Rapax - AI-native Service Assurance for Operations Automation

What happens when one line card fails?

Forty-nine alarms. One root cause. Forty-eight subscribers who don’t know yet. An OLT line card fails at Kings Garden. Every ONT behind it loses GPON signal and reports independently. Under a manual model that is an engineer reading forty-nine rows to work out they describe one event — thirty to sixty minutes before anyone knows which customers are affected.

Could you have seen it coming?

Yes. That line card ran at 91°C against a 55°C daily average, and its optical power fell from −18 dBm to −30 dBm over the three hours before it failed. The signal was there the whole time. Nobody was watching that particular metric on that particular card, because nobody can watch every metric on every card. That is what continuous monitoring is for — not dashboards for people to stare at, but agents that notice.

What does Rapax actually do?

Six AI agents, each owning a layer of network operations. FrankIntercepts incoming support tickets. Deflects what your knowledge base can answer, auto-closes routine questions, validates intake, and escalates the rest with context attached.OscarContinuous operational briefing. Removes the time managers spend joining bridges and pulling status.WadeInstitutional memory.

How do you find out if it works on your network?

You run it on your network. Rapax deploys in five days. You evaluate for thirty against success criteria you define in writing before anything is signed, for $25,000 — credited against the license if you move forward. If it does not meet them, the evaluation ends and you owe nothing further. The ask is fifteen minutes, not a demo. Book 15 minutes [email protected] Rapax X YouTube