stream throughput SLA, GLM-5.2 as a flagship model with stronger coding and reasoning capabilities, and more. Wafer’s technology uses agents that optimize inference across the stack, identifying and enhancing bottlenecks in orchestration, algorithms, serving engines, GPU kernels, and diverse hardware. It profiles the stack to see whether latency or throughput comes from scheduling, decoding, kernels, memory pressure, or hardware fit, then tries many paths and ships the measured winner. Instead of relying on a single switch or heuristic, Wafer searches model, engine, kernel, and hardware combinations.