AI observability stories
Execution and escalation breakdowns now outnumber hallucinations in enterprise AI failures, according to more than 10,000 observed incidents.
The upgrades are aimed at easing bottlenecks for large AI and machine learning deployments, with clusters now scaling to 15,000 nodes.
Enterprise buyers are demanding tighter controls as AI tools move into live systems, with governance now central to deployment decisions.
The service targets firms struggling to control AI agents as they move from pilots into production and face growing security and compliance risks.
Grafana Labs has launched six AI observability tools during its AI Week, including new capabilities for monitoring and investigating AI agents.
Businesses can now run and monitor AI agents for up to seven days as Google Cloud adds tighter identity and governance controls.
Enterprise contact centres could cut queue traffic as the new platform slots into existing systems without forcing costly rip-and-replace upgrades.
Governance features aim to help security teams prove AI controls to boards and regulators as shadow AI and agentic risks spread.
The deal targets demand for governed, self-service AI environments as operators seek to turn GB200 hardware into usable services.
Rising demand for AI security helped Saviynt top USD $300 million in annual recurring revenue as enterprises seek control over non-human identities.
The release aims to help teams catch failures earlier as AI takes a larger role in coding, operations and incident response.
Enterprise demand for AI projects is driving Acceldata to expand in Europe, as firms seek sovereignty controls without lengthy data migrations.
The expanded deal aims to help customers ground AI in their own data while easing governance and cost concerns across Microsoft tools.
Security teams face higher breach costs as ThreatDown expands visibility over unsanctioned AI tools and machine accounts in one console.
The restructure puts sales and customer delivery under new leaders as enterprise buyers demand stronger governance, support and reliability from AI agents.
Growing pressure on software teams to govern AI output and costs has prompted IBM to add multi-agent tools and analytics to Bob.
Engineering teams from Nine, Xero and Canva will show how real-time data tools are being used to support AI and observability in production.
Enterprise buyers are demanding clearer returns and tighter controls as global AI spending is forecast to jump to USD $64 billion in 2026.
As AI moves into production, firms are struggling to track access, costs and policy compliance across agents and workflows.
Only 8% of organisations have agentic AI in production, highlighting the governance gap Harness aims to close with its new tools.