Meta Launches AI Agent for WhatsApp Business Globally
Meta has made its AI agent for WhatsApp Business available worldwide, according to TechCrunch. The offering allows businesses to deploy AI-powered interactions directly within WhatsApp, with pricing structured around token usage. The global rollout marks a significant expansion of Meta's commerce and communication AI offerings for business customers.
Coralogix Raises $200M to Build AI Agent Monitoring Layer
Coralogix has closed a $200 million Series F funding round, valuing the company at $1.6 billion, TechCrunch reports. The round arrives less than a year after Coralogix's previous raise and is focused on building out observability and monitoring infrastructure specifically designed for AI agents. As agentic AI systems become more prevalent in production environments, investor interest in tools that provide visibility into agent behavior and performance has grown considerably. The funding positions Coralogix to expand its platform for teams operating AI agents at scale.
Uber Caps Employee AI Spending After Exhausting Annual Budget in Four Months
Uber has introduced caps on employee AI tool spending after its allocated budget for the year was consumed within just four months, according to TechCrunch. The development follows a period in which Uber had reportedly encouraged staff to adopt and use AI tools extensively. The spending cap represents a shift toward more structured governance of internal AI usage as enterprise AI costs become a meaningful operational consideration for large technology companies.
Microsoft Releases Open Source Framework for AI Behavior Testing
Microsoft has unveiled a new open source tool called Adaptive Spec-driven Scoring for Evaluation and Regression Testing, according to TechCrunch. The framework allows developers to generate AI behavior evaluations using plain text descriptions, lowering the barrier to setting up structured evaluation and regression testing pipelines for AI systems. The tool is designed to help engineering teams more easily define, run, and iterate on tests that assess how AI models and applications behave across a range of conditions. The release reflects continued industry investment in developer tooling aimed at improving the reliability and predictability of AI in production.
Today's stories reflect continued momentum across AI agent deployment, enterprise tooling, and the infrastructure required to monitor and evaluate AI systems at scale. These developments highlight the growing operational complexity that organizations face as AI moves deeper into production environments.