Question 1

What role does OpenSIPS play in real-time analytics for AI contact centers?

Accepted Answer

OpenSIPS operates at the SIP control layer, where it can observe call signaling, routing decisions, and state changes as they happen. This allows analytics to be generated during live calls, rather than relying on post-call records.

Question 2

How is real-time analytics different from traditional call reporting?

Accepted Answer

Traditional analytics focus on what happened after a call ends, using CDRs and logs. Real-time analytics surface live call signals while the conversation is still active, enabling routing changes, AI decisions, and escalations in the moment.

Question 3

How can OpenSIPS analytics reduce AI decision latency?

Accepted Answer

OpenSIPS reduces AI decision latency by exposing call events at the SIP layer, before media processing or application logic introduces delays. Because AI systems receive signals earlier in the call flow, they can react immediately instead of waiting on delayed data pipelines.

Question 4

Can enterprises add real-time analytics without replacing their existing voice stack?

Accepted Answer

Yes. OpenSIPS can be introduced as an analytics-enabling layer in front of existing carriers, SBCs, media servers, and AI platforms. This allows enterprises to add real-time visibility without disrupting stable voice infrastructure.

Question 5

How does OpenSIPS analytics scale with high call traffic?

Accepted Answer

OpenSIPS scales analytics alongside SIP traffic by using lightweight event handling and horizontal scaling. Each instance generates telemetry locally, which avoids central bottlenecks and keeps analytics responsive during traffic spikes.

openSIPs Solution Developer

How OpenSIPS Supports Real-Time Analytics for AI Contact Centers