--- title: "Workers AI" description: "4 posts about Workers AI, summarised, each linking to the original." --- # Workers AI > 4 posts about Workers AI, summarised, each linking to the original. ## Articles ### [Introducing Clef-omni with full multimodality, plus a faster Clef and a cheaper Clef-flash](https://yomu.fyi/post/introducing-clef-omni-with-full-multimodality-plus-a-faster-clef-and-a.md) - Company: [Cloudflare](https://yomu.fyi/company/cloudflare.md) - Author: Kevin Jain - Published: Oct 9, 2026 - Type: Announcement Cloudflare introduced Clef-omni, a decision model that natively handles audio, video, image, and text inputs in a single pipeline, built on a Qwen3-Omni mixture-of-experts backbone with text-to-speech components removed. Unlike cascading pipelines, it directly embeds media into a unified sequence and uses two-stage attention routing with lexical grammar to compute confidence scores, trained by freezing the backbone and applying LoRA adapters with label-smoothed cross-entropy and Brier score calibration. The company also cut Clef-flash’s price to $0.038 per million input tokens while reducing its context window from 64k to 24k for the hosted version, based on usage data showing only 0.24% of requests exceed that limit. Clef’s hosted version received speed optimizations at the infrastructure layer without new model weights, and Clef-omni is available open-weight on HuggingFace. Benchmarks show Clef-omni scoring 98.2 on BFCL case exact and 92.7 on API-Bank accuracy, with median text-only decision latency around 130 milliseconds. ### [Building an evidence-grounded agentic security operations harness on Cloudflare](https://yomu.fyi/post/building-an-evidence-grounded-agentic-security-operations-harness-on-c.md) - Company: [Cloudflare](https://yomu.fyi/company/cloudflare.md) - Author: Blake Darché - Published: Oct 7, 2026 - Type: Problem & solution Cloudflare’s Managed Defense harness uses a team of specialized AI agents to analyze security alerts, separating deterministic evidence collection from model inference to improve accuracy. Before any AI analysis, fixed reconnaissance workflows collect customer identity, detection history, traffic baseline, and enforcement outcomes, making evaluation reproducible. A lightweight triage model called Clef filters high-confidence false positives, while a coordinator agent runs four specialist agents in parallel for deeper investigation. The specialist agents cover traffic analysis, customer context, global telemetry, and threat intelligence, with a synthesis agent combining their typed findings into an advisory. The system preserves customer privacy by using only aggregate global telemetry, and Managed Defense Analysts remain responsible for final decisions and mitigations. The approach addresses three problems from a single-agent prototype: context becoming authority, scope drift, and failure to distinguish missing data from negative results. ### [Building for good: How civil society organizations are automating on Cloudflare](https://yomu.fyi/post/building-for-good-how-civil-society-organizations-are-automating-on-cl.md) - Company: [Cloudflare](https://yomu.fyi/company/cloudflare.md) - Author: Jocelyn Woolbright - Published: Oct 2, 2026 - Type: Announcement Cloudflare awarded $7.5 million in credits to 30 civil society organizations to build automation tools using Workers AI and AI Gateway on its global network. LebTown replaced manual editorial workflows with a custom management system, and Kaya Guides built a WhatsApp mental health app processing 500,000 messages monthly with real-time counselor feedback. Larger groups like Freedom House and Article One received volunteer engineering support to build tools for tracking transnational repression and assessing human rights risks from factory audits. Cloudflare’s developer services include automatic DDoS protection and data minimization, addressing privacy and cost barriers that have limited AI adoption in the sector. The program is now open for a second cohort of non-profit organizations to apply for up to $250,000 in credits. ### [Introducing Clef: our open-source decision models, and new RL fine-tuning platform](https://yomu.fyi/post/introducing-clef-our-open-source-decision-models-and-new-rl-fine-tunin.md) - Company: [Cloudflare](https://yomu.fyi/company/cloudflare.md) - Author: Kevin Flansburg - Published: Oct 1, 2026 - Type: Announcement Cloudflare released two open-source decision models, Clef and Clef-flash, hosted on Workers AI under an Apache 2.0 license and fully compatible with the Jev API. These models produce bounded structured outputs for agentic workflows, classifying inputs like customer support messages or website domains with typed probabilities and confidence scores. Clef includes a vision encoder and a 64k context window, distinguishing it from text-only decision models such as Jev, and currently leads the Jev Decision Index benchmark. The models demonstrated lower latency than alternatives, with Clef classifying a website in 2.2 seconds versus 4.7 seconds for Cloudflare’s fastest general LLM, while Clef-flash offers even faster inference at 38.8 ms median latency. Cloudflare also debuted a reinforcement learning fine-tuning platform that lets customers adapt Clef to their specific use cases using their own data.