The AI boom continues to bring new developments and shows no sign of stopping anytime soon. Agentic AI systems are now embedded in software development, content creation, and customer support workflows in an effort to make processes more efficient with less input from human users required. The failure modes of AI agents—hallucinations, bias, harmful outputs—carry direct operational and reputational consequences for organizations using these tools. Traditional observability metrics like latency and error rates are insufficient in assessing AI quality and reliability.
What Galileo Brings to the Table
Technology leader Cisco recently announced the intent to acquire AI observability startup Galileo Technologies, Inc. in a move toward building infrastructure for AI trust and reliability. Galileo is a purpose-built platform designed to evaluate AI quality, detect failures before they reach end users, and continuously improve agent behavior in production. Designed to address agentic AI security risks that are on the rise in modern environments as organizations continue to increasingly adopt and implement AI agents.
Galileo is notable in that it covers the full agent development lifecycle (ADLC). “It is a complete solution that enables deeper insights from the earliest stages of prompt optimization and model selection, through evaluations, all the way to production monitoring, observability and enforcing guardrails,” says Kamal Hathi, Senior Vice President and GM of the Splunk Business Unit at Cisco. The platform, with its real-time observability capabilities and multi-agentic system guardrails, has been adopted as an industry standard for agentic AI trust across the enterprise. Integrating Galileo’s market-leading functionality will be a significant step in ensuring AI agent security.
Cisco's Strategic Play: Extending the Visibility Mandate
This acquisition strengthens Cisco’s Splunk Observability Cloud with real-time AI agent monitoring capabilities, expanding and reinforcing the existing functionality. Galileo enables teams to rigorously handle the full ADLC through a single platform. The deal helps Cisco in the move from network and infrastructure observability into the AI stack, representing a logical—but still significant—expansion of its platform strategy.
This move signals that AI observability is transitioning from a niche engineering concern to a core enterprise governance requirement. A major leader like Cisco making moves to acquire a full agentic AI trust and observability platform indicates a current and ongoing shift in industry priorities. The success of the era of agentic AI depends upon this growing understanding of the importance of AI agent security and trust.
The New Risk Surface: Agentic Systems at Scale
This deal is a step in the right direction in addressing many new and evolving AI risks, especially as agentic AI systems continue to grow in popularity in enterprise environments. Agentic AI ostensibly offers significant operational benefits in productivity and efficiency, empowering certain processes to be carried out by autonomous non-human identities rather than taking up the time and effort of understaffed and overworked human teams. “However, these leaps in innovation with Agentic AI are only as powerful as the trust we are able to place in them, and the quality of their outputs,” according to Hathi.
Multi-agent systems introduce compounding failure risks that single-model evaluation frameworks were not designed to handle, demanding advances in the way that organizations approach agentic AI dangers. Security, compliance, and cost exposure all increase as agentic AI operates with greater autonomy and less human oversight. Observability without guardrails is incomplete, and the Galileo model integrates detection with enforcement to better address these risks.
What This Means for Enterprise AI Strategy Going Forward
Organizations that deploy agentic AI are now facing an obligation to instrument and monitor agent behavior with the same rigor that they apply to network infrastructure. The combination of the capabilities of Cisco and Galileo raises the baseline expectation for what enterprise-grade AI deployment looks like, indicating an industry move toward prioritizing agentic AI trust and observability. As the market matures, these factors will increasingly become competitive differentiators, rather than simply operational safeguards.
