The live operational visibility and the continuous improvement loop. On any given day we can see 24 of our 27 agents active, resolving over 12,800 conversations in a 24-hour window at 94.3 % fully automated, with average CSAT at 4.8 and handle time down to 42 seconds. The voice agents in particular (Billing and Tech Support) consistently hit 96 %+ resolution with near-human quality. Being able to set a KPI and watch the system iterate toward it without constant manual tuning is the biggest differentiator.

The agents improve against the exact KPIs we set instead of staying locked at their initial performance. Once we defined resolution rate as the primary goal, Scout began iterating and the numbers moved in a measurable way without constant prompt rewriting. The voice latency is consistently low and the agents handle interruptions naturally, which makes longer, multi-party conversations feel smoother than other tools we tested.

What I like most about Giga is that it goes beyond basic conversational AI. The platform enables AI agents to understand complex workflows, take action across business systems, and continue improving based on measurable business outcomes. I particularly appreciate the focus on autonomous improvement and KPI-driven performance, rather than simply automating conversations.