Sedai launches an “autonomous” AI agent optimization platform for enterprises

What changed: Sedai published a product launch for “AI Agent Optimization,” a platform that sits between agents and model providers to route queries across OpenAI, Anthropic, Vertex AI, Bedrock and others, with per‑org performance judging, cost/latency observability, and automated model routing. The company released the announcement on June 9, 2026 and said early access is available now.

Why it matters: Builders operating many specialized agents (customer support, billing, search, automation) get a practical way to reduce token and cloud spend while preserving accuracy by routing different query classes to different models and enforcing governance without re‑engineering each agent. That’s useful for small teams that can’t continuously benchmark every new model release.

Try/watch: Evaluate Sedai (or comparable model‑routing tools) in a controlled pilot by instrumenting a low-risk agent path (e.g., FAQs or order-status lookups) to measure real cost, latency, and correctness tradeoffs before widening deployment. Monitor how the platform’s “custom judge” matches your business’s definition of accuracy.

Zscaler expands Project AI‑Guardian to add partner integrations for securing agentic workflows

What changed: Zscaler announced an expansion of Project AI‑Guardian that integrates its Zero Trust Exchange with a set of technology partners (including OpenAI, Google Cloud, Databricks, Equinix and others) to map identities, applications, agents, and data, and to apply continuous policies and data protections across AI interactions. The press release published June 9, 2026 described new AI‑access graphing, attack surface modeling, and partner signal‑sharing.

Why it matters: Operators and security-conscious buyers deploying agentic systems can use these integrations to detect shadow agents, enforce granular access rules, and prevent sensitive data from being exposed to models or autonomous agent flows; that capability addresses practical regulatory and breach-risk concerns when agents interact with corporate systems.

Try/watch: If you’re deploying agents that touch customer data or internal systems, add an inventory step to identify where agents call external models and evaluate whether your security stack can enforce per‑agent permissions and data filters; prioritize integrations that provide real‑time blocking and audit trails.