Customer value: Visibility into LLM, GPU, and RAG cost signals on the same stack as your production metrics — before agent sprawl hits finance.
One agentic session can emit 1,000+ series where a traditional service emits ~200. Tokens, VRAM, and latency are standard OTel metrics — you get dashboards and alerts, not spreadsheet surprises.
Token counters and GPU gauges — rate and alerts like any RED chart.
VRAM and latency histograms — p95 is your UX ceiling for AI features.
Streams TCO + adoption velocity + agentic ROI — same Serverless project.
Customer value: An ROI model for agentic RCA — FTE hours saved, incidents diagnosed faster, tool overlap removed.
Ops teams spend ~40% of time investigating, not fixing. Agent Builder on metrics + logs + traces quantifies what you get back — then you prove it live on the same Horizon Media and Aether Games stack.
Team size, incidents/month, mean time to diagnose — tune to your account.
Conservative ranges — stress-test before the executive readout.
Not a roadmap slide — Agent Builder on production-shaped data.
Customer value: A leadership-ready response plan — agentic observability as a 2026 evaluation criterion, demonstrated on your stack.
“We already have AI” and “it’s a science project” are ROI questions. You answer with Gartner Agentic Observability recognition, live Agent Builder, and the consolidation + velocity story from Horizon Media.
Science project → production agent on Serverless today.
Agentic Observability in 2026 MQ — rare vs point tools.
TCO → velocity → agentic ROI — one account, one platform.