AISpan: Runtime Security and Observability for AI Agents

AISpan is the security and observability infrastructure that production AI teams deploy between their orchestration layer and their LLM calls. As AI agents gain access to tools, APIs, databases, and external services, the attack surface expands dramatically. Prompt injection, jailbreaking, data exfiltration, and unintended tool calls are no longer theoretical risks — they are production incidents waiting to happen. AISpan intercepts every LLM request and response to enforce configurable security policies. Administrators define what tools an agent is allowed to call, what external domains it can access, and what patterns of output are flagged for review. When a policy violation occurs, AISpan can block, rewrite, or alert in real time. The observability layer captures every agent action in a structured trace format compatible with OpenTelemetry, enabling teams to debug agent behavior with the same tools they use for their API infrastructure. AISpan supports multi-agent architectures, tracking trust boundaries between agents in the same pipeline. Compliance teams get audit logs that satisfy SOC 2 and GDPR requirements for AI-generated decisions. The policy engine uses both rule-based and ML-based detection, with a feedback loop that improves detection accuracy over time. AISpan deploys as a sidecar, proxy, or SDK integration, fitting into any architecture without requiring changes to the underlying agent code. Teams running customer-facing AI features use AISpan to prevent reputation damage from errant agent behavior and to maintain the regulatory compliance that enterprise customers require.